Topic
Soft computing
About: Soft computing is a research topic. Over the lifetime, 6710 publications have been published within this topic receiving 118508 citations.
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TL;DR: This work is based on determining the optimal wait time at traffic signals for the microscopic discrete model and uses Bat Intelligence to solve the transport network design problem.
Abstract: The requirement of the road services and transportation network development planning came into existence with the development of civilization. In the modern urban transport scenario with the forever mounting amount of vehicles, it is very much essential to tackle network congestion and to minimize the travel time. This work is based on determining the optimal wait time at traffic signals for the microscopic discrete model. The problem is formulated as a bilevel model. The upper layer optimizes the travel time by reducing the wait time at traffic signal and the lower layer solves the stochastic user equilibrium. Soft computing techniques like Genetic Algorithms, Ant Colony Optimization, and many other biologically inspired techniques prove to give good results for bilevel problems. Here this work uses Bat Intelligence to solve the transport network design problem. The results are compared with the existing techniques.
26 citations
TL;DR: A soft computing approach is presented for modeling electrical power generating plants in order to characterize the essential dynamic behavior of the plant subsystems and shows the effectiveness and feasibility of the developed model in terms of more accurate and less deviation.
26 citations
TL;DR: The main contributions of this paper include two aspects: the tolerance rough fuzzy set which is extended from rougher fuzzy set is introduced, and some basic properties of the tolerance Rough fuzzy set are investigated.
Abstract: Based on Bayesian decision theory, three-way decisions model (TWDM) proposed by Yao gives new semantic interpretations of positive region, negative region and boundary region. Some extensions of TWDM have been proposed by different authors and have been successfully applied to many fields, such as soft computing, data mining and decision making. However existing three-way decisions models are almost developed in certainty environment, which limits their applications in uncertainty environment. In order to deal with this problem, based on tolerance rough fuzzy set, a TWDM is proposed in this paper. The main contributions of this paper include two aspects: (1) the tolerance rough fuzzy set which is extended from rough fuzzy set is introduced, and some basic properties of the tolerance rough fuzzy set are investigated. (2) The TWDM with respect to the tolerance rough fuzzy set is proposed. In addition, an example is given to illustrate the computation processes of the TWDM.
26 citations
TL;DR: The main theme of this paper is to discuss the fundamental differences between thesoft computing methods and the mathematically based conventional methods in engineering problems, and to explore the potential of soft computing methods in new ways of formulating and solving the otherwise intractable engineering problems.
Abstract: Modem soft computing methods, such as neural networks, evolutionary models and fuzzy logic, are mainly inspired by the problem solving strategies the biological systems use in nature. As such, the soft computing methods are fundamentally different from the conventional engineering problem solving methods, which are based on mathematics. In the author`s opinion, these fundamental differences are the key to the full understanding of the soft computing methods and in the realization of their full potential in engineering applications. The main theme of this paper is to discuss the fundamental differences between the soft computing methods and the mathematically based conventional methods in engineering problems, and to explore the potential of soft computing methods in new ways of formulating and solving the otherwise intractable engineering problems. Inverse problems are identified as a class of particularly difficult engineering problems, and the special capabilities of the soft computing methods in inverse problems are discussed. Soft computing methods are especially suited for engineering design, which can be considered as a special class of inverse problems. Several examples from the research work of the author and his co-workers are presented and discussed to illustrate the main points raised in this paper.
26 citations
Book•
01 Mar 2010
TL;DR: This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities, forming a foundation for the development of the field.
Abstract: Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies is a compendium that addresses this need. It integrates contrasting techniques of conventional hard computing and soft computing to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low-cost solution. This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities, forming a foundation for the development of the field.
26 citations