Multi-Criteria Decision-Making and Optimum Design with Machine Learning : A Practical Guide

Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide

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Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide

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Multi-Criteria Decision-Making and Optimum Design with Machine Learning : A Practical Guide

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Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide

Overall Rating: 2.3 / 5 (average from multiple review sources, as of 23 Jun 2026)
Based on a total of 48,964 customer reviews from independent review platforms.

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The values are derived from publicly available retailer ratings from platforms such as Feefo, http://Reviews.io , Trustpilot, and others, and are aggregated monthly.

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This title will be released on July 20, 2026. Pre-order now. Express Delivery available with Amazon Prime.
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Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide

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Multi-Criteria Decision-Making and Optimum Design with Machine Learning : A Practical Guide

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As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems.This book is intended to guide researchers, practitioners, and students interested in the intersection of ML and MCDM for optimal design. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is a comprehensive resource that bridges the gap between ML and MCDM.It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems.Through case studies and examples, it showcases the effectiveness of these techniques in optimal design.The book also provides a comparative analysis of conventional MCDM algorithms and machine learning techniques, enabling readers to make informed decisions about their use in different scenarios.It also delves into emerging trends, providing insights into future directions and poten
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