08-01-2014, 02:30 PM
Soft Computing and Computational Intelligent Systems
Abstract
This paper reviews basic ideas of intelligent systems. We describe intelligent systems, together with diverse features and constituents of it. We especially focus on computational intelligence and soft computing. This paper reviews basic ideas of computational intelligence (CI) with its relationship to other system sciences. Also it describes a CI position in the whole body of soft computing. Recent developments in the area of intelligent systems and soft computing have presented effective alternatives for dealing with the behavior of this class of systems. In this paper we describe the fundamentals of soft computing based design approaches using tools such as fuzzy inferencing, approximate reasoning, neural networks and neuro-fuzzy systems. This paper outlines the fundamentals of soft computing along with their potential applications to various real world applications in virtually most fields of power engineering including system planning, pattern recognition, power generation, intelligent transportation, optimization, communication, systems and control , robotics and manufacturing, to name a few. This paper considers CI as integrity of theories, applying methods and models analogous to those demonstrated by biological intelligent systems in problem solving and decision making. Among such theories are artificial neural networks, approximate reasoning and learning, simulated annealing. This paper gives a brief report of the computational intelligence (CI) historical development, the current situation and main research and industrial activities in the area.