course-file-soft-computing
... 39. What is general content addressable memory? Any physical system whose dynamics in phase space is dominated by a substantial number of locally stable states to which it is attracted can therefore be regarded as general content-addressable memory. 40. What is basin of attraction? The present input ...
... 39. What is general content addressable memory? Any physical system whose dynamics in phase space is dominated by a substantial number of locally stable states to which it is attracted can therefore be regarded as general content-addressable memory. 40. What is basin of attraction? The present input ...
Neural Network and Fuzzy Logic
... turned out to be very popular.[1, 2] Neural network have been successfully applied to problems in the field of pattern recognition, image processing, data compression forecasting and optimization to quote a few. Neurons considered as a threshold units that fire when their total input exceeds certain ...
... turned out to be very popular.[1, 2] Neural network have been successfully applied to problems in the field of pattern recognition, image processing, data compression forecasting and optimization to quote a few. Neurons considered as a threshold units that fire when their total input exceeds certain ...
On fuzzy semi-preopen sets and fuzzy semi
... studied in fuzzy topological spaces. In [7], the notions of fuzzy semi-preopen sets, fuzzy semi-precontinuous mappings and fuzzy semi-preopen mappings etc. are given according to the sense of Chang-Goguen spaces. By standard terminology in [5], these are corresponding with the following I-topologica ...
... studied in fuzzy topological spaces. In [7], the notions of fuzzy semi-preopen sets, fuzzy semi-precontinuous mappings and fuzzy semi-preopen mappings etc. are given according to the sense of Chang-Goguen spaces. By standard terminology in [5], these are corresponding with the following I-topologica ...
Design And Implementation Of Fuzzy Rule
... The advent of computers and information technology in the recent past has brought a drastic change in the fields of medicine area diagnosis, treatment of illnesses and patient pursuit has highly increased. Despite the fact that these fields, in which the computers are used, have very high complexity ...
... The advent of computers and information technology in the recent past has brought a drastic change in the fields of medicine area diagnosis, treatment of illnesses and patient pursuit has highly increased. Despite the fact that these fields, in which the computers are used, have very high complexity ...
A Parameterized Comparison of Fuzzy Logic, Neural Network and
... Basically it focuses on fixed and approximate reasoning rather than to fixed and exact reasoning. It takes variable value in between 0 and 1 or in between true and false unlike from traditional crisp set which takes either true or false or 0 and 1in. Fuzzy logic provides a way to make definite decis ...
... Basically it focuses on fixed and approximate reasoning rather than to fixed and exact reasoning. It takes variable value in between 0 and 1 or in between true and false unlike from traditional crisp set which takes either true or false or 0 and 1in. Fuzzy logic provides a way to make definite decis ...
Artificial Neural Networks.pdf
... Entity y: to this entity a “short” person may be one whose height is beneath or equal to 3.9 Here “short” is the language descriptor , it applies the same meaning to both x and y but it established that they don’t have a unique definition for short Such type of information associated with dilemma ar ...
... Entity y: to this entity a “short” person may be one whose height is beneath or equal to 3.9 Here “short” is the language descriptor , it applies the same meaning to both x and y but it established that they don’t have a unique definition for short Such type of information associated with dilemma ar ...
An Introduction of Soft Computing Approach over Hard Computing
... Soft computing is a wide ranging term encompassing such varied techniques as fuzzy systems, neural networks, genetic algorithms, simulated annealing etc. In this paper we are using only Fuzzy Logic (FL) and Genetic Algorithm (GA) Techniques. FL and GAs have been successfully used for supply chain mo ...
... Soft computing is a wide ranging term encompassing such varied techniques as fuzzy systems, neural networks, genetic algorithms, simulated annealing etc. In this paper we are using only Fuzzy Logic (FL) and Genetic Algorithm (GA) Techniques. FL and GAs have been successfully used for supply chain mo ...
Lecture 2 - UEF-Wiki
... Implementation: A computer program written and compiled for a specific computer or class of computers that implements a paradigm. ...
... Implementation: A computer program written and compiled for a specific computer or class of computers that implements a paradigm. ...
