PREDICATE LOGIC
... Strong Method Problem Solving Reasoning in Uncertain Situations Soft Computing and Machine Learning ...
... Strong Method Problem Solving Reasoning in Uncertain Situations Soft Computing and Machine Learning ...
Artificial Intelligence Techniques in Power Electronics and Motor
... Artificial intelligence (AI) techniques, such as expert system (ES), fuzzy logic (FL), artificial neural network (ANN), and genetic algorithm (GA) have recently brought a new and advancing frontier in power electronics and motor drives area, which is already a complex and interdisciplinary technolog ...
... Artificial intelligence (AI) techniques, such as expert system (ES), fuzzy logic (FL), artificial neural network (ANN), and genetic algorithm (GA) have recently brought a new and advancing frontier in power electronics and motor drives area, which is already a complex and interdisciplinary technolog ...
Artificial Intelligence
... the role of problem solving, vision, and language in understanding human intelligence from a computational perspective. Course Goals & Objectives: At the conclusion of this course, the successful (passing) students will have an understanding of the basic areas of artificial intelligence including pr ...
... the role of problem solving, vision, and language in understanding human intelligence from a computational perspective. Course Goals & Objectives: At the conclusion of this course, the successful (passing) students will have an understanding of the basic areas of artificial intelligence including pr ...
powerpoint - IDA.LiU.se
... Vocabulary for a logic formula: set of symbols containing all those that occur in the formula (and maybe some more) Interpretation for a logic formula: a mapping from a vocabulary for it, to truth-values T or F Model for a logic formula: an interpretation where the value of the formula is T Joint vo ...
... Vocabulary for a logic formula: set of symbols containing all those that occur in the formula (and maybe some more) Interpretation for a logic formula: a mapping from a vocabulary for it, to truth-values T or F Model for a logic formula: an interpretation where the value of the formula is T Joint vo ...
Data mining
... The chromosome should in some way contain information about solution which it represents. The most used way of encoding is a binary string. Chromosome 1 1101100100110110 Chromosome 2 1101111000011110 Each bit in this string can represent some characteristic of the solution. One can encode directly ...
... The chromosome should in some way contain information about solution which it represents. The most used way of encoding is a binary string. Chromosome 1 1101100100110110 Chromosome 2 1101111000011110 Each bit in this string can represent some characteristic of the solution. One can encode directly ...
Bound and Free Variables Theorems and Proofs
... A typical logic is described in terms of • syntax: what are the valid formulas • semantics: under what circumstances is a formula true • proof theory/ axiomatization: rules for proving a formula true Truth and provability are quite different. • What is provable depends on the axioms and inference ru ...
... A typical logic is described in terms of • syntax: what are the valid formulas • semantics: under what circumstances is a formula true • proof theory/ axiomatization: rules for proving a formula true Truth and provability are quite different. • What is provable depends on the axioms and inference ru ...
Rule Insertion and Rule Extraction from Evolving Fuzzy
... 3.Evolving Fuzzy Neural Networks EFuNNs 3.1.A general description EFuNNs are FuNN structures that evolve according to the ECOS principles [8]. EFuNNs adopt some known techniques from [6, 15, 16] and from other known NN techniques, but here all nodes in an EFuNN are created during (possibly one-pass) ...
... 3.Evolving Fuzzy Neural Networks EFuNNs 3.1.A general description EFuNNs are FuNN structures that evolve according to the ECOS principles [8]. EFuNNs adopt some known techniques from [6, 15, 16] and from other known NN techniques, but here all nodes in an EFuNN are created during (possibly one-pass) ...
PRESERVATION THEOREMS IN LUKASIEWICZ MODEL THEORY
... y), a similar operation is used in [9]. The logical connective related to this operator will be shown by the same notation. We denote the logical connectives by the same notations as their truth functions in B. Let L be a first order language. We always assume that L contains a 2-place predicate sym ...
... y), a similar operation is used in [9]. The logical connective related to this operator will be shown by the same notation. We denote the logical connectives by the same notations as their truth functions in B. Let L be a first order language. We always assume that L contains a 2-place predicate sym ...
Fuzzy logic
Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1. By contrast, in Boolean logic, the truth values of variables may only be 0 or 1. Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false. Furthermore, when linguistic variables are used, these degrees may be managed by specific functions.The term fuzzy logic was introduced with the 1965 proposal of fuzzy set theory by Lotfi A. Zadeh. Fuzzy logic has been applied to many fields, from control theory to artificial intelligence. Fuzzy logic had however been studied since the 1920s, as infinite-valued logic—notably by Łukasiewicz and Tarski.