Technical Development and Applications of Soft Computing in Agricultural and Biological Engineering

Abstract

Soft computing is a set of inexact computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and applied in the last three decades for scientific research and engineering computing. In agricultural and biological engineering, researchers and engineers have developed methods of fuzzy logic, artificial neural networks, genetic algorithms, decision trees, and support vector machines to study soil and water regimes related to crop growth, analyze the operation of food processing, and support decision-making in precision farming. This paper will review the development of soft computing techniques, and a number of advanced soft computing techniques will be introduced. With these concepts and methods, applications of soft computing in the field of agricultural and biological engineering will be presented, especially in the soil and water context for crop management and decision support for precision agriculture. The future of development and application of soft computing in agricultural and biological engineering will be discussed.