. Goal optimisatioo with incomplete infmnatioo and under uncertainty is the key to solving real-life problems in design and manufacturing. The second part of the book is devoted to fundamental aspects of soft computing. The proposed approach is highly parallelizable, flexible and scalable and it can be, in principle, adopted to solve other types of optimization problems as well. Features: - New and highly advanced research results at the forefront of soft computing in engineering design and manufacturing. Neural Networks-Based Approaches to Industrial Processes, 7. Numerical efficiency of these soft methods is illustrated on the analysis and design of complex engineering structures.
It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. Contained in this volume are six chapters discussing various aspects of soft computing in the field of textiles and apparel. Many attention is paid to hybrid systems for inverse analysis fusing soft methods and the finite element method. Soft Computing Techniques and Applications in Mechanical Engineering is a pivotal reference source for the latest research findings on a comprehensive range of soft computing techniques applied in various fields of mechanical engineering. The article presents the problem of knowledge in knowledge-based systems, such as advisory systems used in construction engineering. Based on the knowledge acquisition sessions that have been completed, it can be concluded that only a certain part of the knowledge contained in mental models has been acquired. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.
Artificial neural networks are of particular importance for functioning of the system. They can be used both in processes of well and poorly structured problems, knowledge of which is limited. This comprehensive handbook contains an excellent balance of tutorials and new results, that allows you to: obtain current information understand technical details assess research potentials, and define future directions of the field Manufacturing applications play a leading role in progress, and this handbook gives you a ready reference to guide you easily through these developments. Please click button to get soft computing in engineering design and manufacturing book now. The topics covered by the conference range from applied to theoretical aspects of fuzzy, neuro-fuzzy and rough sets over to neural networks to single and multi-objective optimisation.
The total of 85 papers presented in these proceedings were carefully reviewed and selected from 284 submissions. Artificial Neural Networks: Algorithms and models, 4. Applied Computational Intelligence and Soft Computing in Engineering is an essential reference work featuring the latest scholarly research on the concepts, paradigms, and algorithms of computational intelligence and its constituent methodologies such as evolutionary computation, neural networks, and fuzzy logic. Our sincere appreciation and thanks go to these authors for their contributions to this conference. Featuring extensive coverage on relevant areas such as thermodynamics, fuzzy computing, and computational intelligence, this publication is an ideal resource for students, engineers, research scientists, and academicians involved in soft computing techniques and applications in mechanical engineering areas. The book provides a unified platform for applied scientists and engineers in different fields and industries for the application of soft computing tools in many diverse domains of engineering.
Special attention is focused on applications of genetic algorithms and genetic programming as efficient tools for the analysis of complex, engineering mechanics problems. Precisely speaking, this book provides a platform for handling different kinds of uncertainties of real-life problems. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. This collection of keynote papers, presented at the 7th On-line World Conference on Soft Computing in Engineering Design and Manufacturing, provides a comprehensive overview of recent advances in fuzzy, neural and evolutionary computing techniques and applications in engineering design and manufacturing. This volume explains the primary tools of soft computing as well as provides an abundance of working examples and detailed design studies. The present book represents a cooperative effort to seek out the best strategies for effecting improvements in the quality and the reliability of Neural Networks, Swarm Intelligence, Evolutionary Computing, Image Processing Internet Security, Data Security, Data Mining, Network Security and Protection of data and Cyber laws.
The volume is balanced with respect to these two orientations: it contains six papers concerning methodological developments and five papers concerning applications and examples illustrating the theoretical developments. The total of 86 papers presented in these two volumes was carefully reviewed and selected from 238 submissions. The Bayesian techniques and Kalman filtering are discussed as advanced methods for neural network training and design. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. However, encouraging progress in studying specific neural models has been made by researchers from various disciplines.
A collection of methodologies aimed at researchers and professional design and manufacturing engineers who develop and apply intelligent systems in computer engineering. The different parts in the book also address these issues. The unique characteristics of construction engineering translate directly into unique characteristics of knowledge resources, which is evident in the potential sources of knowledge. The book provides a unified platform for applied scientists and engineers in different fields and industries for the application of soft computing tools in many diverse domains of engineering. Also audio and slide presentations allowed a detailed discussion of the papers. The study of artificial neural networks aims at understanding these computational prin ciples and applying them in the solutions of engineering problems.
This combination can effectively be used in practical areas of various fields of research. The methodological part of the book contains two papers on learning, one paper which presents a computational model of intracortical inhibitory effects, a paper presenting a new development of the random neural network, and two papers on associative memory models. Applications of such hybrid systems in earthquake engineering and reliability of structures will be discussed. The applications range fran design optimisatioo to scheduling and image analysis. Featuring extensive coverage on relevant areas such as thermodynamics, fuzzy computing, and computational intelligence, this publication is an ideal resource for students, engineers, research scientists, and academicians involved in soft computing techniques and applications in mechanical engineering areas.