02708oam 2200517 450 991074335290332120230906111737.0981-16-8929-6981-16-8930-X981-16-8930-X(OCoLC)1396160510(MiFhGG)GVRL572G(EXLCZ)992132559980004120230828h20222022 uy 0engurun|---uuuuatxtrdacontentcrdamediacrrdacarrierAdvances in machine learning for big data analysis /Satchidananda Dehuri, Yen-Wei Chen, editorsSingapore :Springer,[2022]©20221 online resource (xix, 239 pages) illustrations (some color), chartsIntelligent Systems Reference Library ;v.218Print version: Dehuri, Satchidananda Advances in Machine Learning for Big Data Analysis Singapore : Springer Singapore Pte. Limited,c2022 9789811689291 Includes bibliographical references.1. Multi-objective ant colony optimization : an updated review of approaches and applications -- 2. Cost-effective detection of cyber physical system attacks -- 3. A prognostic approach to crime analysis -- 4. A counter-based profiling scheme for improving locality through data and reducer placement -- 5. Hybridization of the higher order neural networks with the evolutionary optimization algorithms--an application to financial time series forecasting -- 6. Supply chain management (SCM) : employing various big data and metaheuristic strategies -- 7. Value of random vector functional link neural networks in software development effort estimation -- 8. Hybrid approach to prevent accidents at railway : an assimilation of big data, IoT and cloud -- 9. Hybrid decision tree for machine learning : a big data perspective.This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems.Intelligent systems reference library ;v. 218.Computational intelligenceMachine learningArtificial intelligenceData processingBig dataComputational intelligence.Machine learning.Artificial intelligenceData processing.Big data.780Dehuri SatchidanandaChen Yen-WeiMiFhGGMiFhGGBOOK9910743352903321Advances in machine learning for big data analysis3559287UNINA