Abstract
The traditional method of problem-solving, known as hard computing, is limited in its ability to handle modern digital technology and real-world problems accurately. Soft computing, a newer paradigm, offers a more versatile approach by utilizing multi-valued logic and human knowledge to solve complex, nonlinear problems efficiently. Unlike hard computing, soft computing can handle imprecise data and uncertainty effectively. This methodology has been successfully applied across various sectors, including scientific, industrial, and medical fields, providing more accurate results. Soft computing is good for its contributions to revolutionizing problem-solving techniques, being tolerant of imprecision, uncertainty, and linguistic variables, and offering approximate solutions to intricate problems.
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