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2004, Fuzzy Sets and Systems
This paper describes hierarchical modeling of fuzzy logic concepts that has been used within the recently developed model of intelligent systems, called OBOA. The model is based on a multilevel, hierarchical, general object-oriented approach. Current methods and software design and development tools for intelligent systems are usually di cult to extend, and it is not easy to reuse their components in developing intelligent systems. The OBOA model tries to reduce these deÿciencies. The model starts with a well-founded software engineering principle, making clear distinction between generic, low-level intelligent software components, and domain-dependent, high-level components of an intelligent system. This paper concentrates on modeling and implementation of fuzzy logic concepts within the hierarchical levels of the OBOA model. The fuzzy components described are extensible and adjustable. As an illustration of how these components are used in practice, a practical design example from the domain of medical diagnosis is shown. The paper also suggests some steps towards future design of fuzzy components and tools for intelligent systems.
Intelligent Systems for Manufacturing, 1998
Various aspects of implementation of fuzzy software systems are discussed. Some theoretical considerations on basic notions are introduced and also OUf approach to implemetation is presented.
Engineering Letters, 2007
describes the design and implementation of an inference engine for the execution of Fuzzy Inference Systems (FIS), the architecture of the system is presented, and the object-oriented design of the main modules is also discussed. The engine is implemented as a component to be referenced by other applications locally or remotely as a web service. This engine is needed by our research group for the implementation of other projects, which are Internet and Web based. The distinctive characteristic of this component is the ability to define fuzzy objects and attributes.
1996
Reusability transfers software implementation into the selection problem: we search across the available reusable components, described by standard attributes that capture their functional characteristic, to depict the one that is most appropriate or fulfills our software development needs to the greatest extent. One of the problems in the process of selecting from the objects repository lies in the fact that reusable components usually do not match our requirements perfectly. The central issue, the- refore is, how to measure the degree of adequacy of the chosen reusable components ? In our article we propose one approach that incorporates the fuzzy sets theory and fuzzy logic into reusable objects (R-objects) management systems. The main idea is to establish one template R-object, based on expressed software implementation demands, and to compute its belongings to different R-objects sets formed according to adopted R-objects classification. The measured values are in direct propor...
Lecture Notes in Computer Science, 1997
Fuzzy Sets and Systems, 1997
This paper presents a modeling approach which couples fuzzy object-oriented database modeling with fuzzy logic. The modeling approach introduced here handles fuzziness at attribute, object/class and class/superclass levels in addition to fuzziness in class/class relationships and various associations among classes. We utilize logical rules to define some of the crisp/fuzzy relationships and associations which cannot be presented easily with object-oriented modeling features alone in the class hierarchies. We think that incorporation of object-oriented database modeling with logic along with usage of fuzzy set theory simplifies the design of complex and knowledge-intensive applications and handles uncertainty effectively, therefore resulting in a powerful modeling framework. © 1997 Elsevier Science B.V.
IEEE Transactions on Knowledge and Data …, 2003
Next generation information system applications require powerful and intelligent information management that necessitates an efficient interaction between database and knowledge base technologies. It is also important for these applications to incorporate uncertainty in data objects, in integrity constraints, and/or in application. In this study, we propose an intelligent object-oriented database architecture, IFOOD, which permits the flexible modeling and querying of complex data and knowledge including uncertainty with powerful retrieval capability.
2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542), 2004
Programs for contemporary industrial control systems are designed using Object Oriented methods and software agents. It is required that the system should reach its objectives even when unexpected events occur in an uncertain environment. A trend is that agents are becoming more autonomous, more complex and are having more responsibilities. There is a need for a high-level information representation such that a predictable behavior can be achieved in a uniform way for all agents. A fuzzy automaton-based approach offers clear benefits for developing agents of reconfigurable architecture. This paper reports on a research project that is currently underway to develop a Generic Encapsulated Fuzzy Automaton Software Agent for Object Oriented Control Systems. A laboratory has been set up to develop and evaluate the performance of new methods and architectures.
IFIP International Federation for Information Processing, 2006
The knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes to extend the classical object oriented architecture in order to allow modeling of problems with intrinsic imperfections. The aim is to use the JAVA object oriented architecture to carry out this objective. In consequence, it is necessary to define the semantics for this extension of JAVA and it will be called Fuzzy JAVA. The NCR FuzzyJ library allows represent the vagueness (fuzziness) and uncertainty in class attributes. JAVA extended allows to model fuzzy inheritance.
International journal of fuzzy system applications, 2017
Hierarchicalfuzzylogicsystemsareincreasinglyappliedtosolvecomplexproblems.Thereisaneed forastructuredandmethodologicalapproachforthedesignanddevelopmentofhierarchicalfuzzy logicsystems.Inthispaperareviewofamethoddevelopedbytheauthorfordesignanddevelopment ofhierarchicalfuzzylogicsystemsisconsidered.Theproposedmethodisbasedontheintegration ofgeneticalgorithmsandfuzzylogictoprovideanintegratedknowledgebaseformodelling,control and prediction. Issues related to the design and construction of hierarchical fuzzy logic systems usingseveralapplicationsareconsideredandmethodsforthedecompositionofcomplexsystems intohierarchicalfuzzylogicsystemsareproposed.Decompositionandconversionofsystemsinto hierarchicalfuzzylogicsystemsreducesthenumberoffuzzyrulesandimprovesthelearningspeed forsuchsystems.Applicationareasconsideredare:thepredictionofinterestrateandhierarchical roboticcontrol.Theaimofthismanuscriptistoreviewandhighlighttheresearchworkcompletedin theareaofhierarchicalfuzzylogicsystembytheauthor.Thepapercanbenefitresearchersinterested intheapplicationofhierarchicalfuzzylogicsystemsinmodelling,controlandprediction.
