Machine Learning Algorithms and Applications in Engineering

Prasenjit Chatterjee, Morteza Yazdani, Francisco Fernández-Navarro, Javier Pérez-Rodríguez, Prasenjit Chatterjee, Morteza Yazdani, Francisco Fernández-Navarro, Javier Pérez-Rodríguez

• Publisher: CRC Press
• Year: 2023
• Print ISBN: 9780367569129
• eBook ISBN: 9781000642384
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

Machine Learning (ML) is a sub field of artificial intelligence that uses soft computing and algorithms to enable computers to learn on their own and identify patterns in observed data, build models that explain the world, and predict things without having explicit pre-programmed rules and models. This book discusses various applications of ML in engineering fields and the use of ML algorithms in solving challenging engineering problems ranging from biomedical, transport, supply chain and logistics, to manufacturing and industrial. Through numerous case studies, it will assist researchers and practitioners in selecting the correct options and strategies for managing organizational tasks.

Table of contents

• Cover
• Half-Title Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Organization of the Book
• The Editors
• 1 Machine Learning for Smart Health Care
• 2 Predictive Analysis for Flood Risk Mapping Utilizing Machine Learning Approach
• 3 Machine Learning for Risk Analysis
• 4 Machine Learning Techniques Enabled Electric Vehicle
• 5 A Comparative Analysis of Established Techniques and Their Applications in the Field of Gesture Detection
• 6 Brain–Computer Interface for Dream Visualization using Deep Learning
• 7 Machine Learning and Data Analysis Based Breast Cancer Classification
• 8 Accurate Automatic Functional Recognition of Proteins: Overview and Current Computational Challenges
• 9 Taxonomy of Shilling Attack Detection Techniques in Recommender System
• 10 Machine Learning Applications in Real-World Time Series Problems
• 11 Prediction of Selective Laser Sintering Part Quality Using Deep Learning
• 12 CBPP: An Efficient Algorithm for Privacy-Preserving Data Publishing of 1:M Micro Data with Multiple Sensitive Attributes
• 13 Classification of Network Traffic on ISP Link and Analysis of Network Bandwidth during COVID-19
• 14 Integration of AI/Ml in 5G Technology toward Intelligent Connectivity, Security, and Challenges
• 15 Electrical Price Prediction using Machine Learning Algorithms
• 16 Machine Learning Application to Predict the Degradation Rate of Biomedical Implants
• 17 Predicting the Outcomes of Myocardial Infarction Using Neural Decision Forest
• 18 Image Classification Using Contrastive Learning
• Index