Metaheuristics and Reinforcement Techniques by Adwitiya Sinha (.ePUB)+
File Size: 14.5 MB
Metaheuristics and Reinforcement Techniques for Smart Sensor Applications by Adwitiya Sinha, Manju, Samayveer Singh
Requirements: .ePUB, .PDF reader, 14.5 MB
Overview: This book discusses the fundamentals of wireless sensor networks,and the prevailing method and trends of smart sensor applications. It presents analytical modelling to foster the understanding of network challenges in developing protocols for next-generation communication standards. Metaheuristic algorithms are optimization techniques that draw inspiration from natural and abstract concepts to solve complex problems. Unlike exact algorithms, which aim for optimal solutions, metaheuristics prioritize speed and adaptability, making them suitable for addressing computationally challenging problems with large solution spaces. These algorithms play a vital role in various fields, including combinatorial optimization, Machine Learning, and operations research. In the realm of WSNs, metaheuristic algorithms are instrumental in optimizing routing protocols. WSNs comprise nodes with limited computational resources, energy constraints, and often operate in dynamic environments. Efficient data routing in WSNs is critical for conserving energy, extending network lifetime, and ensuring reliable data delivery. Genetic Algorithms (GA) for CH selection play a pivotal role in the efficiency and performance of wireless sensor networks. The GA algorithm employs evolutionary principles to strategically choose CHs that are responsible for efficient and reliable data transmission in the network.
Genre: Non-Fiction > Tech & Devices
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