Papers by Ahmed A . Salama
Network security become imperative in the context of our interconnected networks and everyday com... more Network security become imperative in the context of our interconnected networks and everyday communications. Recently, many deep learning models have been proposed to tackle the problem of predicting intrusions and malicious activities in interconnected systems. However, they solely focus on binary classification and lack reporting on individual class performance in case of multi-class classification. Moreover, many of them are trained and tested using outdated datasets which eventually impact the overall performance. Therefore, there is a need for an efficient and accurate network intrusion detection system. In this paper, we propose a novel intelligent detection system based on convolutional neural network, namely DCNN. The proposed model can be utilized to efficiently analyze and detect attacks and intrusions in intelligent network systems (e.g., suspicious network traffic activities and policy violations). The DCNN model is applied against three benchmark datasets and compared with state-ofthe-art models. Experimental results show that the proposed model improved resilience to intrusions and malicious activities for binary as well as multi-class classification, expanding its applicability across different intrusion detection scenarios. Furthermore, our DCNN model outperforms similar intrusion detection systems in terms of positive predicted value, true positive rate, F1 measure, and accuracy. The scores obtained for binary and multi-class classifications on the CICIoT2023 dataset are 99.50% and 99.25%, respectively. Additionally, for the CICIDS-2017 dataset, DCNN attains a score of 99.96% for both binary and multi-class classifications, while the CICIoMT2024 dataset attains a score of 99.98% and 99.86% for binary and multi-class classifications, respectively.
Neutrosophic Sets and Systems, 2025
It is well known that the term vagueness is spread in all aspects of our lives, this
manuscript ... more It is well known that the term vagueness is spread in all aspects of our lives, this
manuscript will clarify the meaning of independence (strict meaning of independence, the illusory
meaning of independence, Oscillating between the true meaning of independence, and the fallacy of
claiming independence and not applying it), this triplet actually refers to the three components that
the Neutrosophic theory standing on which is (truthiness, falsity, indeterminacy), the strategy of
applying the notion of independency in the local institutions, enlighten on the allegation of
applying the independency notion in some governments’ institutions without a real impact of this
term, and studying the meaning of independence from the perspective of a country legal system, all
these issues and some comparisons in applying the term (independency) between some countries
such as Iraq, France, Algeria, USA, etc. have been enclosed in this article.
Neutrosophic Sets and Systems, 2025
Decision-making in medical diagnosis is often hampered by uncertainties due to
incomplete, ambig... more Decision-making in medical diagnosis is often hampered by uncertainties due to
incomplete, ambiguous, and evolving information. In reviewing the traditional methods for lung
cancer detection, we found that crisp and logic values have more difficulties and challenges. These
challenges related to the big data analytics, uncertainty values, and the different circumstances that
make it harder for prediction. In this work, we propose a novel approach that use a Neutrosophic
Topological Spaces (NTS) for the lung cancer detection in the chest X-ray images. Furthermore, the
proposed NTS leverage the strengths points of Neutrosophic Sets (NS) which include the degrees of
truth (T), indeterminacy (I), and falsity (F). The proposed model provides more informative results
about the uncertainty cases compared with the traditional methods. The results indicated that the
proposed NTS approach achieved highest accuracy reached to 85.5% with a sensitivity 88.2%,
specificity 82.1%, and AUC 0.91. which mean that the proposed NTS approach are more reliable and
efficient than traditional methods for uncertainty.
Computational Intelligence and Neuroscience, 2021
Cardiotocography data uncertainty is a critical task for the classification in biomedical field. ... more Cardiotocography data uncertainty is a critical task for the classification in biomedical field. Constructing good and efficient
classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. *e proposed
neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation
algorithm. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural
networks but also to achieve a better performance than the other algorithms. *e experimental results visualize the data using the
boxplot for better understanding of attribute distribution. *e performance measurement of the confusion matrix for the
proposed framework is 95.1, 94.95, 95.2, and 95.1 concerning accuracy rate, precision, recall, and F1-score, respectively. WEKA
application is used to analyse cardiotocography data performance measurement of different algorithms, e.g., neural network,
decision table, the nearest neighbor, and rough neural network. *e comparison with other algorithms shows that the proposed
framework is both feasible and efficient classifier. Additionally, the receiver operation characteristic curve displays the proposed
framework classifications of the pathologic, normal, and suspicious states by 0.93, 0.90, and 0.85 areas that are considered high and
acceptable under the curve, respectively. Improving the performance measurements of the proposed framework by removing
ineffective attributes via feature selection would be suitable advancement in the future. Moreover, the proposed framework can
also be used in various real-life problems such as classification of coronavirus, social media, and satellite image
Neutrosophic Sets and Systems, 2018
In this paper, we propose a new technique for the enhancing images. It will work on removing the ... more In this paper, we propose a new technique for the enhancing images. It will work on removing the noise contained in the image as well as improving its contrast based on three different enhancing transforms, we commence by embedding the image into a neutrosophic domain; where the image will be mapped in three different levels, a level of trueness, a level of falseness and a level of indeterminacy. Hence, we act separately on each level using the enhancement transforms. Finally, we introduce a new analysis in the field of analysis and processing of images using the neutrosophic crisp set theory via Mat lab program where has been obtained three images, which helps in a new analysis to improve and retrieve images.
