Question

What is genetic algorithm in soft computing techniques?

Answer 1

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.




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Answer 2

Answer:

A search-based optimization approach called a genetic algorithm (GA) is based on the concepts of natural selection and genetics. It is commonly utilized to locate ideal or almost ideal answers to challenging issues that would otherwise take a lifetime to solve. It is often employed in machine learning, research, and the solution of optimization issues.

Explanation:

All of humanity has always found immense inspiration in nature. Search-based algorithms called genetic algorithms (GAs) are founded on the ideas of natural selection and genetics. GAs are a part of evolutionary computation, a considerably more diverse computing field.

In GAs, we have a population or pool of potential answers to the given problem. Then, like in natural genetics, these solutions go through recombination and mutation, creating new offspring. This cycle is repeated over a number of generations.

Although genetic algorithms are sufficiently random in nature, they outperform random local search (where we simply try various random solutions and keep track of the best so far) because they also use historical data.

To know more about  Search-based algorithms, click on the link below:

https://brainly.in/question/45108498

To know more about genetics, click on the link below:

https://brainly.in/question/13351243

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