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  • Fault Diagnosis Inverse Problems: Solution with Metaheuristics

    Series series Engineering (R0)
    This book presents a methodology based on inverse problems for use in solutions for fault diagnosis in control systems, combining tools from mathematics, physics, computational and mathematical modeling, optimization and computational intelligence. This methodology, known as fault diagnosis – inverse problem methodology or FD-IPM, unifies the results of several years of work of the authors in the ... Read more

    $80.99 USD

  • Computational Intelligence Applied to Inverse Problems in Radiative Transfer

    Series series Mathematics and Statistics (R0)
    This book offers a careful selection of studies in optimization techniques based on artificial intelligence, applied to inverse problems in radiative transfer. In this book, the reader will find an in-depth exploration of heuristic optimization methods, each meticulously described and accompanied by historical context and natural process analogies.From simulated annealing and genetic algorithms to ... Read more

    $125.09 USD

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  • Pattern Recognition

    This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods ... Read more

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  • Principles Of Artificial Neural Networks (3rd Edition)

    by Daniel Graupe ...
    Series Book 7 - Advanced Series In Circuits And Systems
    Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications ... Read more

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  • Gmdh-methodology And Implementation In Matlab

    Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization. Since its introduction, inductive modelling has been developed to support complex systems in prediction, clusterization, system identification, as well as data mining and knowledge extraction technologies in social science, science, engineering, and medicine.This is the first ... Read more

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  • Fuzzy Neural Networks for Real Time Control Applications

    Concepts, Modeling and Algorithms for Fast Learning

    AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its ... Read more

    $89.09 USD

  • Neural Networks and Statistical Learning

    Series series Engineering (R0)
    Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content.Each of ... Read more

    $107.09 USD

  • Simulation-driven Design Optimization And Modeling For Microwave Engineering

    Computer-aided full-wave electromagnetic (EM) analysis has been used in microwave engineering for the past decade. Initially, its main application area was design verification. Today, EM-simulation-driven optimization and design closure become increasingly important due to the complexity of microwave structures and increasing demands for accuracy. In many situations, theoretical models of ... Read more

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  • Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

    Series series Computer Science (R0)
    This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, ... Read more

    $107.09 USD

  • Bioinspired Optimization Methods and Their Applications

    8th International Conference, BIOMA 2018, Paris, France, May 16-18, 2018, Proceedings

    Series series Springer Nature Proceedings Computer Science
    This book constitutes the thoroughly refereed revised selected papers of the 10th International Conference on Bioinspired Optimization Models and Their Applications, BIOMA 2018, held in Paris, France, in May 2018.The 27 revised full papers were selected from 53 submissions and present papers in all aspects of bioinspired optimization research such as new algorithmic developments, high-impact ... Read more

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  • Vibration-based Techniques For Damage Detection And Localization In Engineering Structures

    Series Book 10 - Computational And Experimental Methods In Structures
    In the oil and gas industries, large companies are endeavoring to find and utilize efficient structural health monitoring methods in order to reduce maintenance costs and time. Through an examination of the vibration-based techniques, this title addresses theoretical, computational and experimental methods used within this trend.By providing comprehensive and up-to-date coverage of established and ... Read more

    $70.19 USD

  • Multivariate Statistical Process Control

    Process Monitoring Methods and Applications

    Series series Engineering (R0)
    Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help ... Read more

    $107.09 USD