Neutrosophic Sets and Systems, 2024
Environmental data analysis often faces uncertainties in measurements. Cubic Bipolar
Neutrosophic... more Environmental data analysis often faces uncertainties in measurements. Cubic Bipolar
Neutrosophic Sets (CBN Sets) provide a powerful framework to address this challenge. This paper
explores the mathematical foundations of CBN Sets and highlights their practical applications
through illustrative examples. We demonstrate how CBN Sets effectively capture varying degrees of
certainty, possibility, and impermanence in environmental parameters. The concept of inclusion
relations facilitates comparisons and information fusion. Fundamental set operations (intersection,
union, complement) are explored for manipulating and analyzing uncertain environmental data. We
present the application of CBN Sets in water quality assessment, highlighting their ability to analyze
parameters while accounting for measurement uncertainties. The potential for air quality monitoring
using CBN Sets is also discussed. Finally, distance measures and similarity coefficients are introduced
to quantify relationships between air quality characteristics from different stations. By leveraging
CBN Sets and their associated operations, researchers can gain a more nuanced understanding of
environmental data, enabling informed decision-making for a healthier planet.
Neutrosophic Sets and Systems, 2025
We developed an information system using an object-oriented programming language
and a distribu... more We developed an information system using an object-oriented programming language
and a distributed database (DDB) consisting of multiple interconnected databases across a computer network, managed by a distributed database management system (DDBMS) for easy access. An intelligent system was designed to assess the difficulty level of preliminary exams and select top-performing advanced students using a Neutrosophic Deep Learning Model. The dataset was randomly split into training (80%) and testing (20%) sets, and the model, trained with the Adam optimizer at a 0.001 learning rate over 50 epochs, incorporated early stopping based on validation loss. This system, implemented at a traditional Egyptian university, achieved a 95% accuracy in predicting student dropout. Student behavior, influenced by personal, environmental, and academic factors, is often evaluated subjectively, leading to inconsistent results. Traditional machine learning approaches struggle with the inherent uncertainty in behavioral data. To address this, we combined neutrosophic theory—a mathematical framework that accounts for truth, falsity, and indeterminacy—with deep learning, which excels at learning complex data relationships, to predict student outcomes such as dropout rates. Evaluating the model on student data, including
attendance and grades, showed superior accuracy, achieving a determination coefficient of 0.95,
demonstrating the approach's potential for identifying at-risk students and enabling targeted
interventions.
Neutrosophic Sets and Systems, 2024
Smartphones contain a vast amount of information about their users, which can be used as evidence... more Smartphones contain a vast amount of information about their users, which can be used as evidence in criminal cases. However, the sheer volume of data can make it challenging for forensic investigators to identify and use the most relevant information. Neutrosophic logic is a generalization of fuzzy logic that allows for uncertainty and vagueness, making it a more potent tool for dealing with the ambiguity of real-world data. The proposed framework aims to identify and utilize the most relevant information for forensic investigators, making it easier to solve criminal casesusing Neutrosophic logic. This novel approach provides a more powerful tool for dealing with the ambiguity of smartphone data, ultimately improving the accuracy and effectiveness of forensic investigations. Our research has utilized Neutrosophic logic to evaluate the degree of truth, falsity, or Indeterminacy of this information. Additionally, this study analyzes conversations between individuals using Excel’s fuzzy lookup add-in to determine the percentage of truth and false in each conversation. The results were compiled into a dataset and utilized a Neutrosophic Python code to evaluate the information. The results indicate the percentage of truth, false, and Indeterminacy in each conversation and which can be used to determine its admissibility as evidence and which not.
Neutrosophic Sets and Systems, 2024
This paper presents a novel approach known as Neutrosophic Fuzzy Power
Management (NFPM) aimed ... more This paper presents a novel approach known as Neutrosophic Fuzzy Power
Management (NFPM) aimed at addressing the critical challenge of uncertain energy availability in
Energy Harvesting Sensor Networks (EHWSNs). The main objective of this research is to enhance
the management of energy resources within these networks, which traditional fuzzy logic methods
often fail to do, leading to power failures and reduced reliability. NFPM utilizes neutrosophic logic
to effectively model uncertainty by representing the degrees of truth, indeterminacy, and falsity of
both harvested and residual energy levels. Through a fuzzy inference system, NFPM dynamically
allocates energy budgets for each time slot based on these neutrosophic sets, resulting in more
adaptive and conservative energy distribution. The results are validated through numerical
examples and extensive simulations, demonstrating NFPM's superiority over traditional fuzzy
logic, with significant improvements such as a 25% reduction in power failures, 95% enhanced
network connectivity, a 15% increase in data transmission success rates, and overall improvements
in energy efficiency and robustness to fluctuations and noise. This research establishes NFPM as a
promising solution to the uncertainties inherent in EHWSNs. Future research directions include
exploring the integration of NFPM with machine learning algorithms for predictive energy
management, assessing its scalability in larger networks, and examining its applicability in other
domains requiring energy management under uncertainty.
