04429nam a22005895i 4500 978-3-031-65392-6 DE-He213 20251030112659.0 cr nn 008mamaa 240730s2024 sz | s |||| 0|eng d 9783031653926 978-3-031-65392-6 10.1007/978-3-031-65392-6 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Machine Intelligence, Tools, and Applications [electronic resource] : Proceedings of the International Conference on Machine Intelligence, Tools, and Applications—ICMITA 2024 / edited by Satchidananda Dehuri, Sung-Bae Cho, Venkat Prasad Padhy, Poonkuntrun Shanmugam, Ashish Ghosh. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XII, 422 p. 211 illus., 160 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Learning and Analytics in Intelligent Systems, 2662-3455 ; 40 Fuzzy Guided Genetic Algorithm Routing for Energy Conservation in Wireless Sensor Networks -- Comparative Analysis of Prediction Models for Software Bug Prediction -- Mandelbug Classification Engine Transfer Learning and NLP Approach -- Software Maintenance Prediction Using Regression Models -- Rough Set ELM Classifier and Deep Architecture for Remote Sensing Images -- Design of an Efficient Model for Satellite Image Classification Using Graph Neural Networks and Elephant Herding Optimization -- Multifaceted Analysis of Climate Trends and Air Quality in Indian Metropolises A Machine Learning and Time Series Forecasting Approach -- Machine Learning based Analysis and Forecasting of Electricity Demand in Misamis Occidental Philippines -- Implementation and Optimization of Swarm based System for Multi Agent Coordination and Task Execution in Marine Environment -- Implementing Deep NN for Plant Disease Detection and Diagnosis -- A PSO approach for two warehouse inventory problem with imperfect quality and variable discount -- Design of Intraday Stock Price Prediction Model using Machine Learning via Technical Indicators. This book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML). This would enable the readers with a strong understanding of critical issues in ML by providing both broad and detailed perspectives on cutting-edge theories, algorithms, and tools. This will become a single source of reference on conceptual, methodological, technical, and managerial issues, as well as provide insight into emerging trends and future opportunities in the discipline of ML. This book contains altogether 36 chapters in the area of ML and its applications. Computational intelligence. 64052 Artificial intelligence. 58441 Machine learning. 55059 Computational Intelligence. 64052 Artificial Intelligence. 58441 Machine Learning. 55059 Dehuri, Satchidananda. editor. edt http://id.loc.gov/vocabulary/relators/edt 81542 Cho, Sung-Bae. editor. edt http://id.loc.gov/vocabulary/relators/edt 81543 Padhy, Venkat Prasad. editor. edt http://id.loc.gov/vocabulary/relators/edt 81544 Shanmugam, Poonkuntrun. editor. edt http://id.loc.gov/vocabulary/relators/edt 81545 Ghosh, Ashish. editor. (orcid)0000-0003-1548-5576 https://orcid.org/0000-0003-1548-5576 edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031653919 Printed edition: 9783031653933 Printed edition: 9783031653940 Learning and Analytics in Intelligent Systems, 2662-3455 ; 40 69955 https://doi.org/10.1007/978-3-031-65392-6 ZDB-2-INR ZDB-2-SXIT 62053 62053