This book is a collection of best-selected research papers presented at the International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2024) held at BITS Pilani, K K Birla Goa Campus, Goa, India, during September 20-21, 2024. It includes state-of-the-art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book is useful for academicians, research scholars, and industry persons. …mehr
This book is a collection of best-selected research papers presented at the International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2024) held at BITS Pilani, K K Birla Goa Campus, Goa, India, during September 20-21, 2024. It includes state-of-the-art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book is useful for academicians, research scholars, and industry persons.
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Inhaltsangabe
Optimizing Traffic Signal Timings in Urban Intersections A Methodology Incorporating PCU and Lane Width.- Texture Feature Analysis and Clustering of Remotely Sensed Data using Gray Level Co-occurrence Matrix and Haralick Features.- Comparative Analysis of Deep Learning Models for VM Load Prediction.- Optimizing Task Allocation in Cloud Computing Environments using Hybrid Meta-heuristic Algorithms.- Contrastive Scenarios Enhancing ML Model Interpretability.
Optimizing Traffic Signal Timings in Urban Intersections A Methodology Incorporating PCU and Lane Width.- Texture Feature Analysis and Clustering of Remotely Sensed Data using Gray Level Co-occurrence Matrix and Haralick Features.- Comparative Analysis of Deep Learning Models for VM Load Prediction.- Optimizing Task Allocation in Cloud Computing Environments using Hybrid Meta-heuristic Algorithms.- Contrastive Scenarios Enhancing ML Model Interpretability.
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