Studies in Systems, Decision and Control, 2022
To facilitate timely treatment and management of COVID-ap patients, efficient and quick identific... more To facilitate timely treatment and management of COVID-ap patients, efficient and quick identification of COVID-19 patients is of immense importance during the COVID-19 crisis. Technological developments in machine learning (ML) methods, edge computing, computer-aided medical diagnostic been utilized for COVID-19 Classification. This is mainly because of their ability to deal with Big data and their inherent robustness and ability to provide distinct output characteristics attributed to the underlying application. The contrary transcription-polymerase chain reaction is currently the clinical typical for COVID-19 diagnosis. Besides being expensive, it has low sensitivity and requires expert medical personnel. Compared with RT-PCR, chest X-rays are easily accessible with highly available annotated datasets and can be utilized as an ascendant alternative in COVID-19 diagnosis. Using X-rays, ML methods can be employed to identify COVID-19 patients by quantitively examining chest X-rays effectively. Therefore, we introduce an alternative, robust, and intelligent diagnostic tool for automatically detecting COVID-19 utilizing available resources from digital chest X-rays. Our technique is a hybrid framework that is based on the fusion of two techniques, Neutrosophic techniques (NTs) and ML. Classification features are extracted from X-ray images using morphological features (MFs) and principal component analysis (PCA). The ML networks were trained to classify the chest X-rays into two classes: positive (+ve) COVID-19 patients or normal subjects (or −ve). The experimental results are performed based on a sample from a collected comprehensive image dataset from several hospitals worldwide. The classification accuracy, precision, sensitivity, specificity and F1-score for the proposed scheme was 98.46%, 98.19%, 98.18%, 98.67%, and 98.17%. The experimental results also documented the high accuracy of the proposed pipeline compared to other literature techniques.
The aim of this paper is devoted to introduce and study the concepts of semi-compact (resp. semi-... more The aim of this paper is devoted to introduce and study the concepts of semi-compact (resp. semi-Lindelӧf, locally semi-compact) spaces in a neutrosophic crisp topological space. Several properties, functions properties of neutrosophic crisp semi-compact spaces are studied. In addition to these, we introduce and study the definition of neutrosophic crisp semi-Lindelӧf spaces and neutrosophic crisp locally semi-compact spaces. We show that neutrosophic crisp semi-compact spaces is preserved under neutrosophic crisp irresolute function and neutrosophic crisp pre-semi-closed function with neutrosophic crisp semi-compact point inverses.
In this paper we introduce a new type of classical set called the neutrosophic classical set. Aft... more In this paper we introduce a new type of classical set called the neutrosophic classical set. After given the fundamental definitions of neutrosophic classical set operations, we obtain several properties, and discussed the relationship between neutrosophic classical sets and others. Finally, we generalize the classical probability to the notion of neutrosophic probability. This kind of probability is necessary because it provides a better representation than classical probability to uncertain events. Possible applications to computer sciences are touched upon.
The focus of this paper is to propose a new notion of neutrosophic crisp sets via neutrosophic cr... more The focus of this paper is to propose a new notion of neutrosophic crisp sets via neutrosophic crisp ideals and to study some basic operations and results in neutrosophic crisp topological spaces.
Since the world is full of indeterminacy, the neutrosophics found their place into contemporary r... more Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. In neutrosophic set, indeterminacy is quantified explicitly and truth-membership, indeterminacy-membership and falsity-membership are independent. For that purpose, it is natural to adopt the value from the selected set with highest degree of truth-membership, indeterminacy membership and least degree of falsity-membership on the decision set. These factors indicate that a decision making process takes place in neutrosophic environment. In this paper, we introduce and study the probability of neutrosophic crisp sets. After giving the fundamental definitions and operations, we obtain several properties and discuss the relationship between them. These notions can help researchers and make great use in the future in making algorithms to solve problems and manage between these notions to produce a new application or new algorithm of solving decision support problems. Possible applications to mathematical computer sciences are touched upon.
In this paper, we generalize the crisp topological spaces to the notion of neutrosophic crisp top... more In this paper, we generalize the crisp topological spaces to the notion of neutrosophic crisp topological space, and we construct the basic concepts of the neutrosophic crisp topology.
In this paper, we introduce and study the concept of "neutrosophic closed set "and "neutrosophic ... more In this paper, we introduce and study the concept of "neutrosophic closed set "and "neutrosophic continuous function". Possible application to GIS topology rules are touched upon.
Mobile adhoc networks (MANETs) poses a large area of challenges in the field of security, this is... more Mobile adhoc networks (MANETs) poses a large area of challenges in the field of security, this is due to the lake of infrastructure and the continuous changing in the network topology. Botnets are believed to be the most harmful danger that threatens any type of networks; because it controls the units in a non noticeable manner so detection of botnets is more difficult . in this paper the Artificial Immune System (AIS) is used as the defense system to the MANET to face botnets. Experimental results show that the use of fuzzy based security can enhance the security of AIS in MANETs.
