Industrial Applications of Neural Networks

This book is concerned with the application of neural network technology to real industrial problems.

Author: Ian F. Croall

Publisher: Springer

ISBN: 3540558756

Category: Computers

Page: 297

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Neural network technology encompasses a class of methods which attempt to mimic the basic structures used in the brain for information processing. Thetechnology is aimed at problems such as pattern recognition which are difficult for traditional computational methods. Neural networks have potential applications in many industrial areas such as advanced robotics, operations research, and process engineering. This book is concerned with the application of neural network technology to real industrial problems. It summarizes a three-year collaborative international project called ANNIE (Applications of Neural Networks for Industry in Europe) which was jointly funded by industry and the European Commission within the ESPRIT programme. As a record of a working project, the book gives an insight into the real problems faced in taking a new technology from the workbench into a live industrial application, and shows just how it can be achieved. It stresses the comparison between neural networks and conventional approaches. Even the non-specialist reader will benefit from understanding the limitations as well as the advantages of the new technology.
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Applications of Neural Networks

The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'.

Author: Alan Murray

Publisher: Springer Science & Business Media

ISBN: 9781475723793

Category: Science

Page: 322

View: 759

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Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'. For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.
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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.

Author: Lazaros S. Iliadis

Publisher: Springer

ISBN: 364241012X

Category: Computers

Page: 510

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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 of AI evolution, image and video analysis, classification, pattern recognition, social media and community based governance, medical applications of AI-bioinformatics and learning.
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Proceedings 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.

Author: Lazaros Iliadis

Publisher: Springer Nature

ISBN: 9783030805685

Category: Technology & Engineering

Page: 521

View: 592

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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 detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.
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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.

Author: Giacomo Boracchi

Publisher: Springer

ISBN: 3319651714

Category: Computers

Page: 737

View: 462

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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 papers presented at the 6th Mining Humanistic Data Workshop (MHDW 2017) and the 2nd Workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE).
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Business Applications of Neural Networks

The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise.This book reviews the state-of-the-art in current applications of neural ...

Author: Paulo J G Lisboa

Publisher: World Scientific

ISBN: 9789814494229

Category: Business & Economics

Page: 220

View: 866

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Neural networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice. Their use for risk assessment is also growing and they have been employed to visualise complex databases for marketing segmentation. This boom in applications covers a wide range of business interests — from finance management, through forecasting, to production. The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise. This book reviews the state-of-the-art in current applications of neural-network methods in three important areas of business analysis. It includes a tutorial chapter to introduce new users to the potential and pitfalls of this new technology. Contents:Preface: Business Applications of Neural Networks (P J G Lisboa & A Vellido)On the Use of Neural Networks for Analysis Travel Preference Data (S Cumings)Extracting Rules Concerning Market Segmentation from Artificial Neural Networks (R Setiono et al.)Characterization and Segmenting the Business-to-Consumer E-Commerce Market Using Neural Networks (A Vellido et al.)A Neurofuzzy Model for Predicting Business Bankruptcy (A H Boussabaine & M Wanous)Neural Networks for Analysis of Financial Statements (K Kiviluoto et al.)Developments in Accurate Consumer Risk Assessment Technology (M Somers & G Piper)Strategies for Exploiting Neural Networks in Retail Finance (I Sandhu)Novel Techniques for Profiling and Fraud Detection in Mobile Telecommunications (J Shawe-Taylor et al.)Detecting Payment Card Fraud with Neural Networks (K Hassibi)Money Laundering Detection with a Neural-Network (B Chartier & T Spillane)Utilising Fuzzy Logic and Neurofuzzy for Business Advantage (B Edisbury et al.) Readership: Business managers involved in retail, marketing and risk analysis, in small businesses, banks and insurance companies; students of neural networks or business studies. Keywords:Artificial Neural Networks;Rule Extraction;Segmentation;Credit Card Fraud;Customer Profiling;Bankruptcy Prediction;Risk Assessment;Money Laundering
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Industrial Applications of Neural Networks

This book is a collection of real-world applications of neural networks, which were presented at the ICANN '95 conference of the European Neural Network Society.

Author: Françoise Fogelman Soulié

Publisher: World Scientific

ISBN: 9789814525374

Category: Technology & Engineering

Page: 488

View: 260

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This book is a collection of real-world applications of neural networks, which were presented at the ICANN '95 conference of the European Neural Network Society. The contributions have been carefully selected by the Program Committee under three criteria: soundness of the technical approach, relevance for the application sector, and quality of the results obtained. The book covers all major areas of industrial and service activities: process engineering, control and monitoring, technical diagnosis and nondestructive testing, power systems, robotics, transportation, telecommunications, remote sensing, banking, finance and insurance, forecasting, document processing, and medicine. It thus represents one of the most comprehensive existing surveys of the applicability and use of neural networks in industry and services. Contents:Process Engineering, Control and MonitoringTechnical Diagnosis and Nondestructive TestingPower SystemsRoboticsTransportationTelecommunicationsRemote SensingBanking, Finance and InsuranceDocument ProcessingMedicine Readership: Undergraduates, engineers, researchers and scientists in neural networks, electrical & electronic engineering, ocean engineering, systems & knowledge engineering, pattern/ handwriting recognition, robotics, economics/finance and medicine. keywords:
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Scientific Applications of Neural Nets

This book, devoted to this highly interdisciplinary research area, addresses scientists and graduate students.

Author: John W. Clark

Publisher: Springer

ISBN: 366214235X

Category: Science

Page: 290

View: 164

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Neural-network models for event analysis are widely used in experimental high-energy physics, star/galaxy discrimination, control of adaptive optical systems, prediction of nuclear properties, fast interpolation of potential energy surfaces in chemistry, classification of mass spectra of organic compounds, protein-structure prediction, analysis of DNA sequences, and design of pharmaceuticals. This book, devoted to this highly interdisciplinary research area, addresses scientists and graduate students. The pedagogically written review articles range over a variety of fields including astronomy, nuclear physics, experimental particle physics, bioinformatics, linguistics, and information processing.
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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.

Author: John Macintyre

Publisher: Springer

ISBN: 3030202569

Category: Computers

Page: 546

View: 542

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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 - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.
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A Theory of Learning and Generalization

This is the first book to treat the problem of machine learning in conjunction with the theory of empirical processes, the latter being a well-established branch of probability theory.

Author: Mathukumalli Vidyasagar

Publisher: Springer

ISBN: UOM:39015038596170

Category: Computers

Page: 383

View: 823

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A Theory of Learning and Generalization provides a formal mathematical theory for addressing intuitive questions of the type: How does a machine learn a new concept on the basis of examples? How can a neural network, after sufficient training, correctly predict the output of a previously unseen input? How much training is required to achieve a specified level of accuracy in the prediction? How can one "identify" the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite interval of time? This is the first book to treat the problem of machine learning in conjunction with the theory of empirical processes, the latter being a well-established branch of probability theory. The treatment of both topics side by side leads to new insights, as well as new results in both topics. An extensive references section and open problems will help readers to develop their own work in the field.
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