Decision-Making in Computational Intelligence-Based Systems
Description
This book delivers actionable insights through 21 peer-reviewed chapters featuring new methods, models, and applications based on computational intelligence. Discover cutting-edge tools to support smart, efficient decision-making in complex, real-world scenarios. Organized into three parts-prescriptive analytics, soft computing models, and practical case studies-it spans domains such as healthcare, energy, mobility, finance, and public services. Readers will find innovative approaches using fuzzy logic, machine learning, optimization, and hybrid systems. Ideal for researchers, practitioners, and graduate students, this book offers practical solutions for modern decision challenges across industries.
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Content
Using Shapley Additive Explanations for supporting individual and group recommendation: survey and new perspectives.- A P-based multiple criteria ordinal classification method where classes are described by subsets of "non-central" profiles.- A Framework of Targeted Marketing Based on the Outranking Approach.- SINDy meets Schelling. Transforming Agent-Based model spatial outputs into Dynamical Systems.- Optimizing Electric Vehicle Routes: A Hybrid Approach of Genetic Algorithm with Q-Learning.- Enhancing Clinical Decision-Making: An Integrated Approach Using ISPS and KMoS-SSA Framework.- New Rainfall Missing Values Estimation Proposal: Normal Ratio with Additive Correlation.