In this paper we introduce the notion of ideals on neutrosophic set which is considered as a gene... more In this paper we introduce the notion of ideals on neutrosophic set which is considered as a generalization of fuzzy and fuzzy intuitionistic ideals studies, the important neutrosophic
ideals has been given in.
The purpose of this paper is to introduce a new types of
crisp sets are called the neutrosophic c... more The purpose of this paper is to introduce a new types of
crisp sets are called the neutrosophic crisp set with three types 1, 2, 3.
The purpose of this paper is to introduce and study the characteristic function of a neutrosophic... more The purpose of this paper is to introduce and study the characteristic function of a neutrosophic set.
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Papers by Ahmed A . Salama
manuscript will clarify the meaning of independence (strict meaning of independence, the illusory
meaning of independence, Oscillating between the true meaning of independence, and the fallacy of
claiming independence and not applying it), this triplet actually refers to the three components that
the Neutrosophic theory standing on which is (truthiness, falsity, indeterminacy), the strategy of
applying the notion of independency in the local institutions, enlighten on the allegation of
applying the independency notion in some governments’ institutions without a real impact of this
term, and studying the meaning of independence from the perspective of a country legal system, all
these issues and some comparisons in applying the term (independency) between some countries
such as Iraq, France, Algeria, USA, etc. have been enclosed in this article.
incomplete, ambiguous, and evolving information. In reviewing the traditional methods for lung
cancer detection, we found that crisp and logic values have more difficulties and challenges. These
challenges related to the big data analytics, uncertainty values, and the different circumstances that
make it harder for prediction. In this work, we propose a novel approach that use a Neutrosophic
Topological Spaces (NTS) for the lung cancer detection in the chest X-ray images. Furthermore, the
proposed NTS leverage the strengths points of Neutrosophic Sets (NS) which include the degrees of
truth (T), indeterminacy (I), and falsity (F). The proposed model provides more informative results
about the uncertainty cases compared with the traditional methods. The results indicated that the
proposed NTS approach achieved highest accuracy reached to 85.5% with a sensitivity 88.2%,
specificity 82.1%, and AUC 0.91. which mean that the proposed NTS approach are more reliable and
efficient than traditional methods for uncertainty.
classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. *e proposed
neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation
algorithm. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural
networks but also to achieve a better performance than the other algorithms. *e experimental results visualize the data using the
boxplot for better understanding of attribute distribution. *e performance measurement of the confusion matrix for the
proposed framework is 95.1, 94.95, 95.2, and 95.1 concerning accuracy rate, precision, recall, and F1-score, respectively. WEKA
application is used to analyse cardiotocography data performance measurement of different algorithms, e.g., neural network,
decision table, the nearest neighbor, and rough neural network. *e comparison with other algorithms shows that the proposed
framework is both feasible and efficient classifier. Additionally, the receiver operation characteristic curve displays the proposed
framework classifications of the pathologic, normal, and suspicious states by 0.93, 0.90, and 0.85 areas that are considered high and
acceptable under the curve, respectively. Improving the performance measurements of the proposed framework by removing
ineffective attributes via feature selection would be suitable advancement in the future. Moreover, the proposed framework can
also be used in various real-life problems such as classification of coronavirus, social media, and satellite image
Neutrosophic Sets (CBN Sets) provide a powerful framework to address this challenge. This paper
explores the mathematical foundations of CBN Sets and highlights their practical applications
through illustrative examples. We demonstrate how CBN Sets effectively capture varying degrees of
certainty, possibility, and impermanence in environmental parameters. The concept of inclusion
relations facilitates comparisons and information fusion. Fundamental set operations (intersection,
union, complement) are explored for manipulating and analyzing uncertain environmental data. We
present the application of CBN Sets in water quality assessment, highlighting their ability to analyze
parameters while accounting for measurement uncertainties. The potential for air quality monitoring
using CBN Sets is also discussed. Finally, distance measures and similarity coefficients are introduced
to quantify relationships between air quality characteristics from different stations. By leveraging
CBN Sets and their associated operations, researchers can gain a more nuanced understanding of
environmental data, enabling informed decision-making for a healthier planet.
and a distributed database (DDB) consisting of multiple interconnected databases across a computer network, managed by a distributed database management system (DDBMS) for easy access. An intelligent system was designed to assess the difficulty level of preliminary exams and select top-performing advanced students using a Neutrosophic Deep Learning Model. The dataset was randomly split into training (80%) and testing (20%) sets, and the model, trained with the Adam optimizer at a 0.001 learning rate over 50 epochs, incorporated early stopping based on validation loss. This system, implemented at a traditional Egyptian university, achieved a 95% accuracy in predicting student dropout. Student behavior, influenced by personal, environmental, and academic factors, is often evaluated subjectively, leading to inconsistent results. Traditional machine learning approaches struggle with the inherent uncertainty in behavioral data. To address this, we combined neutrosophic theory—a mathematical framework that accounts for truth, falsity, and indeterminacy—with deep learning, which excels at learning complex data relationships, to predict student outcomes such as dropout rates. Evaluating the model on student data, including
attendance and grades, showed superior accuracy, achieving a determination coefficient of 0.95,
demonstrating the approach's potential for identifying at-risk students and enabling targeted
interventions.
