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Soft computing is the reverse of hard (conventional) computing. It refers to a group of computational techniques that are based on artificial intelligence (AI) and natural selection. It provides cost-effective solutions to the complex real-life problems for which hard computing solution does not exist.
Soft Computing is a hub for system solutions based on unique soft computing techniques. Ensures dissemination of key findings in soft computing technologies. Covers a wide range of topics including soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy ...
Soft computing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer science. Typically, traditional hard-computing algorithms heavily rely on concrete data and mathematical models to produce solutions to problems.
Feb 14, 2023 · Soft computing is a branch of artificial intelligence that provides approximate solutions to complex problems that are difficult or impossible to solve using classical methods. The following are some of the reasons why soft computing is needed:
Introduction To Soft Computing. By Prof. Debasis Samanta | IIT Kharagpur. Learners enrolled: 3178. Soft computing is an emerging approach to computing which parallel the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision.
Jan 1, 2014 · Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent...
Jan 1, 2016 · Soft computing is based on techniques such as fuzzy logic, genetic algorithms, artificial neural networks, machine learning, and expert systems. Although soft computing theory and techniques were first introduced in 1980s, it has now become a major research and study area in automatic control engineering.
