Guest-editorial Special issue recent advances in soft computing: Theories and applications

Abstract. Soft Computing is an interdisciplinary area that encompasses a variety of computing paradigms. Examples of some popular soft computing paradigms include fuzzy computing, neural computing, evolutionary computing, and probabilistic com-puting. Soft computing paradigms, in general, aim to produce computing systems/machines that exhibit some useful properties, e.g. making inference with vague and/or ambiguous information, learning from noisy and/or incomplete data, adapting to changing environments, and reasoning with uncertainties. These properties are important for the systems/machines to be useful in assisting humans in our daily activities. Indeed, soft computing paradigms have been demonstrated to be capable of tackling a wide range of problems, e.g. optimization, decision making, information processing, pattern recognition, and intelligent data analysis. A number of papers pertaining to some recent advances in theoretical development and practical application of different soft computing paradigms are highlighted in this special issue. 1