Training the fuzzy integral
James M. Keller,Jeffrey Osborn +1 more
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A neuron model for using the fuzzy integral in a multiclass decision making environment is presented and a method of training the fuzzy density values from labeled data is developed, resulting in more comparable values for the fuzzy integrals.About:
This article is published in International Journal of Approximate Reasoning.The article was published on 1996-07-01 and is currently open access. It has received 113 citations till now. The article focuses on the topics: Fuzzy number & Fuzzy set operations.read more
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Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications
TL;DR: This book considers the principal constituents of soft computing, namely fuzzy logic, neurocomputing, genetic computing, and probabilistic reasoning, the relations between them, and their fusion in industrial applications, and how the combination can be used to achieve a high Machine Intelligence Quotient.
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A genetic algorithm for determining nonadditive set functions in information fusion
TL;DR: A specially designed genetic algorithm is employed to realize the optimization in determining the nonadditive set function from given input-output data when the nonlinear integral is viewed as a multi-input single-output system.
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Particle swarm optimization for determining fuzzy measures from data
TL;DR: This paper makes the first attempt to design a special particle swarm algorithm to determine a type of general fuzzy measures from data, and demonstrates that the algorithm is effective and efficient and is extended to identify and revise other types of fuzzy measures.
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Machinery fault diagnosis based on fuzzy measure and fuzzy integral data fusion techniques
TL;DR: The results show that the proposed schemas and models perform very well in selecting feature set and can improve accuracy in diagnosing both the rolling element bearing and electrical motor faults.
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Numerical recipes in C
TL;DR: The Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08.
Book
A mathematical theory of evidence
TL;DR: This book develops an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions.
Book
Introduction to Artificial Intelligence
Eugene Charniak,Drew McDermott +1 more
TL;DR: In this article, an introduction to artificial intelligence is presented, including reasoning under uncertainty, robot plans, language understanding, and learning, and the history of the field as well as intellectual ties to related disciplines are presented.