LEADER 03868nam 22006135 450 001 9910878059903321 005 20250626163856.0 010 $a3-031-65392-0 024 7 $a10.1007/978-3-031-65392-6 035 $a(MiAaPQ)EBC31572120 035 $a(Au-PeEL)EBL31572120 035 $a(CKB)33566467300041 035 $a(DE-He213)978-3-031-65392-6 035 $a(EXLCZ)9933566467300041 100 $a20240730d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Intelligence, Tools, and Applications $eProceedings of the International Conference on Machine Intelligence, Tools, and Applications?ICMITA 2024 /$fedited by Satchidananda Dehuri, Sung-Bae Cho, Venkat Prasad Padhy, Poonkuntrun Shanmugam, Ashish Ghosh 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (435 pages) 225 1 $aLearning and Analytics in Intelligent Systems,$x2662-3455 ;$v40 311 08$a3-031-65391-2 327 $aFuzzy 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. 330 $aThis book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML). This would enable the readers with a strong understanding of critical issues in ML by providing both broad and detailed perspectives on cutting-edge theories, algorithms, and tools. This will become a single source of reference on conceptual, methodological, technical, and managerial issues, as well as provide insight into emerging trends and future opportunities in the discipline of ML. This book contains altogether 36 chapters in the area of ML and its applications. 410 0$aLearning and Analytics in Intelligent Systems,$x2662-3455 ;$v40 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aMachine learning 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aMachine Learning 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aMachine learning. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aMachine Learning. 676 $a006.3 700 $aDehuri$b Satchidananda$01615124 701 $aCho$b Sung-Bae$01615126 701 $aPadhy$b Venkat Prasad$01758537 701 $aShanmugam$b Poonkuntrun$01758538 701 $aGhosh$b Ashish$01346642 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910878059903321 996 $aMachine Intelligence, Tools, and Applications$94196773 997 $aUNINA