Neurocomputing for Design Automation

Neurocomputing for Design Automation

Author: Hyo Seon Park

Publisher: CRC Press

Published: 2018-10-08

Total Pages: 239

ISBN-13: 1482274418

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Neurocomputing for Design Automation provides innovative design theories and computational models with two broad objectives: automation and optimization. This singular book: Presents an introduction to the automation and optimization of engineering design of complex engineering systems using neural network computing Outlines new computational models and paradigms for automating the complex process of design for unique engineering systems, such as steel highrise building structures Applies design theories and models to the solution of structural design problems Integrates three computing paradigms: mathematical optimization, neural network computing, and parallel processing The applications described are general enough to be applied directly or by extension to other engineering design problems, such as aerospace or mechanical design. Also, the computational models are shown to be stable and robust - particularly suitable for design automation of large systems, such as a 144-story steel super-highrise building structure with more than 20,000 members. The book provides an exceptional framework for the automation and optimization of engineering design, focusing on a new computing paradigm - neural networks computing. It presents the automation of complex systems at a new and higher level never achieved before.


Author:

Publisher: IOS Press

Published:

Total Pages: 7289

ISBN-13:

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Recent Metaheuristic Computation Schemes in Engineering

Recent Metaheuristic Computation Schemes in Engineering

Author: Erik Cuevas

Publisher: Springer Nature

Published: 2021-02-04

Total Pages: 282

ISBN-13: 3030660079

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This book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand.


Applications of Computational Intelligence

Applications of Computational Intelligence

Author: Alvaro David Orjuela-Cañón

Publisher: Springer

Published: 2018-12-13

Total Pages: 223

ISBN-13: 3030030237

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This book constitutes the thoroughly refereed proceedings of the First IEEE Colombian Conference, ColCACI 2018, held in Medellin, Colombia, in May 2018. The 17 full papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on artificial neural networks; computational intelligence; computer science.


Neurocomputing

Neurocomputing

Author: James A. Anderson

Publisher: MIT Press

Published: 1993-08-26

Total Pages: 762

ISBN-13: 0262510758

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In bringing together seminal articles on the foundations of research, the first volume of Neurocomputing has become an established guide to the background of concepts employed in this burgeoning field. Neurocomputing 2 collects forty-one articles covering network architecture, neurobiological computation, statistics and pattern classification, and problems and applications that suggest important directions for the evolution of neurocomputing.James A. Anderson is Professor in the Department of Cognitive and Linguistic Sciences at Brown University. Andras Pellionisz is a Research Associate Professor in the Department of Physiology and Biophysics at New York Medical Center and a Senior National Research Council Associate to NASA. Edward Rosenfeld is editor and publisher of the newsletters Intelligence and Medical Intelligence.


Creative Systems in Structural and Construction Engineering

Creative Systems in Structural and Construction Engineering

Author: Amarjit Singh

Publisher: CRC Press

Published: 2017-11-22

Total Pages: 1040

ISBN-13: 1351457071

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An examination of creative systems in structural and construction engineering taken from conference proceedings. Topics covered range from construction methods, safety and quality to seismic response of structural elements and soils and pavement analysis.


Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Author:

Publisher: Academic Press

Published: 2021-03-28

Total Pages: 416

ISBN-13: 0128231246

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. - Updates on new information on the architecture of GPU, NPU and DNN - Discusses In-memory computing, Machine intelligence and Quantum computing - Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance


Advanced Parallel Processing Technologies

Advanced Parallel Processing Technologies

Author: Chao Li

Publisher: Springer Nature

Published: 2023-11-07

Total Pages: 454

ISBN-13: 9819978726

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This book constitutes the refereed proceedings of the 15th International Symposium on Advanced Parallel Processing Technologies, APPT 2023, held in Nanchang, China, during August 4–6, 2023. The 23 full papers and 1 short papers included in this book were carefully reviewed and selected from 49 submissions. They were organized in topical sections as follows: High Performance Computing and Parallelized Computing, Storage Systems and File Management, Networking and Cloud Computing, Computer Architecture and Hardware Acceleration, Machine Learning and Data Analysis, Distinguished Work from Student Competition.


Neural Information Processing and VLSI

Neural Information Processing and VLSI

Author: Bing J. Sheu

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 569

ISBN-13: 1461522471

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Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding, and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources. The secret lies in the design optimization at various levels of computing and communication of intelligent machines. Each neural network system consists of massively paralleled and distributed signal processors with every processor performing very simple operations, thus consuming little power. Large computational capabilities of these systems in the range of some hundred giga to several tera operations per second are derived from collectively parallel processing and efficient data routing, through well-structured interconnection networks. Deep-submicron very large-scale integration (VLSI) technologies can integrate tens of millions of transistors in a single silicon chip for complex signal processing and information manipulation. The book is suitable for those interested in efficient neurocomputing as well as those curious about neural network system applications. It has been especially prepared for use as a text for advanced undergraduate and first year graduate students, and is an excellent reference book for researchers and scientists working in the fields covered.