Paper Key : IRJ************950
Author: Pratiksha D. Gaikwad,P.s. Gade
Date Published: 13 Apr 2024
Abstract
ABSTRACT Soft computing techniques have emerged as powerful tools for addressing complex and uncertain problems in machine learning. This paper presents a comprehensive review of soft computing methodologies, including fuzzy logic, neural networks, genetic algorithms, and evolutionary computation, within the context of machine learning applications. The paper elucidates the fundamental principles behind each technique and explores their diverse applications across various domains. Through comparative analyses, it assesses the strengths and weaknesses of these techniques and highlights their suitability for different types of problems. Furthermore, the paper discusses recent advancements, challenges, and future directions in the integration of soft computing approaches with machine learning algorithms, providing valuable insights for practitioners and researchers in the field.
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