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Soft Computing in Chemical and Physical Sciences: A Shift in Computing Paradigm
by Kanchan Sarkar Sankar Prasad BhattacharyyaThis book can be regarded as 'Soft computing for physicists and chemists self-taught'. It prepares the readers with a solid background of soft computing and how to adapt soft computing techniques to problem solving in physical and chemical research. Soft computing methods have been little explored by researchers in physical and chemical sciences primarily because of the absence of books that bridge the gap between the traditional computing paradigm pursued by researchers in science and the new soft computing paradigm that has emerged in computer science. This book is the interface between these primary sources and researchers in physics and chemistry.
Soft Computing in Chemical and Physical Sciences: A Shift in Computing Paradigm
by Kanchan Sarkar Sankar Prasad BhattacharyyaThis book can be regarded as 'Soft computing for physicists and chemists self-taught'. It prepares the readers with a solid background of soft computing and how to adapt soft computing techniques to problem solving in physical and chemical research. Soft computing methods have been little explored by researchers in physical and chemical sciences primarily because of the absence of books that bridge the gap between the traditional computing paradigm pursued by researchers in science and the new soft computing paradigm that has emerged in computer science. This book is the interface between these primary sources and researchers in physics and chemistry.
Soft Computing in Engineering
by Jamshid GhaboussiSoft computing methods such as neural networks and genetic algorithms draw on the problem solving strategies of the natural world which differ fundamentally from the mathematically-based computing methods normally used in engineering. Human brains are highly effective computers with capabilities far beyond those of the most sophisticated electronic computers. The 'soft computing‘ methods they use can solve very difficult inverse problems based on reduction in disorder. This book outlines these methods and applies them to a range of difficult engineering problems, including applications in computational mechanics, earthquake engineering, and engineering design. Most of these are difficult inverse problems – especially in engineering design – and are treated in depth.
Soft Computing in Engineering
by Jamshid GhaboussiSoft computing methods such as neural networks and genetic algorithms draw on the problem solving strategies of the natural world which differ fundamentally from the mathematically-based computing methods normally used in engineering. Human brains are highly effective computers with capabilities far beyond those of the most sophisticated electronic computers. The 'soft computing‘ methods they use can solve very difficult inverse problems based on reduction in disorder. This book outlines these methods and applies them to a range of difficult engineering problems, including applications in computational mechanics, earthquake engineering, and engineering design. Most of these are difficult inverse problems – especially in engineering design – and are treated in depth.
Soft Computing in Industrial Applications: Algorithms, Integration, and Success Stories (Advances in Intelligent and Soft Computing #75)
by António Gaspar-Cunha Mario Köppen Jun Wang Gerald Schaefer X. Z. GaoThe 14th onlineWorld Conference on Soft Computing in Industrial Applications provides a unique opportunity for soft computing researchers and practitioners to publish high quality papers and discuss research issues in detail without incurring a huge cost. The conference has established itself as a truly global event on the Internet. The quality of the conference has improved over the years. The WSC14 conference has covered new trends in soft computing to state of the art applications. The conference has also added new features such as community tools, syndication, and multimedia online presentations.
Soft Computing in Industrial Applications: Recent and Emerging Methods and Techniques (Advances in Intelligent and Soft Computing #39)
by Rajkumar Roy Ashraf Saad Erel Avineri Keshav Dahal Muhammad SarfrazHere is a collection of papers presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization.
Soft Computing in Measurement and Information Acquisition (Studies in Fuzziness and Soft Computing #127)
by Leon Reznik Vladik KreinovichThis volume covers the fields of measurement and information acqulSltlon. It contains a collection of papers representing the current research trends in these areas. What are those trends? The first one is the enormous growth in the amount of information and the amazing technologies, which make this information available anywhere and anytime. The second one is a substantial development of methods of the information presentation including, to name just a few, multimedia, virtual environment, computer animation. The third one is the all-time boosting demand for improving the quality of decisions made on the base of this information in various applications ranging from engineering to business. Nowadays information acquisition should not only provide more information but also provide it in such a way as to assure effective and efficient processing of this information. And here comes a relatively new methodology of soft computing. Application of soft computing in measurement and information acquisition is considered in this volume.