The paper discusses the motivation for, heritage, architecture and future development plans of the FuzzyCOPE software environment. FuzzyCOPE is a free software environment for teaching, research and intelligent system development.
Journal of Information Technology Research, 2008
Computational intelligence techniques such as neural networks, fuzzy logic, and evolutionary algorithms have been applied successfully in the place of the complex mathematical
1999
The paper discusses the motivation for, heritage, architecture and future development plans of the FuzzyCOPE software environment. FuzzyCOPE is a free software environment for teaching, research and intelligent system development.
Modeling and Applications, 2005
Fuzzy object-oriented database models allow the representation, storage, and retrieval of complex imperfect information according to the object-oriented data paradigm. This chapter describes both a framework and an architecture that can be used to develop fuzzy object-oriented capabilities using the conventional features of the object-oriented data paradigm. We present a framework composed of a set of classical classes, which gives support to fuzzily described complex objects. We also explain how to deal with fuzzy extensions of object-oriented features using as a basis, the conventional object-oriented features. This proposal can be used to build a fuzzy object-oriented database system, by taking as a base an existing database system and minimizing the development effort.
2014
This technological era is raising new challenges towards the storage and management of data, that is getting more complex and imprecise with the evolution of utilization of computer engineering in most of the areas of society. To confront the arising challenges, database researchers has introduced fuzzy object oriented databases, by blending the concepts of database management system, object oriented data modeling and fuzzy techniques. This paper approaches to define and standardize the conceptual modeling for the fuzzy object oriented databases and recognize the scope of their application in the fields of science, engineering, agriculture, spatial, astronomical, environmental and medical sciences.
This paper shows a introduction to an new integrated development envelopment for a complex neuro fuzzy controller. IDEA based in the Object Oriented Programing. In this system a complex hierarchical controller is described by a source code of EDA language. This source is compiled. The compiler dinamically produces an internal representation of the controller using object. Then it is possible to train the controller and to make different implementations of this controller. It is viable to simulate the system or to implement it by analog electronic circuits. The IDEA system can connect with SPICE, an analog simulation circuit program, and with PCB design programs to the physical implementation of the circuit. Finally, this method is applied to two examples: the control of an autonomous robot and a simple fuzzy controller.
Simulated Evolution and Learning, 2002
In this paper the design and development of a hierarchical fuzzy logic Systems are investigated. A new method using genetic algorithms for design of hierarchical fuzzy logic systems are proposed. This research study is unique in the way proposed method is applied to design and development of hierarchical fuzzy logic systems. The proposed method is then applied to financial modelling and prediction. A hierarchical fuzzy logic system is developed to predict quarterly interest rates in Australia. The new method proposed determines the number of layer in a hierarchical fuzzy logic system. The advantages and disadvantages of using hierarchical fuzzy logic systems for financial modelling is also considered. Good prediction of quarterly interest rate in Australia is obtained using the above method. The number of fuzzy rule used are reduced dramatically and prediction of interest rate is improved.
Soft Computing, 2012
This work introduces an OWL-based upper ontology, called OWL-FC (Ontology Web Language for Fuzzy Control), capable to support a semantic definition of Fuzzy Control. It focuses on the fuzzy rules representation by providing domain independent ontology, supporting interoperability and favoring domain ontologies re-usability. The main contribution is that OWL-FC exploits Fuzzy Logic in OWL to model vagueness and uncertainty of the real world. Moreover, OWL-FC enables automatic discovery and execution of fuzzy controllers, by means of context aware parameter setting: appropriate controllers can be activated, depending on the parameters proactively identified in the work environment. In fact, the semantic modeling of concepts allows the characterization of constraints and restrictions for the identification of the right matches between concepts and individuals. OWL-FC ontology provides a wide, semantic-based interoperability among different domain ontologies, through the specification of fuzzy concepts, independently by the application domain. Then, OWL-FC is coherent to the Semantic Web infrastructure and avoids inconsistencies in the ontology.
2006
In this paper a novel method for designing hierarchical fuzzy logic Systems are investigated. A new method using genetic algorithms for design of hierarchical fuzzy logic systems are proposed. The proposed method is then applied to financial modelling and prediction. A hierarchical fuzzy logic system is developed to predict quarterly interest rates in Australia. The new method proposed determines the number of layer in a hierarchical fuzzy logic system. The advantages and disadvantages of using hierarchical fuzzy logic systems for financial modelling is also considered. Good prediction of quarterly interest rate in Australia is obtained using the above method. The number of fuzzy rule used are reduced dramatically and prediction of interest rate is improved.
Artificial Intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. From all types of software development approaches, object oriented software development approach have a great role in the development of AI. Due to the increasing of complexness of AI developers know a days use object oriented approach for reusability, maintainability, modularity e.t.c. Generally object oriented software development have many great applications for the development of artificial intelligence.
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