Abstract
In contrast to traditional computing, soft computing can be used to adjust prediction models and locate answers to difficult, real-world issues. Soft computing is more forgiving of ambiguity than classical computing. For soft computing, the gold standard is the human brain. Soft computing includes innovations like machine learning, artificial neural networks, genetic algorithms, fuzzy logic, and expert systems. First proposed in the 1980s, soft computing is now a central focus of academic inquiry across disciplines. Soft computing is widely used in commercial, industrial, and household settings due to its low cost and high performance. Soft computing is finding more and more uses today. This article compares and contrasts the benefits of traditional computing with those of contemporary soft computing.
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