Any soft computing methodology is characterized with
Answers
Answer:
The correct answer to this question is an algorithm that can easily adapt to the change in the dynamic environment.
Explanation:
Given - Soft computing methodology.
To Find - Write any soft computing methodology is characterized.
Any soft computing methodology is characterized by an algorithm that can easily adapt to the change in the dynamic environment.
The term "soft computing" refers to a collection of computational methods based on artificial intelligence (decision making that is similar to that of a human) and natural selection that offer quick and economical solutions to extremely complex problems for which analytical (hard computing) formulations are not available.
Techniques like fuzzy logic, genetic algorithms, artificial neural networks, machine learning, and expert systems are the foundation of soft computing. Even though soft computing theory and methods were initially established in the 1980s, automated control engineering is currently focusing a lot of research and study on this field.
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Answer: Algorithm which can easily adapt with the change of dynamic environment.
Is the answer of this question.
Explanation:
The goal of soft computing is to analyse and build intelligent systems. It is based on fuzzy logic, artificial neural networks, and probabilistic reasoning, as well as genetic algorithms, chaos theory, and machine learning components, and contains approximation and dispositionality properties.
Soft computing is supplemented by Fuzzy Logic (FL), Machine Learning (ML), Neural Network (NN), Probabilistic Reasoning (PR), and Evolutionary Computation (EC). Soft computing also use similar strategies to address any difficult problem.
Machine learning, fuzzy logic, evolutionary computation, and probabilistic theory are all components of soft computing. These components are cognitively capable of learning effectively. They deal with imprecision and have a high tolerance for ambiguity.
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