Applied Machine Learning for IoT and Data Analytics (Volume 1) is an integrated exploration of nature-inspired optimisation techniques within the emerging Industry 5.0 paradigm- Positioned at the intersection of artificial intelligence, computational intelligence, industrial engineering, and cyber-physical systems, this volume centres on human-centricity, sustainability, resilience, and intelligent automation.
The book comprehensively reviews evolutionary computation, swarm intelligence, neural computation, and hybrid metaheuristics, explaining how these methods can be systematically designed, statistically validated, and benchmarked for real-world deployment. Foundational chapters address Explainable AI (XAI), statistical experimental design, ANOVA-based modelling, parameter tuning strategies, and performance evaluation frameworks.
Through fifteen carefully curated chapters, the book presents practical case studies in wireless sensor networks, smart manufacturing, micro-machining, welding optimisation, renewable energy systems, motor control, wireless communications, banking automation, and advanced antenna design. Emphasis is placed on experimental rigour, benchmarking, and reproducibility—bridging the gap between theoretical advancements and industrial implementation.
Key Features:
-Comprehensive review of classical and hybrid bio-inspired algorithms.
-Integration of optimisation techniques within the Industry 5.0 framework
-Covers Explainable AI for transparent optimisation systems with a strong focus on experimental design, ANOVA modelling, and statistical validation.
-Practical case studies across manufacturing, energy, communications, and automation
-Emphasis on reproducibility and methodological rigour with forward-looking insights into AI-enhanced and explainable optimisation trends.
eBook - ePub
Experimental Design of Bio-Inspired Algorithms for Optimization Problems in Industry 5.0
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Experimental Design of Bio-Inspired Algorithms for Optimization Problems in Industry 5.0
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Table of contents
- BENTHAM SCIENCE PUBLISHERS LTD.
- FOREWORD
- PREFACE
- List of Contributors
- Explainable AI in Industry 5.0: Principles, Mission, and Future Direction
- Optimization of Process Parameters Using ANOVA: A Review
- Study on Intelligent WSN Localization Error Using Anova-based Optimization Technique
- Modeling and Optimization of Process Parameters of Grinding Using ANOVA Analysis for Industry 5.0
- An ANOVA-based Optimization Technique to Predict the Part Weight During Micro-powder Injection Molding of Alumina Feedstock
- ANOVA-based Analysis and Optimization of Micro-performances during Blend Hole Generation on Glass
- Micro-ECDM Performance Analysis Based on ANOVA
- Metaheuristics-based Parametric Optimization of Semi-automatic MIG Welded Austenitic AISI 304 Stainless Steel for Industry 5.0
- Bio-Inspired Algorithm-based Performance Enhancement of Solar-powered SR Motor for Sustainable Marine Propulsion
- Experimental Framework for Bio-inspired Algorithms in Wireless Communication: An Industry 5.0 Perspective.
- Artificial Intelligence and Robotic Process Automation in the Indian Banking Industry: Implementation Strategies, Applications, Benefits, and Sustainability
- Artificial Neural Network-Based Modelling of Hexagonal Slotted Microstrip Patch Antenna Operating at 4.5 GHz for 5G Communication in Industry 5.0
- Comparative Study of Hybrid GAPSO for Parametric Optimization of the Liquid Flow Model
- Photovoltaic Cell Performance Assessment Using the Hybrid CSPSO Algorithm
- Design of Rectangular Microstrip Patch Antenna Using ANOVA at 26 GHz for Industry 5.0
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Yes, you can access Experimental Design of Bio-Inspired Algorithms for Optimization Problems in Industry 5.0 by Pijush Dutta,Sudip Mandal,Korhan Cengiz in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.