Author: "Tsadiras, Athanasios" / Topic: predictions - Searchworks@Jio Institute Digital Library Search Results

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Author: Tsadiras, Athanasios, Zitopoulos, George, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Iliadis, Lazaros, editor, and Jayne, Chrisina, editor
Published: 2015
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Author: Tsadiras, Athanasios, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Darzentas, John, editor, Vouros, George A., editor, Vosinakis, Spyros, editor, and Arnellos, Argyris, editor
Published: 2008
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Author: Tsadiras, Athanasios and Bassiliades, Nick
Subjects: *FUZZY logic, *ARTIFICIAL neural networks, *STRATEGIC planning, *DECISION making, *PREDICTION models, *PROGRAMMING languages, *SYSTEMS design, *SIMULATION methods & models
Abstract: Abstract: Fuzzy Cognitive Map (FCM) technique is a combination of Fuzzy Logic and Artificial Neural Networks that is extensively used by experts and scientists of a diversity of disciplines, for strategic planning, decision making and predictions. A standardized representation of FCMs accompanied by a system that would assist decision makers to simulate their own developed Fuzzy Cognitive Maps would be highly appreciated by them, and would help the dissemination of FCMs. In this paper, (a) a RuleML representation of FCM is proposed and (b) a system is designed and implemented in Prolog programming language to assist experts to simulate their own FCMs. This system returns results in valid RuleML syntax, making them readily available to other cooperative systems. The representation capabilities and the design choices of the implemented system are discussed and a variety of examples are given to demonstrate the use of the system. [Copyright &y& Elsevier]
Published: 2013
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Author: Tsadiras, Athanasios K.
Subjects: *ARTIFICIAL neural networks, *ARTIFICIAL intelligence, *NEURONS, *NERVOUS system
Abstract: Abstract: In this paper, we compare the inference capabilities of three different types of fuzzy cognitive maps (FCMs). A fuzzy cognitive map is a recurrent artificial neural network that creates models as collections of concepts/neurons and the various causal relations that exist between these concepts/neurons. In the paper, a variety of industry/engineering FCM applications is presented. The three different types of FCMs that we study and compare are the binary, the trivalent and the sigmoid FCM, each of them using the corresponding transfer function for their neurons/concepts. Predictions are made by viewing dynamically the consequences of the various imposed scenarios. The prediction making capabilities are examined and presented. Conclusions are drawn concerning the use of the three types of FCMs for making predictions. Guidance is given, in order FCM users to choose the most suitable type of FCM, according to (a) the nature of the problem, (b) the required representation capabilities of the problem and (c) the level of inference required by the case. [Copyright &y& Elsevier]
Published: 2008
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