Автор: Modestus O. Okwu, Lagouge K. Tartibu
Издательство: Springer
Год: 2021
Страниц: 196
Язык: английский
Формат: pdf (true)
Размер: 17.2 Mb
This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others.
The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.
Artificial Neural Networks (ANNs) are known to be one of the most prevalent intelligent systems whose architecture or structure is modeled by mimicking the human brain. The system is built in such a way that hundreds of Simple Processing Units (SPU) are contained in a set of complex network systems. The SPU is collectively reinforced, strengthened, and intertwined in a network of multifaceted communication settings. The architecture consists of nodes of which each set is unassumingly connected to neurons capable of sending information and signals in the form of input from one end of the node to another following the system of connections. According to Albert Einstein, real-life problems can be addressed by looking deep into nature. Most of the real-life problem that has been solved so far followed the dimension of natural systems be it aquatic or terrestrial. Summarily, intelligent and soft computational techniques are developed looking deep into nature and mimicry approach of natural systems.
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