Metaheuristics for Enterprise Data Intelligence (Advances in Metaheuristics)

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Synopsis
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.
Copyright:
2025

Book Details

Book Quality:
Publisher Quality
Book Size:
168 Pages
ISBN-13:
9781040096505
Related ISBNs:
9781040096475, 9781032699806, 9781032683775
Publisher:
CRC Press
Date of Addition:
Copyrighted By:
selection and editorial matter, Kaustubh Vaman Sakhare, Vibha Vyas and Apoorva S Shastri
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Reference, Computers and Internet, Business and Finance, Mathematics and Statistics
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.
Edited by:
Kaustubh Vaman Sakhare
Edited by:
Vibha Vyas
Edited by:
Apoorva S Shastri

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