Papers by Harshada C Mandhare
International Journal of Advanced Research in Computer Science, 2017
Outliers is view as an error data in information which is turned into important crisis that has b... more Outliers is view as an error data in information which is turned into important crisis that has been investigated in various areas of study plus functional fields. Several outlier detection methods have been implemented to assured functional fields, whereas several methods are supplementary basic. Various functional areas are also investigated in severe privacy like study on offense as well as terrorist behaviors. Through the improvement in information skills, the numeral of records, plus their measurement as well as difficulty, raise fast, that outcome in the need of computerized examination of huge quantity of various ordered data. For this intention, different data mining systems are utilized. The objective of these types of systems is to detect unseen dependencies from the records. Outlier detection in data mining is the detection of objects, remarks or observations that doesn’t match to a predictable sample in a set of record. This detection technique is more beneficial in the ...
2017 International Conference on Intelligent Computing and Control Systems (ICICCS), 2017
Bu çalışmada farklı alanlarda yetişen kızılağaç odunundan üretilen kontrplakların formaldehit emi... more Bu çalışmada farklı alanlarda yetişen kızılağaç odunundan üretilen kontrplakların formaldehit emisyonu üzerine bölge farklılığının ve kontrplak üretiminde kullanılan tutkal türünün etkileri araştırılmıştır. Bu maksatla, Trabzon, Giresun ve Artvin bölgelerinden elde edilen Kızılağaç tomruklarından laboratuar şartlarında melamin üre formaldehit ve üre formaldehit olmak üzere iki tutkal türü kullanılarak 3 tabakalı kontrplaklar üretilmiştir. Bölgelerden alınan odun örneklerinin pH değerleri TAPPI t m-45'e göre belirlenirken, odun özgül ağırlıkları TS 2472 de belirtilen esaslara göre tespit edilmiştir. Deneme kontrplaklarının formaldehit emisyonu miktarları ise EN 717-3'e göre ölçülmüştür. Sonuç olarak üre formaldehitle üretilen kontrplakların formaldehit emisyonu değerleri melamin üre formaldehit ile üretilen kontrplaklardan daha yüksek çıkmıştır. Her iki tutkal türü için de Giresun/Espiye bölgesi en yüksek formaldehit emisyonu değerlerini vermiştir. Odunun ağaç yetişme bölgesine göre değişen pH ve özgül ağırlığının formaldehit emisyonuna bir etkisi olduğu tespit edilmiştir.
as there is an increasing demand of data, outlier detection is coming across as a popular field o... more as there is an increasing demand of data, outlier detection is coming across as a popular field of research. Outlier is stated as an observation which is dissimilar from the other observations present in the data set. It is advantageous in the fields like medical industry, crime detection, fraudulent transaction, public safety etc. Outlier can be learnt in different fields like big data, time series data, high dimension data, biological data, uncertain data and many more. Most of the time 10% of the whole sample data set is incorrect, not accessible or missing sometimes. This paper studies and compares the popular outlier detection algorithms namely, Cluster based outlier detection, Distance based outlier detection and Density based outlier detection. Comparative study of these outlier detection techniques is performed to find out most efficient outlier detection method for calculation of the outlier.
— as there is an increasing demand of data, outlier detection is coming across as a popular field... more — as there is an increasing demand of data, outlier detection is coming across as a popular field of research. Outlier is stated as an observation which is dissimilar from the other observations present in the data set. It is advantageous in the fields like medical industry, crime detection, fraudulent transaction, public safety etc. Outlier can be learnt in different fields like big data, time series data, high dimension data, biological data, uncertain data and many more. Most of the time 10% of the whole sample data set is incorrect, not accessible or missing sometimes. This paper studies and compares the popular outlier detection algorithms namely, Cluster based outlier detection, Distance based outlier detection and Density based outlier detection. Comparative study of these outlier detection techniques is performed to find out most efficient outlier detection method for calculation of the outlier.
Outliers is view as an error data in information which is turned into important crisis that has b... more Outliers is view as an error data in information which is turned into important crisis that has been investigated in various areas of study plus functional fields. Several outlier detection methods have been implemented to assured functional fields, whereas several methods are supplementary basic. Various functional areas are also investigated in severe privacy like study on offense as well as terrorist behaviors. Through the improvement in information skills, the numeral of records, plus their measurement as well as difficulty, raise fast, that outcome in the need of computerized examination of huge quantity of various ordered data. For this intention, different data mining systems are utilized. The objective of these types of systems is to detect unseen dependencies from the records. Outlier detection in data mining is the detection of objects, remarks or observations that doesn't match to a predictable sample in a set of record. This detection technique is more beneficial in the several areas such as health trade, offense finding, fake operation, community protection and so on. In this paper we have studied different outlier detection algorithms such as Cluster based outlier detection, Distance based outlier detection plus Density based outlier detection. Result experimentation is done on different four dataset to identify the outliers and the comparative result shows that the cluster based methods are efficient for calculation of clusters and density-based outlier detection algorithm offers improved accuracy and faster execution for identification of outliers than other two outlier detection algorithm.
The Soft Computing is an accumulated branch of Computer Science and Engineering since it is a
col... more The Soft Computing is an accumulated branch of Computer Science and Engineering since it is a
collection of various computational techniques, it includes the phenomenon of several other
computational disciplines like Artificial Intelligence, Machine Learning, Decision Support Systems,
Fuzzy Systems, Neuro Computing, Computational Intelligence etc. The guiding principle of Soft
Computing is “Derive benefit from the tolerance for imprecision, uncertainty, partial truth and
approximation to achieve tractability, robustness and low solution cost.” This is very important to
understand that the Soft Computing is not a medley. Rather, it is an affiliation in which each member
contributes a distinct methodology of solving the problem of its domain. The intention of this paper is
not to provide thorough attention to all Soft Computing paradigms, but to give an overview of most
popular aspects of Soft Computing.
Keywords – Computational Intelligent, Fuzzy Sets, Artificial Neural Networks, Decision Support System, machine learning
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Papers by Harshada C Mandhare
collection of various computational techniques, it includes the phenomenon of several other
computational disciplines like Artificial Intelligence, Machine Learning, Decision Support Systems,
Fuzzy Systems, Neuro Computing, Computational Intelligence etc. The guiding principle of Soft
Computing is “Derive benefit from the tolerance for imprecision, uncertainty, partial truth and
approximation to achieve tractability, robustness and low solution cost.” This is very important to
understand that the Soft Computing is not a medley. Rather, it is an affiliation in which each member
contributes a distinct methodology of solving the problem of its domain. The intention of this paper is
not to provide thorough attention to all Soft Computing paradigms, but to give an overview of most
popular aspects of Soft Computing.
Keywords – Computational Intelligent, Fuzzy Sets, Artificial Neural Networks, Decision Support System, machine learning
collection of various computational techniques, it includes the phenomenon of several other
computational disciplines like Artificial Intelligence, Machine Learning, Decision Support Systems,
Fuzzy Systems, Neuro Computing, Computational Intelligence etc. The guiding principle of Soft
Computing is “Derive benefit from the tolerance for imprecision, uncertainty, partial truth and
approximation to achieve tractability, robustness and low solution cost.” This is very important to
understand that the Soft Computing is not a medley. Rather, it is an affiliation in which each member
contributes a distinct methodology of solving the problem of its domain. The intention of this paper is
not to provide thorough attention to all Soft Computing paradigms, but to give an overview of most
popular aspects of Soft Computing.
Keywords – Computational Intelligent, Fuzzy Sets, Artificial Neural Networks, Decision Support System, machine learning