Management (NFPM) aimed at addressing the critical challenge of uncertain energy availability in
Energy Harvesting Sensor Networks (EHWSNs). The main objective of this research is to enhance
the management of energy resources within these networks, which traditional fuzzy logic methods
often fail to do, leading to power failures and reduced reliability. NFPM utilizes neutrosophic logic
to effectively model uncertainty by representing the degrees of truth, indeterminacy, and falsity of
both harvested and residual energy levels. Through a fuzzy inference system, NFPM dynamically
allocates energy budgets for each time slot based on these neutrosophic sets, resulting in more
adaptive and conservative energy distribution. The results are validated through numerical
examples and extensive simulations, demonstrating NFPM's superiority over traditional fuzzy
logic, with significant improvements such as a 25% reduction in power failures, 95% enhanced
network connectivity, a 15% increase in data transmission success rates, and overall improvements
in energy efficiency and robustness to fluctuations and noise. This research establishes NFPM as a
promising solution to the uncertainties inherent in EHWSNs. Future research directions include
exploring the integration of NFPM with machine learning algorithms for predictive energy
management, assessing its scalability in larger networks, and examining its applicability in other
domains requiring energy management under uncertainty.
ideals has been given in.
crisp sets are called the neutrosophic crisp set with three types 1, 2, 3.
manuscript will clarify the meaning of independence (strict meaning of independence, the illusory
meaning of independence, Oscillating between the true meaning of independence, and the fallacy of
claiming independence and not applying it), this triplet actually refers to the three components that
the Neutrosophic theory standing on which is (truthiness, falsity, indeterminacy), the strategy of
applying the notion of independency in the local institutions, enlighten on the allegation of
applying the independency notion in some governments’ institutions without a real impact of this
term, and studying the meaning of independence from the perspective of a country legal system, all
these issues and some comparisons in applying the term (independency) between some countries
such as Iraq, France, Algeria, USA, etc. have been enclosed in this article.
incomplete, ambiguous, and evolving information. In reviewing the traditional methods for lung
cancer detection, we found that crisp and logic values have more difficulties and challenges. These
challenges related to the big data analytics, uncertainty values, and the different circumstances that
make it harder for prediction. In this work, we propose a novel approach that use a Neutrosophic
Topological Spaces (NTS) for the lung cancer detection in the chest X-ray images. Furthermore, the
proposed NTS leverage the strengths points of Neutrosophic Sets (NS) which include the degrees of
truth (T), indeterminacy (I), and falsity (F). The proposed model provides more informative results
about the uncertainty cases compared with the traditional methods. The results indicated that the
proposed NTS approach achieved highest accuracy reached to 85.5% with a sensitivity 88.2%,
specificity 82.1%, and AUC 0.91. which mean that the proposed NTS approach are more reliable and
efficient than traditional methods for uncertainty.
classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. *e proposed
neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation
algorithm. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural
networks but also to achieve a better performance than the other algorithms. *e experimental results visualize the data using the
boxplot for better understanding of attribute distribution. *e performance measurement of the confusion matrix for the
proposed framework is 95.1, 94.95, 95.2, and 95.1 concerning accuracy rate, precision, recall, and F1-score, respectively. WEKA
application is used to analyse cardiotocography data performance measurement of different algorithms, e.g., neural network,
decision table, the nearest neighbor, and rough neural network. *e comparison with other algorithms shows that the proposed
framework is both feasible and efficient classifier. Additionally, the receiver operation characteristic curve displays the proposed
framework classifications of the pathologic, normal, and suspicious states by 0.93, 0.90, and 0.85 areas that are considered high and
acceptable under the curve, respectively. Improving the performance measurements of the proposed framework by removing
ineffective attributes via feature selection would be suitable advancement in the future. Moreover, the proposed framework can
also be used in various real-life problems such as classification of coronavirus, social media, and satellite image
Neutrosophic Sets (CBN Sets) provide a powerful framework to address this challenge. This paper
explores the mathematical foundations of CBN Sets and highlights their practical applications
through illustrative examples. We demonstrate how CBN Sets effectively capture varying degrees of
certainty, possibility, and impermanence in environmental parameters. The concept of inclusion
relations facilitates comparisons and information fusion. Fundamental set operations (intersection,
union, complement) are explored for manipulating and analyzing uncertain environmental data. We
present the application of CBN Sets in water quality assessment, highlighting their ability to analyze
parameters while accounting for measurement uncertainties. The potential for air quality monitoring
using CBN Sets is also discussed. Finally, distance measures and similarity coefficients are introduced
to quantify relationships between air quality characteristics from different stations. By leveraging
CBN Sets and their associated operations, researchers can gain a more nuanced understanding of
environmental data, enabling informed decision-making for a healthier planet.
and a distributed database (DDB) consisting of multiple interconnected databases across a computer network, managed by a distributed database management system (DDBMS) for easy access. An intelligent system was designed to assess the difficulty level of preliminary exams and select top-performing advanced students using a Neutrosophic Deep Learning Model. The dataset was randomly split into training (80%) and testing (20%) sets, and the model, trained with the Adam optimizer at a 0.001 learning rate over 50 epochs, incorporated early stopping based on validation loss. This system, implemented at a traditional Egyptian university, achieved a 95% accuracy in predicting student dropout. Student behavior, influenced by personal, environmental, and academic factors, is often evaluated subjectively, leading to inconsistent results. Traditional machine learning approaches struggle with the inherent uncertainty in behavioral data. To address this, we combined neutrosophic theory—a mathematical framework that accounts for truth, falsity, and indeterminacy—with deep learning, which excels at learning complex data relationships, to predict student outcomes such as dropout rates. Evaluating the model on student data, including
attendance and grades, showed superior accuracy, achieving a determination coefficient of 0.95,
demonstrating the approach's potential for identifying at-risk students and enabling targeted
interventions.
