Ebook: Applications of Computational Intelligence Techniques in Communications
The book titled "Applications of Computational Intelligence Techniques in Communications" is a one-stop platform for the researchers, academicians, and people from industry to get a thorough understanding of the latest research in the field of communication engineering. Over the past decade, a manyfold increase in the use of computational intelligence techniques has been identified for obtaining the most optimal and timely solution to a problem. The various aspects covering the significant contribution of numerous computational intelligence techniques have been discussed in detail in this book.
Today’s era of machine learning and Internet of Things (IoT) is demanding as high as possible data rate which has resulted into tremendous increased speed of communication. To match-up the pace, the computational intelligence is posing to be the most efficient and favourite tool. The book aims to cover the current technological advancements in the field of communication engineering and give a detailed prospect of computational intelligence to its readers.
Swarm Intelligence (SI) is an important concept when it comes to Artificial Intelligence. In nature, Swarm-based Intelligence is seen in a diversified manner, e.g., colonies of ants, flocks of birds, schools of fish, herds of animals etc. These swarms possess a very unique phenomenon, i.e., a collective behaviour on a global scale, whereas individual swarms show restricted behaviour with the surrounding environment on a local scale. This collective global behaviour has been studied by researchers in an exhaustive manner in nature and simulated in the form of artificial swarms to solve large-scale optimization problems in the field of computational intelligence. Some of the well-established swarm intelligence-based optimization algorithms are Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm etc. This chapter deals with the explanation of optimization techniques based on SI and their application in the field of communication technology focusing on Unmanned Aerial Vehicle (UAV) optimal placement problem and optimal path planning of UAV.
This book will be a great support to the people working in the field of IoT, machine learning, healthcare, optimization, filter design, 5G and beyond, signal processing etc. The chapters included here will expose its audience to various newly introduced and advanced computational intelligence techniques applicable in communication domain. The readers will be exposed multiple interdisciplinary areas of research in communication and will get the motivation to work in collaboration with other professionals from both the academia and industry.
Today’s era of machine learning and Internet of Things (IoT) is demanding as high as possible data rate which has resulted into tremendous increased speed of communication. To match-up the pace, the computational intelligence is posing to be the most efficient and favourite tool. The book aims to cover the current technological advancements in the field of communication engineering and give a detailed prospect of computational intelligence to its readers.
Swarm Intelligence (SI) is an important concept when it comes to Artificial Intelligence. In nature, Swarm-based Intelligence is seen in a diversified manner, e.g., colonies of ants, flocks of birds, schools of fish, herds of animals etc. These swarms possess a very unique phenomenon, i.e., a collective behaviour on a global scale, whereas individual swarms show restricted behaviour with the surrounding environment on a local scale. This collective global behaviour has been studied by researchers in an exhaustive manner in nature and simulated in the form of artificial swarms to solve large-scale optimization problems in the field of computational intelligence. Some of the well-established swarm intelligence-based optimization algorithms are Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm etc. This chapter deals with the explanation of optimization techniques based on SI and their application in the field of communication technology focusing on Unmanned Aerial Vehicle (UAV) optimal placement problem and optimal path planning of UAV.
This book will be a great support to the people working in the field of IoT, machine learning, healthcare, optimization, filter design, 5G and beyond, signal processing etc. The chapters included here will expose its audience to various newly introduced and advanced computational intelligence techniques applicable in communication domain. The readers will be exposed multiple interdisciplinary areas of research in communication and will get the motivation to work in collaboration with other professionals from both the academia and industry.
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