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Applications of Artificial Intelligence Techniques in Industry 4.0

  • Aydin Azizi

Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Aydin Azizi
    Pages 1-6
  3. Aydin Azizi
    Pages 7-17
  4. Aydin Azizi
    Pages 19-25
  5. Aydin Azizi
    Pages 49-61

About this book

Introduction

This book is to presents and evaluates a way of modelling and optimizing nonlinear RFID Network Planning (RNP) problems using artificial intelligence techniques. It uses Artificial Neural Network models (ANN) to bind together the computational artificial intelligence algorithm with knowledge representation an efficient artificial intelligence paradigm to model and optimize RFID networks.

This effort leads to proposing a novel artificial intelligence algorithm which has been named hybrid artificial intelligence optimization technique to perform optimization of RNP as a hard learning problem. This hybrid optimization technique consists of two different optimization phases. First phase is optimizing RNP by Redundant Antenna Elimination (RAE) algorithm and the second phase which completes RNP optimization process is Ring Probabilistic Logic Neural Networks (RPLNN).

The hybrid paradigm is explored using a flexible manufacturing system (FMS) and the results are compared with well-known evolutionary optimization technique namely Genetic Algorithm (GA) to demonstrate the feasibility of the proposed architecture successfully.

Keywords

Flexible Manufacturing Systems Inventory Management RFID Network Planning RFID Antenna Artificial Neural Network ANN Redundant Antenna Elimination RAE Ring Probabilistic Logic Neural Networks RPLNN Hybrid Artificial Intelligence Algorithm Genetic Algorithm

Authors and affiliations

  • Aydin Azizi
    • 1
  1. 1.Department of EngineeringGerman University of Technology in OmanMuscatOman

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-13-2640-0
  • Copyright Information The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2019
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-13-2639-4
  • Online ISBN 978-981-13-2640-0
  • Series Print ISSN 2191-530X
  • Series Online ISSN 2191-5318
  • Buy this book on publisher's site