Management (NFPM) aimed at addressing the critical challenge of uncertain energy availability in
Energy Harvesting Sensor Networks (EHWSNs). The main objective of this research is to enhance
the management of energy resources within these networks, which traditional fuzzy logic methods
often fail to do, leading to power failures and reduced reliability. NFPM utilizes neutrosophic logic
to effectively model uncertainty by representing the degrees of truth, indeterminacy, and falsity of
both harvested and residual energy levels. Through a fuzzy inference system, NFPM dynamically
allocates energy budgets for each time slot based on these neutrosophic sets, resulting in more
adaptive and conservative energy distribution. The results are validated through numerical
examples and extensive simulations, demonstrating NFPM's superiority over traditional fuzzy
logic, with significant improvements such as a 25% reduction in power failures, 95% enhanced
network connectivity, a 15% increase in data transmission success rates, and overall improvements
in energy efficiency and robustness to fluctuations and noise. This research establishes NFPM as a
promising solution to the uncertainties inherent in EHWSNs. Future research directions include
exploring the integration of NFPM with machine learning algorithms for predictive energy
management, assessing its scalability in larger networks, and examining its applicability in other
domains requiring energy management under uncertainty.
ideals has been given in.
crisp sets are called the neutrosophic crisp set with three types 1, 2, 3.
فكرة مقترحة للدراسة من :
الدكتور أحمد عبد الخالق سلامة
قسم الرياضيات وعلوم الحاسب - كلية العلوم – جامعة بور سعيد
للباحثة : دعاء رضا درويش - معيدة بكلية التجارة – جامعة دمياط
لنيل درجة الماجستير في الاحصاء التطبيقي
المقدمة:-
قدم سمارانداك عام 1999 Florentin Smarandache (1999) المنطق النيتروسفكى Neutrosophic Logic كتعميم للمنطق الفازى Fuzzy Logic وامتداد لنظرية الفئات الفازية Fuzzy Sets Theory التى قدمها لطفى زاده عام 1965 Lotfi A. Zadeh (1965) حيث تم استخدامها في التحليل الإحصائي للبيانات الفازية من خلال دراسة درجتي التأكد والرسوب ( عدم التأكد ) وأعطت نتائج عالية الدقة في التحليل الإحصائي وتم عمل دراسات مختلفة في هذا المجال أدت إلى اشتقاق بعض المقاييس الفازية منها معاملي الارتباط والانحدار الفازى وحديثا قام سمارانداك Smarandache بإدخال مفهوم الفئات النيتروسوفكية Neutrosophic Sets وامتداد لهذا المفهوم أدخل أحمد سلامة وآخرون مفاهيم وعمليات جديدة علي مفهوم الفئات النيتروسوفيكية التي تتوسع بشكل أكبر في استخدام البيانات من خلال دراسة درجات التأكد والرسوب والحيادية والتقسيمات المختلفة لكل درجة منها بما يسمح بإعطاء وصف أكثر دقة لبيانات الظاهرة محل الدراسة مما يسهم في دراسة وتحليل بيانات الظاهرة بشكل أكثر دقة حيث أن ذلك يقلل من درجة العشوائية في البيانات وذلك من شأنه الوصول إلى نتائج عالية الدقة تساهم في اتخاذ أمثل القرارات المناسبة لدى متخذى القرار ومما سبق يتضح لنا مدى أهمية دراسة نظرية الفئات النيتروسوفكية Neutrosophic Sets Theory والعمليات عليها من أجل إدخال ودراسة المنطق النيتروسفكى Neutrosophic Logic في التحليل الإحصائي لاشتقاق بعض المقاييس الإحصائية من خلال نظرية الفئات النيتروسوفكية Neutrosophic Sets Theory مثل معاملي الارتباط والانحدار النيتروسوفكى.
