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雷达卡
Author(s): Mohit Kumar
Description:
This coursebook comprises 16 chapters, each covering intertwining concepts at two key levels of interest to the scientific community: Artificial Intelligence and Edge/Cloud Computing.
Chapter One explores navigating next-generation network architecture, unleashing the power of SDN, NFV, NS, and AI convergence. Chapter Two examines OctoEdge, an octopus-inspired adaptive edge computing architecture. Chapter Three discusses the development of optimized machine learning-oriented models.
Chapter Four focuses on leveraging multimodal data and deep learning for enhanced stock market prediction. Chapter Five delves into context-dependent sentiment analysis using machine learning. Chapter Six investigates enhancing thyroid cancer prediction by applying machine learning algorithms to clinical data.
Chapter Seven presents an LSTM-oriented approach for next-word prediction using deep learning. Chapter Eight analyzes churn prediction in social networks using a modified BiLSTM-CNN model. Chapter Nine addresses security concerns in healthcare fog computing using IoT and blockchain.
Chapter Ten highlights the smart agriculture revolution with cloud and IoT-based solutions for sustainable crop management and precisionfarming. Chapter Eleven explores a greedy particle swarm optimization approach using the Lecky ReLU function for solving minimum spanning tree problems.
Chapter Twelve introduces an SDN-deployed secure application design framework for IoT using game theory. Chapter Thirteen presents a framework for PLM in Industry 4.0 based on industrial blockchain.
Chapter Fourteen discusses a machine learning-enabled smart agriculture classification technique for edge devices using a remote sensing platform. Chapter Fifteen examines a lightweight intelligent detection approach for interest flooding attacks. Chapter Sixteen describes an Internet of Vehicles model architecture with seven layers.
AI-Based Advanced Optimization Techniques for Edge Computing (2025).pdf
(19.86 MB, 需要: RMB 19 元)
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