Data Science and Applications : Proceedings of ICDSA 2025, Volume 5 (Lecture Notes in Networks and Systems)

Nanda, Satyasai Jagannath (EDT)/ Yadav, Rajendra Prasad (EDT)/ Prasad, Mukesh (EDT)

Springer Nature Switzerland AG（2026/01発売）

• 製本 Paperback:紙装版/ペーパーバック版
• 言語 ENG
• 商品コード 9783032128263

Full Description

This book gathers outstanding papers presented at the 6th International Conference on Data Science and Applications (ICDSA 2025), organized by Soft Computing Research Society (SCRS) and Malaviya National Institute of Technology Jaipur, India, from 16 to 18 July 2025. The book is divided into eight volumes, and it covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

Contents

Machine Learning-Based Prediction of MRP Process Runtime and Memory Usage for Scalable Business Operations.- Crop Yield Prediction of Indian States based on Machine Learning and Feature Engineering.- Heart Disease Prediction using Machine Learning: A Comparative Approach on CHSLB and Cleveland Datasets with Advanced Modeling Techniques.- Extensive Analysis of Electric Vehicles: Battery Management Systems, Machine Learning Strategies to Prevent Thermal Runaway for Improved Safety and Performance.- Analysis of Security Vulnerabilities in OSS For Predicting Diabetes using OWASP ZAP.- A SEM-Neural Network Approach to Predict Customers Intention to Purchase Battery Electric Vehicles in the Bangalore.- Automating Court Judgement Prediction and Explanation for Indian Legal Cases.- Deep Learning-Driven Real Time Video Summarization with Temporal Modeling and Attention Mechanism.- Integrated Monitoring System for Railway Wagon Coal Load Tracking: Sensor-Based Detection and Real-Time Notification.- Emotion Recognition from ECG Signals using Deep Neural Networks.- Brain Tumor Survival Prediction using MRI Segmentation and Autoencoder Features.- Analysis of Conventional vs Machine Learning Models for Decision-Making in Logistics based on Uncertainty Quantification.