أهمية البحث:-
في ظل التطورات المتتابعة التى شهدتها الساحة السياسية في مصر عقب قيام ثورة 25 يناير من إسقاط النظام السابق وتأسيس أحزاب سياسية عديدة وتفعيل أحزاب كانت مهمشة من قبل وتمكن بعض الجماعات التى كانت محظورة في عهود ظالمة مستبدة من تكوين أحزاب لها دور مؤثر في المجتمع وتعددت الآراء واختلفت الاتجاهات الموجهة للرأي العام ومع هذا التعددية في الآراء والاتجاهات السياسية كانت الحاجة إلى تطوير الأدوات السياسية في الدولة ومن أهمها تطوير الدستور المصرى بما يسمح باستيعاب كل هذه التوجهات من أجل التحول نحو الديمقراطية التى كانت مطلب الشعب وهدف الثورة الأول ونظرا لتعدد الاتجاهات السياسية في المجتمع المصرى وانخفاض مستوى التعليم والثقافة والوعى السياسى بين الغالبية العظمى من أفراد الشعب وتباين الطبقات الاجتماعية في المجتمع حدث تضارب كبير بين قرار إلغاء الدستور وإعداد دستور جديد قبل إجراء الانتخابات البرلمانية في ذلك الوقت أو إجراء تعديلات على بعض مواد الدستور القائم حتى تتم الانتخابات البرلمانية وأصبحت هناك مشكلة وهى البرلمان أولا أم الدستور أولا فتم إجراء استفتاء شعبى على هذه التعديلات وكانت استمارة الاستفتاء تحتوى على اختيارين فقط وهما:
1- نعم ( درجة التأكد ) وتعنى الموافقة على التعديلات الدستورية.
2- لا ( درجة الرسوب ) وتعنى رفض التعديلات الدستورية.
وهذين الاختيارين لم يأخذا في الاعتبار رأى الأصوات التى أبطلت ( درجة الحياد ) وتم أخذ القرار بناء على رأى الأغلبية أى بأخذ درجة التأكد فقط في الاعتبار وبالتالي تم إهمال رأى الأقلية ( درجة الرسوب ) ورأى الذين أبطلوا أصواتهم ( درجة الحيادية ) وهنا يأتى دور المنطق النيتروسوفكى Neutrosophic Logic ليقدم خطوة جديدة في اتخاذ القرار وهى دراسة وتحليل درجات التأكد والرسوب والحيادية جميعها معا بعد تقسيمها وذلك من أجل الوصول إلى ازدياد مستوى الدقة في التحليل الاحصائى والرياضي مما يؤدى إلى اتخاذ أفضل القرارات المثلى من بين كل القرارات المناسبة.
مشكلة البحث:-
تعد نظرية الفئات الفازية Fuzzy Sets Theory من أكثر الطرق التى ساهمت في الحصول على مستوى عال من الدقة في التحليل الاحصائى من خلال دراسة درجة التأكد الخاصة بكل عنصر من عناصر بيانات الظاهرة محل الدراسة إلا أنها لم تأخذ في الاعتبار درجتي الرسوب والحياد مما استدعى إلى استحداث أسلوب أكثر ملائمة لدراسة هذا النوع من المتغيرات بما يساهم في الحصول على نتائج أكثر دقة من التي تم التوصل إليها باستخدام التحليل الفازى Fuzzy Analysis والتغلب على هذا القصور في معالجة البيانات ومن هنا يأتى دور نظرية الفئات النيتروسفكية Neutrosophic Sets Theory في التحليل الاحصائى والتي تعتبر بمثابة اللبنة الأولى لدراسة البيانات النيتروسفكية Neutrosophic Data .
أهدف البحث:-
تهدف هذه الدراسة إلى :
1- تقديم وعرض المفاهيم الإحصائية من خلال نظرية الفئات الفازية والفازية الحدسية والفئات الحدسية المعممة وامتدادا لهذه المفاهيم نستخدم المنطق النيتروسوفكي في ادخال مفهوم الفئات النيتروسوفكية Neutrosophic Sets والعمليات عليها واشتقاق نوع جديد من البيانات Neutrosophic Data في علم الإحصاء التطبيقي كنواة جديدة لتطبيقات الإحصاء المختلفة.
2- استنباط أسلوب جديد للتحليل الاحصائى باستخدام بعض البيانات النيتروسوفكية لاشتقاق بعض المقاييس الإحصائية مثل معاملى الارتباط والانحدار النيتروسوفكىNeutrosophic Correlation Coefficient & Neutrosophic Regression Coefficient والذى يعطى نتائج أكثر دقة , ذلك أن المنطق النيتروسفكى Neutrosophic Logic من المفاهيم الحديثة لتفسير وتحليل الظواهر بشكل أدق من المفاهيم التقليدية والفازية.
3- مقارنة ما تم التوصل إليه من نتائج باستخدام نظرية الفئات النيتروسوفكية Neutrosophic Sets Theory بالنماذج التقليدية والفازية.
المجال التطبيقي:-
يتناول البحث بيانات الاستفتاء على التعديلات الدستورية الذى تم في 19 مارس عام 2011 كمجتمع للدراسة وسوف تقوم الباحثة باختيار عينة عشوائية بسيطة من هذا المجتمع.
الدراسات السابقة:-
1- دراسة Florentin Smarandache ( 1991 )
تحت عنوان Neutrosophy ، أدخل الباحث منطق متعدد جديد فى مجال الفلسفة سماه المنطق النيتروسوفكى وأشار أن هذا المنطق سيقوم بتعميم كلا من المفاهيم التالية نظرية الاحتمالات ونظرية الفئات الفازية .
