Metaheuristics for Enterprise Data Intelligence

Metaheuristics for Enterprise Data Intelligence (Advances in Metaheuristics)
Author: Kaustubh Vaman Sakhare (Editor), Vibha Vyas (Editor), Apoorva S Shastri (Editor) &
Publisher finelybook 出版社:‏ CRC Press
Edition 版本:‏ 1st
Publication Date 出版日期:‏ 2024-08-07
Language 语言: English
Print Length 页数: 146 pages
ISBN-10: 1032683775
ISBN-13: 9781032683775

Book Description

With the emergence of the data economy, information has become integral to business excellence. Every enterprise, irrespective of its domain of interest, carries and processes a lot of data in their day-to-day activities. Converting massive datasets into insightful information plays an important role in developing better business solutions. Data intelligence and its analysis pose several challenges in data representation, building knowledge systems, issue resolution and predictive systems for trend analysis and decisionmaking. The data available could be of any modality, especially when data is associated with healthcare, biomedical, finance, retail, cybersecurity, networking, supply chain management, manufacturing, etc. The optimization of such systems is therefore crucial to leveraging the best outcomes and conclusions. To this end, AI-based nature-inspired optimization methods or approximation-based optimization methods are becoming very powerful. Notable metaheuristics include genetic algorithms, differential evolution, ant colony optimization, particle swarm optimization, artificial bee colony, grey wolf optimizer, political optimizer, cohort intelligence and league championship algorithm. This book provides a systematic discussion of AI-based metaheuristics application in a wide range of areas, including big data intelligence and predictive analytics, enterprise analytics, graph optimization algorithms, machine learning and ensemble learning, computer vision enterprise practices and data benchmarking.