Xin-She Yang
                        
                                        
                        
    
    
            
            
            
                                                                
    
                    
                
                    
    
    
                
    
                    
            
                
            
            
                                                    
    
                    
                
                    
    
    
                
    
                    
            
                
            
            
                                                    
    
                    
                
                    
    
    
                
    
                    
            
                
            
            
                                                    
    
                    
                
                    
    
    
                
    
                    
            
                
            
            
                                                    
    
                    
                
                    
    
    
                
    
                    
            
                
            
            
                                    
            
        
                                                
                Mathematical Foundations of Nature-Inspired Algorithms
Ebook (PDF Format)
            This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization pro…
        
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                                    Beschreibung
                        This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.
                    
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Produktdetails
Weitere Autoren: He, Xing-Shi
- ISBN: 978-3-030-16936-7
- EAN: 9783030169367
- Produktnummer: 31357983
- Verlag: Springer
- Sprache: Englisch
- Erscheinungsjahr: 2019
- Plattform: PDF
- Masse: 1'600 KB
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