Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications

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  • Author : Alma Y. Alanis
  • Publisher : Academic Press
  • Pages : 224 pages
  • ISBN : 0128182474
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKArtificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications
  • Author : Alma Y. Alanis,Nancy Arana-Daniel,Carlos Lopez-Franco
  • Publisher : Academic Press
  • Release : 15 March 2019
GET THIS BOOKArtificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Lazaros S. Iliadis,Harris Papadopoulos,Chrisina Jayne
  • Publisher : Springer
  • Release : 11 September 2013
GET THIS BOOKEngineering Applications of Neural Networks

The two volumes set, CCIS 383 and 384, constitutes the refereed proceedings of the 14th International Conference on Engineering Applications of Neural Networks, EANN 2013, held on Halkidiki, Greece, in September 2013. The 91 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers describe the applications of artificial neural networks and other soft computing approaches to various fields such as pattern recognition-predictors, soft computing applications, medical applications of AI, fuzzy inference, evolutionary algorithms, classification, learning and data mining, control techniques-aspects

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : John Macintyre,Lazaros Iliadis,Ilias Maglogiannis,Chrisina Jayne
  • Publisher : Springer
  • Release : 15 May 2019
GET THIS BOOKEngineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling -

Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications
  • Author : Alma Y. Alanis,Nancy Arana-Daniel,Carlos Lopez-Franco
  • Publisher : Academic Press
  • Release : 07 February 2019
GET THIS BOOKArtificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the

Artificial Neural Network Applications in Business and Engineering

Artificial Neural Network Applications in Business and Engineering
  • Author : Do, Quang Hung
  • Publisher : IGI Global
  • Release : 08 January 2021
GET THIS BOOKArtificial Neural Network Applications in Business and Engineering

In today’s modernized market, various disciplines continue to search for universally functional technologies that improve upon traditional processes. Artificial neural networks are a set of statistical modeling tools that are capable of processing nonlinear data with strong accuracy. Due to their complexity, utilizing their potential was previously seen as a challenge. However, with the development of artificial intelligence, this technology has proven to be an effective and efficient problem-solving method. Artificial Neural Network Applications in Business and Engineering is

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Giacomo Boracchi,Lazaros Iliadis,Chrisina Jayne,Aristidis Likas
  • Publisher : Springer
  • Release : 30 July 2017
GET THIS BOOKEngineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 18th International Conference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes

Artificial Neural Networks for Civil Engineers

Artificial Neural Networks for Civil Engineers
  • Author : Ian Flood,Nabil Kartam
  • Publisher : ASCE Publications
  • Release : 01 January 1998
GET THIS BOOKArtificial Neural Networks for Civil Engineers

Sponsored by the Committee on Expert Systems and Artificial Intelligence of the Technical Council on Computer Practices of ASCE. This report illustrates advanced methods and new developments in the application of artificial neural networks to solve problems in civil engineering.Ø Topics include: Øevaluating new construction technologies; Øusing multi-layeredØartificial neural networkØarchitecture to overcome problems with conventional traffic signal control systems; Øincreasing the computational efficiency of an optimization model; Øpredicting carbonation depth in concrete structures; Ødetecting defects in concrete piles; Ø

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Lazaros Iliadis,Chrisina Jayne
  • Publisher : Springer
  • Release : 28 September 2015
GET THIS BOOKEngineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 16th International Conference on Engineering Applications of Neural Networks, EANN 2015, held in Rhodes, Greece, in September 2015. The 36 revised full papers presented together with the abstracts of three invited talks and two tutorials were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on industrial-engineering applications of ANN; bioinformatics; intelligent medical modeling; life-earth sciences intelligent modeling; learning-algorithms; intelligent telecommunications modeling; fuzzy modeling; robotics and control; smart cameras; pattern recognition-facial

Neural Networks for Applied Sciences and Engineering

Neural Networks for Applied Sciences and Engineering
  • Author : Sandhya Samarasinghe
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKNeural Networks for Applied Sciences and Engineering

In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage

Proceedings of the 22nd Engineering Applications of Neural Networks Conference

Proceedings of the 22nd Engineering Applications of Neural Networks Conference
  • Author : Lazaros S. Iliadis,John D. MacIntyre,Chrisina Jayne,Elias Pimenidis
  • Publisher : Springer Nature
  • Release : 18 October 2021
GET THIS BOOKProceedings of the 22nd Engineering Applications of Neural Networks Conference

This book contains the proceedings of the 22nd EANN "Engineering Applications of Neural Networks" 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent -- long short-term memory. The application domains are related to: Anomaly

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Lazaros S. Iliadis,Harris Papadopoulos,Chrisina Jayne
  • Publisher : Springer
  • Release : 25 September 2013
GET THIS BOOKEngineering Applications of Neural Networks

The two volumes set, CCIS 383 and 384, constitutes the refereed proceedings of the 14th International Conference on Engineering Applications of Neural Networks, EANN 2013, held on Halkidiki, Greece, in September 2013. The 91 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers describe the applications of artificial neural networks and other soft computing approaches to various fields such as pattern recognition-predictors, soft computing applications, medical applications of AI, fuzzy inference, evolutionary algorithms, classification, learning and data mining, control techniques-aspects

Artificial Neural Networks for Engineers and Scientists

Artificial Neural Networks for Engineers and Scientists
  • Author : S. Chakraverty,Susmita Mall
  • Publisher : CRC Press
  • Release : 20 July 2017
GET THIS BOOKArtificial Neural Networks for Engineers and Scientists

Differential equations play a vital role in the fields of engineering and science. Problems in engineering and science can be modeled using ordinary or partial differential equations. Analytical solutions of differential equations may not be obtained easily, so numerical methods have been developed to handle them. Machine intelligence methods, such as Artificial Neural Networks (ANN), are being used to solve differential equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This

Artificial Neural Networks for Civil Engineers

Artificial Neural Networks for Civil Engineers
  • Author : Nabil Kartam,Ian Flood,James H. Garrett,Girish Agrawal
  • Publisher : American Society of Civil Engineers
  • Release : 01 January 1997
GET THIS BOOKArtificial Neural Networks for Civil Engineers

This monograph provides researchers with an understanding of the potential of artificial neural networks for solving civil engineering related problems, and guidance on how to develop successful implementations for a broad range of problems. Fundamental issues in the selection, development, and use of neural networks, as well as example applications to each of the various disciplines in civil engineering are presented. An introduction to neural networks is provided, along with a classification of the various forms of neural networking systems

Applied Artificial Neural Network Methods For Engineers And Scientists: Solving Algebraic Equations

Applied Artificial Neural Network Methods For Engineers And Scientists: Solving Algebraic Equations
  • Author : Snehashish Chakraverty,Sumit Kumar Jeswal
  • Publisher : World Scientific
  • Release : 26 January 2021
GET THIS BOOKApplied Artificial Neural Network Methods For Engineers And Scientists: Solving Algebraic Equations

The aim of this book is to handle different application problems of science and engineering using expert Artificial Neural Network (ANN). As such, the book starts with basics of ANN along with different mathematical preliminaries with respect to algebraic equations. Then it addresses ANN based methods for solving different algebraic equations viz. polynomial equations, diophantine equations, transcendental equations, system of linear and nonlinear equations, eigenvalue problems etc. which are the basic equations to handle the application problems mentioned in the