Soft Computing in Ontologies and Semantic Web (Studies in Fuzziness and Soft Computing #204)
by Zongmin MaThis book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and the Semantic Web. The author shows how components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing methodology.
Soft Computing in Software Engineering (Studies in Fuzziness and Soft Computing #159)
by Ernesto Damiani Mauro MadravioSoft computing is playing an increasing role in the study of complex systems in science and engineering. There is a large spectrum of successful applications of soft computing in very different applications domains such as aerospace, communication, consumer appliances, electric power systems, process engineering, transportation, and manufacturing automation and robotics. It has taken a while to bring the early ideas of soft computing to an area and a discipline that seems to be more than appropriate for that. Here it is! This book studies SOFT computing in SOFTware engineering environment. The book is HARD in terms of its results. It covers a range of core topics from software engineering that are soft from its very nature: selection of components, software design, software reuse, software cost estimation and software processes. Soft computing differs from conventional (hard) computing in its ability to be tolerant of imprecision, uncertainty, partial truth, and approximation. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. The role model for soft computing is the human mind. This seems to be a natural fit with software engineering, a human-based development activity based on sound engineering principles. A recent survey by researchers reveals that "Software Engineering research tends to be quite self-contained, not relying on other disciplines for its thinking".
Soft Computing in Web Information Retrieval: Models and Applications (Studies in Fuzziness and Soft Computing #197)
by Enrique Herrera-Viedma Gabriella Pasi Fabio CrestaniThis book presents recent studies on the application of Soft Computing techniques in information access on the World Wide Web. The book is divided in four parts reflecting the areas of research of the presented works such as Document Classification, Semantic Web, Web Information Retrieval and Web Applications. The text demonstrates that Web Information Retrieval is a stimulating area of research where Soft Computing technologies can be applied satisfactorily.
Soft Computing in Wireless Sensor Networks
by Huynh Thi Thanh Binh Nilanjan DeyThis book focuses on the suitable methods to solve optimization problems in wireless network system utilizing digital sensors like Wireless Sensor Network. This kind of system has been emerging as the cornerstone technology for all new smart devices and its direct application in many fields in life.
Soft Computing in Wireless Sensor Networks
by Huynh Thi Thanh Binh Nilanjan DeyThis book focuses on the suitable methods to solve optimization problems in wireless network system utilizing digital sensors like Wireless Sensor Network. This kind of system has been emerging as the cornerstone technology for all new smart devices and its direct application in many fields in life.
Soft Computing: Methodologies and Applications (Advances in Intelligent and Soft Computing #32)
by Rajkumar Roy Frank Hoffmann Mario Köppen Frank KlawonnThe series of Online World Conferences on Soft Computing (WSC) is organized by the World Federation of Soft Computing (WFSC) and has become an established annual event in the academic calendar and was already held for the 8th time in 2003. Starting as a small workshop held at Nagoya University, Japan in 1994 it has - tured to the premier online event on soft computing in industrial applications. It has been hosted by the universities of Granada, Spain, Fraunhofer Gesellschaft, Berlin, Cran?eld University, Helsinki University of Technology and Nagoya University. The goal of WFSC is to promote soft computing across the world, by using the internet as a forum for virtual technical discussion and publishing at no cost to authors and participants. The of?cial journal of the World Federation on Soft Computing is the journal Applied Soft Computing. The 8th WSC Conference (WSC8) took place from September 29th to October 10th, 2003. Registered participants had the opportunity to follow and discuss the online presentations of authors from all over the world. Out of more than 60 subm- sions the program committee had accepted 27 papers for ?nal presentation at WSC8.
