Real Time Applications of Soft Computing Techniques

Abstract

It is certain to accept that many different soft computing techniques and its appropriate algorithms which in turn plays a very significant role for better evaluation and has been proven to have successful solution for practical complex optimization problems. Also, soft computing is committed to system solutions constructed on soft computing methods which acknowledges uncertainty, approximate reasoning, imprecision, and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. Additionally, soft computing encourages the integration of soft computing techniques and tools into both day to-day and advanced practical applications. By merging novel notions and techniques of soft computing with other diversified multidiscipline, a unifying platform that fosters comparisons, extensions, and new applications can be obtained in order to establish better outputs. The principal constituents of soft computing methods include fuzzy systems/logic, neural networks/computing, evolutionary algorithms/computation, genetic algorithms, ant colony optimization, particle swarm optimization/intelligence, machine learning, probabilistic reasoning, and especially hybrid systems combining techniques from these fields, with the latter subsuming belief networks, chaos theory and parts of learning theory which lead to successful output not only in industrial applications but also in business, management, economics, finance, engineering and technology and science etc. There are wide range of real time application areas concerned with soft computing which includes data analysis and data mining, optimization, fault diagnosis, control, pattern recognition, signal processing, image and video processing as well as traffic and transportation systems, parameter estimation, system identification, robust solution, adaptive system, selforganization and failure analysis, multi-objective optimization etc. It is known that by employing various soft computing techniques can lead to higher optimum of business decision-making, but generally in many other fields such engineering, technology, public services etc. However, the idea behind soft computing is to model cognitive behavior of human mind and it is a foundation of conceptual intelligence in machines.