2- دراسة لأحمد سلامة :A. A. Salama (2012) وأخرون
الفئات النيتروسوفيكية والفراغات التوبولوجية النيتروسوفيك
Neutrosophic Sets and Neutrosophic Topological Spaces
أدخل الباحث مفهوم جديد في الفئات وأعطي العديد من العمليات علي هذا النوع من الفئات وأمكن ادخال فراغي توبولوجي جديد بالمفهوم الجديد لهذا النوع الجديد من الفئات كتعميم للفراغات التوبولوجية التي تم تعريفها من قبل .
3- دراسة لأحمد سلامة A. A. Salama (2012) وأخرون
معامل الارتباط للبيانات النيتروسوفيك Correlation for the Neutrosophic Data
أعطي الباحث نوع جديد من البيانات سماها البيانات النيتروسوفيك واعطي لها قانون لقياس معامل الارتباط بين البيانات
بفكرة واشراف الدكتور أحمد سلامة
DR.Ahmed Salama
Indeterminacy is different from randomness. Indeterminacy can be caused by physical space, materials and type of construction, by items involved in the space, or by other factors. In 1965 [51], Zadeh generalized the concept of crisp set by introducing the concept of fuzzy set, corresponding to the situation in which there is no precisely defined set;there are increasing applications in various fields, including probability, artificial intelligence, control systems, biology and economics. Thus, developments in abstract mathematics using the idea of fuzzy sets possess sound footing. In accordance, fuzzy topological spaces were introduced by Chang [12] and Lowen [33]. After the development of fuzzy sets, much attention has been paid to the generalization of basic concepts of classical topology to fuzzy sets and accordingly developing a theory of fuzzy topology [1-58]. In 1983, the intuitionistic fuzzy set was introduced by K. Atanassov [55, 56, 57] as a generalization of the fuzzy set, beyond the degree of membership and the degree of non-membership of each element. In 1999 and 2002, Smarandache [71, 72, 73, 74] defined the notion of Neutrosophic Sets, which is a generalization of Zadeh’s fuzzy set and Atanassov's intuitionistic fuzzy set. Some neutrosophic concepts have been investigated by Salama et al. [61-70]. Forwarding the study of neutrosophic sets, this book consists of seven chapters, targeting to:
generalize the previous studies in [1-59], and[91-94] so to define the neutrosopic crisp set and neutrosophic set concepts;
discuss their main properties;
introduce and study some concepts of neutrosophic crisp
and neutrosophic topological spaces and deduce their
properties;
deduce many types of functions and give the relationships
between different neutrosophic topological spaces, which
helps to build new properties of neutrosophic topological
spaces;
stress once more the importance of Neutrosophic Ideal as a
nontrivial extension of neutrosophic set and neutrosophic
logic [71, 72, 73, 74];
propose applications on computer sciences by using
neutrosophic sets.
on advanced studies in neutrosophy, neutrosophic set,
neutrosophic logic, neutrosophic probability, neutrosophic statistics
that started in 1995 and their applications in any field, such
as the neutrosophic structures developed in algebra, geometry,
topology, etc. The submitted papers should be professional, in good English, containing a brief review of a problem and obtained results. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities
statistics that started in 1995 and their applications in any field,
such as the neutrosophic structures developed in algebra,
geometry, topology, etc. The submitted papers should be professional, in good
English, containing a brief review of a problem and obtained
results. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their
interactions with different ideational spectra. This theory considers every notion or idea <A> together with
its opposite or negation <antiA> and with their spectrum of
neutralities <neutA> in between them (i.e. notions or ideas
supporting neither <A> nor <antiA>). The <neutA> and <antiA>
ideas together are referred to as <nonA>.
Neutrosophy is a generalization of Hegel's dialectics (the last one
is based on <A> and <antiA> only). According to this theory every idea <A> tends to be neutralized and balanced by <antiA> and <nonA> ideas - as a state of equilibrium. In a classical way <A>, <neutA>, <antiA> are disjoint two by two. But, since in many cases the borders between notions are vague, imprecise, Sorites, it is possible that <A>, <neutA>, <antiA> (and <nonA> of course) have common parts two by two, or even all three of them as well. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic).
statistics that started in 1995 and their applications in any field,
such as the neutrosophic structures developed in algebra,
geometry, topology, etc. The submitted papers should be professional, in good
English, containing a brief review of a problem and obtained
results. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their
interactions with different ideational spectra. This theory considers every notion or idea <A> together with
its opposite or negation <antiA> and with their spectrum of
neutralities <neutA> in between them (i.e. notions or ideas
supporting neither <A> nor <antiA>). The <neutA> and <antiA>
ideas together are referred to as <nonA>.
Neutrosophy is a generalization of Hegel's dialectics (the last one
is based on <A> and <antiA> only). According to this theory every idea <A> tends to be neutralized and balanced by <antiA> and <nonA> ideas - as a state of equilibrium. In a classical way <A>, <neutA>, <antiA> are disjoint two by two. But, since in many cases the borders between notions are vague, imprecise, Sorites, it is possible that <A>, <neutA>, <antiA> (and <nonA> of course) have common parts two by two, or even all three of them as well. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic).