Machine Intelligence, Tools, and Applications
Description
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.
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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.