Artificial Neural Networks for Engineering Applications

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  • Author : Alma Y. Alanis
  • Publisher : Academic Press
  • Pages : 176 pages
  • ISBN : 0128182482
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Artificial Neural Networks for Engineering Applications

Download or Read online Artificial Neural Networks for Engineering Applications full in PDF, ePub and kindle. this book written by Alma Y. Alanis and published by Academic Press which was released on 07 February 2019 with total page 176 pages. We cannot guarantee that Artificial Neural Networks for Engineering Applications book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

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 BOOK 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

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 BOOK 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

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 BOOK Engineering 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 Bio Inspired Artificial Neural Networks

Engineering Applications of Bio Inspired Artificial Neural Networks
  • Author : Jose Mira,Juan V. Sanchez-Andres
  • Publisher : Springer Science & Business Media
  • Release : 19 May 1999
GET THIS BOOK Engineering Applications of Bio Inspired Artificial Neural Networks

This book constitutes, together with its compagnion LNCS 1606, the refereed proceedings of the International Work-Conference on Artificial and Neural Networks, IWANN'99, held in Alicante, Spain in June 1999. The 91 revised papers presented were carefully reviewed and selected for inclusion in the book. This volume is devoted to applications of biologically inspired artificial neural networks in various engineering disciplines. The papers are organized in parts on artificial neural nets simulation and implementation, image processing, and engineering applications.

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 BOOK Engineering 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

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Dominic Palmer-Brown,Chrisina Draganova,Elias Pimenidis,Haris Mouratidis
  • Publisher : Springer Science & Business Media
  • Release : 19 August 2009
GET THIS BOOK Engineering Applications of Neural Networks

A cursory glance at the table of contents of EANN 2009 reveals the am- ing range of neural network and related applications. A random but revealing sample includes: reducing urban concentration, entropy topography in epil- tic electroencephalography, phytoplanktonic species recognition, revealing the structure of childhood abdominal pain data, robot control, discriminating angry and happy facial expressions, ?ood forecasting, and assessing credit worthiness. The diverse nature of applications demonstrates the vitality of neural comp- ing and related soft computing approaches, and their

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : John Macintyre,Lazaros Iliadis,Ilias Maglogiannis,Chrisina Jayne
  • Publisher : Springer
  • Release : 14 May 2019
GET THIS BOOK Engineering 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 in Water Supply Engineering

Artificial Neural Networks in Water Supply Engineering
  • Author : Srinivasa Lingireddy,Gail M. Brion
  • Publisher : ASCE Publications
  • Release : 01 January 2005
GET THIS BOOK Artificial Neural Networks in Water Supply Engineering

Prepared by the Water Supply Engineering Technical Committee of the Infrastructure Council of the Environmental and Water Resources Institute of ASCE. This report examines the application of artificial neural network (ANN) technology to water supply engineering problems. Although ANN has rarely been used in in this area, those who have done so report findings that were beyond the capability of traditional statistical and mathematical modeling tools. This report describes the availability of diverse applications, along with the basics of neural

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Lazaros S. Iliadis,Chrisina Jayne
  • Publisher : Springer
  • Release : 15 September 2011
GET THIS BOOK Engineering Applications of Neural Networks

The two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th International Conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 International Conference, AIAI 2011, held jointly in Corfu, Greece, in September 2011. The 52 revised full papers and 28 revised short papers presented together with 31 workshop papers were carefully reviewed and selected from 150 submissions. The first volume includes the papers that were accepted for presentation at the EANN 2011 conference. They are organized in topical sections on computer

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Chrisina Jayne,Lazaros Iliadis
  • Publisher : Springer
  • Release : 18 August 2016
GET THIS BOOK Engineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016. The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.

Proceedings of the 21st EANN Engineering Applications of Neural Networks 2020 Conference

Proceedings of the 21st EANN  Engineering Applications of Neural Networks  2020 Conference
  • Author : Lazaros Iliadis,Plamen Parvanov Angelov,Chrisina Jayne,Elias Pimenidis
  • Publisher : Springer Nature
  • Release : 27 May 2020
GET THIS BOOK Proceedings of the 21st EANN Engineering Applications of Neural Networks 2020 Conference

This book gathers the proceedings of the 21st Engineering Applications of Neural Networks Conference, which is supported by the International Neural Networks Society (INNS). Artificial Intelligence (AI) has been following a unique course, characterized by alternating growth spurts and “AI winters.” Today, AI is an essential component of the fourth industrial revolution and enjoying its heyday. Further, in specific areas, AI is catching up with or even outperforming human beings. This book offers a comprehensive guide to AI in a

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 BOOK Artificial 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