Soft Computing Methods for Microwave and Millimeter-Wave Design Problems (Studies in Computational Intelligence #392)
by Narendra Chauhan Machavaram Kartikeyan Ankush MittalThe growing commercial market of Microwave/ Millimeter wave industry over the past decade has led to the explosion of interests and opportunities for the design and development of microwave components.The design of most microwave components requires the use of commercially available electromagnetic (EM) simulation tools for their analysis. In the design process, the simulations are carried out by varying the design parameters until the desired response is obtained. The optimization of design parameters by manual searching is a cumbersome and time consuming process. Soft computing methods such as Genetic Algorithm (GA), Artificial Neural Network (ANN) and Fuzzy Logic (FL) have been widely used by EM researchers for microwave design since last decade. The aim of these methods is to tolerate imprecision, uncertainty, and approximation to achieve robust and low cost solution in a small time frame. Modeling and optimization are essential parts and powerful tools for the microwave/millimeter wave design. This book deals with the development and use of soft computing methods for tackling challenging design problems in the microwave/millimeter wave domain. The aim in the development of these methods is to obtain the design in small time frame while improving the accuracy of the design for a wide range of applications. To achieve this goal, a few diverse design problems of microwave field, representing varied challenges in the design, such as different microstrip antennas, microwave filters, a microstrip-via and also some critical high power components such as nonlinear tapers and RF-windows are considered as case-study design problems. Different design methodologies are developed for these applications. The presents soft computing methods, their review for microwave/millimeter wave design problems and specific case-study problems to infuse better insight and understanding of the subject.
Soft Computing Methods in Human Sciences (Studies in Fuzziness and Soft Computing #134)
by Vesa A NiskanenAn in-depth look at soft computing methods and their applications in the human sciences, such as the social and the behavioral sciences. Soft computing methods - including fuzzy systems, neural networks, evolutionary computing and probabilistic reasoning - are state-of-the-art methods in theory formation and model construction. The powerful application areas of these methods in the human sciences are demonstrated, including the replacement of statistical models by simpler numerical or linguistic soft computing models and the use of computer simulations with approximate and linguistic constituents. "Dr. Niskanen's work opens new vistas in application of soft computing, fuzzy logic and fuzzy set theory to the human sciences. This book is likely to be viewed in retrospect as a landmark in its field" (Lotfi A. Zadeh, Berkeley)
Soft Computing Techniques for Engineering Optimization (Science, Technology, and Management)
by Kaushik Kumar Supriyo Roy J. Paulo DavimThis book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook. It covers a broad area related to real life complex decision making problems using a heuristics approach. It also explores a wide perspective and future directions in industrial engineering research on a global platform/scenario. The book highlights the concept of optimization, presents various soft computing techniques, offers sample problems, and discusses related software programs complete with illustrations. Features Explains the concept of optimization and relevance to soft computing techniques towards optimal solution in engineering and management Presents various soft computing techniques Offers problems and their optimization using various soft computing techniques Discusses related software programs, with illustrations Provides a step-by-step tutorial on how to handle relevant software for obtaining the optimal solution to various engineering problems
Soft Computing Techniques for Engineering Optimization (Science, Technology, and Management)
by Kaushik Kumar Supriyo Roy J. Paulo DavimThis book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook. It covers a broad area related to real life complex decision making problems using a heuristics approach. It also explores a wide perspective and future directions in industrial engineering research on a global platform/scenario. The book highlights the concept of optimization, presents various soft computing techniques, offers sample problems, and discusses related software programs complete with illustrations. Features Explains the concept of optimization and relevance to soft computing techniques towards optimal solution in engineering and management Presents various soft computing techniques Offers problems and their optimization using various soft computing techniques Discusses related software programs, with illustrations Provides a step-by-step tutorial on how to handle relevant software for obtaining the optimal solution to various engineering problems
Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences (Edge AI in Future Computing)
by Pradip Debnath S. A. MohiuddineSoft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.
Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences (Edge AI in Future Computing)
by Pradip Debnath S. A. MohiuddineSoft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.
Soft Condensed Matter: Configurations, Dynamics and Functionality (Nato Science Series C: #552)
by A. T. Skjeltorp Sam F. EdwardsThis volume comprises the proceedings of a NATO Advanced Study In stitute held at Geilo, Norway, April 6 -16 1999. The ASI was the fifteenth in a series held biannually on topics related to cooperative phenomena and phase transitions, in this case applied to soft condensed matter and its configurations, dynamics and functionality. It addressed the current experimental and theoretical knowledge of the physical properties of soft condensed matter such as polymers, gels, complex fluids, colloids, granular materials and biomaterials. The main purpose of the lectures was to obtain basic understanding of important aspects in relating molecular configurations and dynamics to macroscopic properties and biological functionality. To our knowledge, the term Soft Condensed Matter was actually coined and used for the first time in 1989 at Geilo and some selected topics of soft matter were also given at Geilo in 1991, 1993 and 1995. A return to this subject 10 years after its instigation thus allowed a fresh look and a possibility for defining new directions for research.
