Big Data and Data Science Engineering
Description
This book reports state-of-the-art results in Big Data and Data Science Engineering in both printed and electronic form. Studies in Computation Intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world.
This book publishes original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.
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Content
Using Modified SA With Adaptive Clustering for Solving The Electric Vehicle Routing Problem.-Utilizing Machine Learning Methods For Predicting Stock Market Movement A Case StudyWith The S&P 500 Index.- Career awareness of foreigners working in Hokkaido as a result of studying abroad.- Predicting Power Plant Start Up Time Leveraging Random Forest Algorithm and Univariate Selection for Enhanced Generator Performance.- Explainable Sentiment Analysis Utilizing Deep Learning Methods and LIME.- Quantum safe Hash Time locked Cross chain Transaction Mechanism.- Positive Computing through Images and Scents.- Edge Enhanced ConvNeXt Unet for Foveal Avascular Zone Segmentation from Optical Coherence Tomography Angiography.- Edge Enhanced ConvNeXt Unet for Foveal Avascular Zone Segmentation from Optical Coherence Tomography Angiography.- Wavelet Enhanced GAN for Image Outpainting.- Wood Strength Prediction via Log Section Images using Filtered Swin Transformer Model.- Lifelog Tagging System Using Physiological and Environmental Indicators.- Governance of Cyber Threat Information Sharing for Public Private Partnerships Comparative Analysis of National Cases.- Extracting Unique Keywords Related to Customer Engagement from Review Text Using UncorrelatedWeights Estimation in Neural Networks.
