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Applied Intelligence for Industry 4.0

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AdaBoost Classifier
Adults Dataset
AI
algorithms
autonomous systems engineering
Average Monthly Hours
Category=UYQ
computational intelligence
computing
Convolutional Neural Network Models
cyber security analytics
cybersecurity
data science
Dataset Split
Dengue Case
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Feature Selection Techniques
Gradient Boosting
health informatics
Human-computer interaction
Hyperparameter Tuning
Industry 4.0
Informatics
Information retrieval
internet of things
Machine Learning
Machine Learning Algorithms
Machine Learning Approach
Machine Learning Classifiers
machine learning for industrial diagnosis
Machine Learning Model
MV Technique
Naive Bayes Algorithm
neural network models
Random Forest Classifier
RF
smart computing
smart sensor networks
Soil Quality
Spam Detection
Spectrum Sensing
Supervised Machine Learning
SVM
Synthetic Minority Oversampling Technique
transfer learning methods
Vice Versa

Product details

  • ISBN 9781032187556
  • Weight: 520g
  • Dimensions: 178 x 254mm
  • Publication Date: 30 Jan 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

We are all aware that artificial intelligence (AI) has brought a change in our lives, driven by a new form of interaction between man and machine. We are in the era of the fourth Industrial Revolution (IR) where AI plays vital roles in human development by enabling extraordinary technological advances making fundamental changes to the way we live, work and relate to one another. It is an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. We need to prepare our graduates as well as researchers to conduct their research with 4.0 IR-related technologies. We need to develop policies and implement those policies to focus on the components of 4.0 IR for sustainable developments. Applied Intelligence for Industry 4.0 will cover cutting edge topics in the fields of AI and industry 4.0. The text will appeal to beginners and advanced researchers in computer science, information sciences, engineering and robotics.

Features

  • Discusses advance data mining, feature extraction and classification algorithms for disease detection, cyber security detection and prevention, soil quality assessment and other industrial applications

  • Includes the parameter optimization and explanation of intelligent approaches for business applications

  • Presents context-aware smart insights and energy efficient and smart computing for the next-generation of smart industry
About

Nazmul Siddique received the Dipl.-Ing. degree in Cybernetics and Automation from Dresden University of Technology, Dresden, Germany, MSc in Computer Science from Bangladesh University of Engineering and Technology, Dhaka, Bangladesh and the Ph.D in Intelligent Control from the University of Sheffield, England, U.K. He has been a Lecturer with the School of Computing, Engineering and Intelligent Systems, University of Ulster Magee Campus, Londonderry, U.K since 2001. He was previously with the Computer Science and Engineering Discipline, Khulna University, Khulna, Bangladesh. He has been a guest editor of seven special issues of several reputed journals. He has served as committee member and chair of a number of national and international conferences. He is a senior member of IEEE. He is on the Editorial Board of a number of International Journals. Dr. Siddique has published over 170 journal, refereed conference papers, book chapters, and five books (John Wiley, Springer, Taylor & Francis). His research interests are in the fields of intelligent systems, computational intelligence, stochastic systems, and Markov modeling.