Soft Methodology and Random Information Systems (Advances in Intelligent and Soft Computing #26)
by Miguel Concepcion Lopez-Diaz Maria Angeles Gil Przemyslaw Grzegorzewski Olgierd Hryniewicz Jonathan LawryThe analysis of experimental data resulting from some underlying random process is a fundamental part of most scientific research. Probability Theory and Statistics have been developed as flexible tools for this analyis, and have been applied successfully in various fields such as Biology, Economics, Engineering, Medicine or Psychology. However, traditional techniques in Probability and Statistics were devised to model only a singe source of uncertainty, namely randomness. In many real-life problems randomness arises in conjunction with other sources, making the development of additional "softening" approaches essential. This book is a collection of papers presented at the 2nd International Conference on Soft Methods in Probability and Statistics (SMPS’2004) held in Oviedo, providing a comprehensive overview of the innovative new research taking place within this emerging field.
Soft Methods for Data Science (Advances in Intelligent Systems and Computing #456)
by Maria Brigida Ferraro Paolo Giordani Barbara Vantaggi Marek Gagolewski María Ángeles Gil Przemysław Grzegorzewski Olgierd HryniewiczThis proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.
Soft Methods for Handling Variability and Imprecision (Advances in Intelligent and Soft Computing #48)
by Didier Dubois Maria Asuncion Lubiano Henri Prade María Angeles Gil Przemyslaw Grzegorzewski Olgierd HryniewiczProbability theory has been the only well-founded theory of uncertainty for a long time. It was viewed either as a powerful tool for modelling random phenomena, or as a rational approach to the notion of degree of belief. During the last thirty years, in areas centered around decision theory, artificial intelligence and information processing, numerous approaches extending or orthogonal to the existing theory of probability and mathematical statistics have come to the front. The common feature of those attempts is to allow for softer or wider frameworks for taking into account the incompleteness or imprecision of information. Many of these approaches come down to blending interval or fuzzy interval analysis with probabilistic methods. This book gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. Its aim is to present recent results illustrating such new trends that enlarge the statistical and uncertainty modeling traditions, towards the handling of incomplete or subjective information. It covers a broad scope ranging from philosophical and mathematical underpinnings of new uncertainty theories, with a stress on their impact in the area of statistics and data analysis, to numerical methods and applications to environmental risk analysis and mechanical engineering. A unique feature of this collection is to establish a dialogue between fuzzy random variables and imprecise probability theories.
Soft Methods for Integrated Uncertainty Modelling (Advances in Intelligent and Soft Computing #37)
by Alberto Bugarin Shoumei Li Maria Angeles Gil Przemyslaw Grzegorzewski Olgierd Hryniewicz Jonathan Lawry Enrique MirandaThe idea of soft computing emerged in the early 1990s from the fuzzy systems c- munity, and refers to an understanding that the uncertainty, imprecision and ig- rance present in a problem should be explicitly represented and possibly even - ploited rather than either eliminated or ignored in computations. For instance, Zadeh de?ned ‘Soft Computing’ as follows: Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role model for soft computing is the human mind. Recently soft computing has, to some extent, become synonymous with a hybrid approach combining AI techniques including fuzzy systems, neural networks, and biologically inspired methods such as genetic algorithms. Here, however, we adopt a more straightforward de?nition consistent with the original concept. Hence, soft methods are understood as those uncertainty formalisms not part of mainstream s- tistics and probability theory which have typically been developed within the AI and decisionanalysiscommunity.Thesearemathematicallysounduncertaintymodelling methodologies which are complementary to conventional statistics and probability theory.
Soft Methods in Probability, Statistics and Data Analysis (Advances in Intelligent and Soft Computing #16)
by Przemyslaw Grzegorzewski Olgierd Hryniewicz Maria A. GilClassical probability theory and mathematical statistics appear sometimes too rigid for real life problems, especially while dealing with vague data or imprecise requirements. These problems have motivated many researchers to "soften" the classical theory. Some "softening" approaches utilize concepts and techniques developed in theories such as fuzzy sets theory, rough sets, possibility theory, theory of belief functions and imprecise probabilities, etc. Since interesting mathematical models and methods have been proposed in the frameworks of various theories, this text brings together experts representing different approaches used in soft probability, statistics and data analysis.