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Project Created: Sep 09, 2024
The fuzzy logic deals with incomplete, inconsistent, uncertain, vagueand undecided information with belief. Fuzzy logic with twofold fuzzy set will give more accuracy then single membership function. In this paper, fuzzy logic with twofold fuzzy sets are studied. Fuzzy neural net used learn fuzzy inference. Fuzz certainity factor (FCF) is studied to eliminate conflict between two membership functions. Sometimes decision has to be taken under risk. Fuzzy Decision set is defined with fuzzy certainty factor (FCF). Different fuzzy resoning methods are discussed. Fuzzy inference anr reasoning mrthods are given for business intelligence.
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1 Document(s)
Project Created: Sep 09, 2024
Zadeh, Mamdani and TSK are proposed different fuzzy conditional inferences for "if ¿ then ¿ ". These Zadeh and Mamdani fuzzy conditional inference are required prior information for both precedent and consequent part. Zadeh defined fuzzy set with single membership function. Fuzzy set with two membership function will give more evidence than single membership function. In this paper, fuzzy conditional inference is studied for "if ¿ then ¿" when prior information is not available for consequent part. Generalized fuzzy certainty factor is proposed for fuzzy set with two membership function. Fuzzy medial expert system is given as an application.
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1 Document(s)
Project Created: Sep 09, 2024
The information available to the system is incomplete in many applications like Decision Support Systems, Control Systems and Medical Expert Systems. Sometimes decision has to be taken under risk with incomplete information. Fuzzy logic deals with incomplete information with belief rather than likelihood (probability). The fuzzy set is defined with single membership function. The fuzzy set with two membership functions will give more information than single membership function. In this paper, the Fuzzy Certainty Factor (FCF) is studied as difference between fuzzy membership functions "true" and "false" for decision making. The fuzzy certainty factor is studied for fuzzy risk set. The fuzzy inference is studied. Business application is given as an application to fuzzy risk set.
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1 Document(s)
Project Created: Sep 09, 2024
Computer programs are now acceptable in Medicine. Artificial Intelligence in Medicine will perform better medical diagnosis and better surgery. Surgery intelligence is supporting system for the surgeon to take decision. Information available to the surgery is incomplete. The fuzzy logic deals incomplete information with belief rather than likelihood (probability). In this paper, fuzzy conditional inference is discussed. The fuzzy logic with two membership functions will give more evidence than single membership function. Generalized fuzzy logic is discussed with two membership functions. Generalized fuzzy certainty factor is discussed to eliminate conflict between two membership functions. The medical diagnosis is studied as an example. The fuzzy decision set is studied for decision making. The surgery intelligence is studied as an application.
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Fuzzy Security for Web Data Mining
1 Document(s)
Project Created: Sep 09, 2024
The data mining on web is difficult for online analytic processing (OLAP) with BIG DATA. The data mining is made simple by approximating the databases of BIG DATA for knowledge discovery process particularly MapReducing. The approximate information is fuzzy rather than probability. In this paper, fuzzy web data mining is discussed for BIG DATA for association rules. The query processing is discussed with SQL and Xquery for fuzzy data mining the fuzzy Algorithms are discussed to design queries in data mining. Some examples are discussed for fuzzy web data mining.
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1 Document(s)
Project Created: Sep 09, 2024
the logical data independence and physical data independence are necessary for data mining particularly for BIG DATA. The data base defining inherency with fuzziness will reduce the time in Information retrieval. The Data Mining is very fast using the fuzzy log for BIG DATA. In this paper, fuzzy data mining is studied and fuzzy association dependency is defied. The fuzzy MapReducibg algorithm is studied for BIG DATA to reduce the retrieval time for BIG DATA. This algorithm wills qick reference to perticular information and actual information will be secured.
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1 Document(s)
Project Created: Sep 09, 2024
Zadeh fuzzy set is defined with single fuzzy membership for incomplete information. Fuzzy set with two fuzzy membership functions "True" and "False" will give more information than the single fuzzy membership function. Zadeh and Mamdani fuzzy conditional inferences need to know both "Precedent part" and "Consequent part". In many applications like Medical diagnosis, Business intelligence and Control systems, the consequent part may not be known. In this paper, fuzzy conditional inference is studied when consequent part is not known. Generalized fuzzy logic with two membership function is studied for Rough sets. Fuzzy Certainty Factor(FCF ) is studied as the difference of "True " and "False" to eliminate the conflict of evidence The fuzzy control system is given as an application.
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ML Fuzzy Reinforcement Learning
1 Document(s)
Project Created: Sep 09, 2024
Sometimes Artificial Intelligence (AI) has to deal with uncertain problems. Uncertain Problems like Medical Intelligence, Business intelligence etc. Machine Learning analyzing before Programming.FuGePeNuNet method is studded by combining fuzzy logic, Genetic algorithms, Petri net and Neural net for large problems of Fuzzy Expert Systems.
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ML Wireless Sensor Network & Fuzzy Control Systems
1 Document(s)
Project Created: Sep 09, 2024
Zadeh, mamdani and TSK are proposed different fuzzy conditional inferences for ¿if ... then ...¿ to approximate with incomplete information. The Zadeh and mamdani fuzzy conditional inferences are require prior information for consequent part. The TSK fuzzy conditional inference need not know prior information for consequent part but it is difficult to compute. In this paper, new methods are proposed for ¿if ... then ...¿ when prior information is not known to consequent part with single fuzzy membership function and two fuzzy membership functions. The two fold fuzzy set made single fuzzy membership function as Fuzzy Certainty Factor(FCF). Sensors are discussed as application for proposed fuzzy conditional inference. Fuzzy inference system (FIS) is discussed for WSN to detect Costal erosion and Turbo Charger Fuzzy Control System as an examples.
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Truth Maintenance System to Problem Solving System
1 Document(s)
Project Created: Sep 09, 2024
Sometimes Artificial Intelligence (AI) has to deal with undecided problems. Undecided Problems like Medical diagnosis more than two conclusions, Business intelligence more than two possibilities, Investigations more than two conclusions etc. Truth maintenance Syste (TMS) will solve such undecided problems.
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