What is computing? Counting, calculating The discipline of
... and uncertainty to achieve tractability, robustness, and low solution cost. Its principal constituents are fuzzy logic, neurocomputing, and probabilistic reasoning. Soft computing is likely to play an increasingly important role in many application areas, including software engineering. The role mod ...
... and uncertainty to achieve tractability, robustness, and low solution cost. Its principal constituents are fuzzy logic, neurocomputing, and probabilistic reasoning. Soft computing is likely to play an increasingly important role in many application areas, including software engineering. The role mod ...
Fuzzy Systems and Neuro-Computing in Credit Approval
... deal with inexact information. Traditional computational techniques, such as statistical models and neural networks, require precision—on/off, yes/no, right/wrong. However, human beings do not experience the world this way; many of our activities and decisions are inexact. Fuzzy logic achieves a tra ...
... deal with inexact information. Traditional computational techniques, such as statistical models and neural networks, require precision—on/off, yes/no, right/wrong. However, human beings do not experience the world this way; many of our activities and decisions are inexact. Fuzzy logic achieves a tra ...
Chapter 02 for Neuro-Fuzzy and Soft Computing
... the application of AI theories (shortcoming of symbolism) ...
... the application of AI theories (shortcoming of symbolism) ...
i S dS i S dS Fuzzy Logic, Sets and Systems Lecture 1 Introduction
... Approximate and inexact nature of the real word; vague concepts easily dealt with by humans in daily life. Fuzzy Logic, Sets and Systems ...
... Approximate and inexact nature of the real word; vague concepts easily dealt with by humans in daily life. Fuzzy Logic, Sets and Systems ...
Fuzzy-probabilistic logic for common sense
... Vagueness is pervasive in common-sense reasoning. A calculus of degrees allows commonsense statements to be rendered into formal logic and be reasoned about computationally, thus fulfilling a need in logic-based AGI (artificial general intelligence) systems [5]. It is widely believed that a general- ...
... Vagueness is pervasive in common-sense reasoning. A calculus of degrees allows commonsense statements to be rendered into formal logic and be reasoned about computationally, thus fulfilling a need in logic-based AGI (artificial general intelligence) systems [5]. It is widely believed that a general- ...
What is rule-based reasoning
... Software code which processes the rules, cases, objects or other type of knowledge and expertise based on the facts of a given situation. Most AI tools contain some form of deductive or inductive reasoning capability. What is an expert system? Simply put, an expert system represents information and ...
... Software code which processes the rules, cases, objects or other type of knowledge and expertise based on the facts of a given situation. Most AI tools contain some form of deductive or inductive reasoning capability. What is an expert system? Simply put, an expert system represents information and ...
PPT
... In fuzzy set theory any element can to be member of set with any uncertainty or confidence Is(a,A) = 0 or 1 or 0.5 or 0.126 or … from interval (0,1) This uncertainty is determined by membership function 0≤μA(a)≤1 ...
... In fuzzy set theory any element can to be member of set with any uncertainty or confidence Is(a,A) = 0 or 1 or 0.5 or 0.126 or … from interval (0,1) This uncertainty is determined by membership function 0≤μA(a)≤1 ...
Fuzzy Control
... " So far as the laws of mathematics refer to reality, they are not certain, And so far as they are certain, they do not refer to reality." Albert Einstein Geometrie und Erfahrung ...
... " So far as the laws of mathematics refer to reality, they are not certain, And so far as they are certain, they do not refer to reality." Albert Einstein Geometrie und Erfahrung ...
Modeling and Experimentation Framework for Fuzzy Cognitive Maps Maikel Leon Espinosa
... since they are oriented to pattern classification problems, where understanding the behavior of the system under investigation is well appreciated. The third group includes procedures for evaluating the system behavior which generally requires more expertise. The user could also modify graphical asp ...
... since they are oriented to pattern classification problems, where understanding the behavior of the system under investigation is well appreciated. The third group includes procedures for evaluating the system behavior which generally requires more expertise. The user could also modify graphical asp ...