eBook
Particle Swarm Optimisation : Classical and Quantum Perspectives
| Τίτλος: | Particle Swarm Optimisation : Classical and Quantum Perspectives |
|---|---|
| Περιγραφή: | Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives, the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle swarm optimisation (QPSO) algorithm. This globally convergent algorithm has fewer parameters, a faster convergence rate, and stronger searchability for complex problems.The book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles of the PSO algorithm. Examples illustrate how the PSO algorithm solves optimisation problems. The authors also analyse the reasons behind the shortcomings of the PSO algorithm.Moving on to the QPSO algorithm, the authors give a thorough overview of the literature on QPSO, describe the fundamental model for the QPSO algorithm, and explore applications of the algorithm to solve typical optimisation problems. They also discuss some advanced theoretical topics, including the behaviour of individual particles, global convergence, computational complexity, convergence rate, and parameter selection. The text closes with coverage of several real-world applications, including inverse problems, optimal design of digital filters, economic dispatch problems, biological multiple sequence alignment, and image processing. MATLAB®, Fortran, and C++ source codes for the main algorithms are provided on an accompanying downloadable resources.Helping you numerically solve optimisation problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. It not only explains how to use the algorithms, but also covers advanced topics that establish the groundwork for understanding. |
| Συγγραφείς: | Jun Sun, Choi-Hong Lai, Xiao-Jun Wu |
| Resource Type: | eBook. |
| Θέματα: | Mathematical optimization, Particles (Nuclear physics), Swarm intelligence, COMPUTERS / Programming / Algorithms, MATHEMATICS / General, MATHEMATICS / Number Systems |
| Categories: | MATHEMATICS / Optimization, COMPUTERS / Programming / Algorithms, TECHNOLOGY & ENGINEERING / Operations Research |
| Βάση Δεδομένων: | eBook Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: edsebk DbLabel: eBook Index An: 411950 RelevancyScore: 900 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 899.57275390625 |
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| Items | – Name: Title Label: Title Group: Ti Data: Particle Swarm Optimisation : Classical and Quantum Perspectives – Name: Abstract Label: Description Group: Ab Data: Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives, the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle swarm optimisation (QPSO) algorithm. This globally convergent algorithm has fewer parameters, a faster convergence rate, and stronger searchability for complex problems.The book presents the concepts of optimisation problems as well as random search methods for optimisation before discussing the principles of the PSO algorithm. Examples illustrate how the PSO algorithm solves optimisation problems. The authors also analyse the reasons behind the shortcomings of the PSO algorithm.Moving on to the QPSO algorithm, the authors give a thorough overview of the literature on QPSO, describe the fundamental model for the QPSO algorithm, and explore applications of the algorithm to solve typical optimisation problems. They also discuss some advanced theoretical topics, including the behaviour of individual particles, global convergence, computational complexity, convergence rate, and parameter selection. The text closes with coverage of several real-world applications, including inverse problems, optimal design of digital filters, economic dispatch problems, biological multiple sequence alignment, and image processing. MATLAB®, Fortran, and C++ source codes for the main algorithms are provided on an accompanying downloadable resources.Helping you numerically solve optimisation problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. It not only explains how to use the algorithms, but also covers advanced topics that establish the groundwork for understanding. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jun+Sun%22">Jun Sun</searchLink><br /><searchLink fieldCode="AR" term="%22Choi-Hong+Lai%22">Choi-Hong Lai</searchLink><br /><searchLink fieldCode="AR" term="%22Xiao-Jun+Wu%22">Xiao-Jun Wu</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Particles+%28Nuclear+physics%29%22">Particles (Nuclear physics)</searchLink><br /><searchLink fieldCode="DE" term="%22Swarm+intelligence%22">Swarm intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22COMPUTERS+%2F+Programming+%2F+Algorithms%22">COMPUTERS / Programming / Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22MATHEMATICS+%2F+General%22">MATHEMATICS / General</searchLink><br /><searchLink fieldCode="DE" term="%22MATHEMATICS+%2F+Number+Systems%22">MATHEMATICS / Number Systems</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Optimization%22">MATHEMATICS / Optimization</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Programming+%2F+Algorithms%22">COMPUTERS / Programming / Algorithms</searchLink><br /><searchLink fieldCode="ZK" term="%22TECHNOLOGY+%26+ENGINEERING+%2F+Operations+Research%22">TECHNOLOGY & ENGINEERING / Operations Research</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 531.16 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Mathematical optimization Type: general – SubjectFull: Particles (Nuclear physics) Type: general – SubjectFull: Swarm intelligence Type: general – SubjectFull: COMPUTERS / Programming / Algorithms Type: general – SubjectFull: MATHEMATICS / General Type: general – SubjectFull: MATHEMATICS / Number Systems Type: general Titles: – TitleFull: Particle Swarm Optimisation : Classical and Quantum Perspectives Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jun Sun – PersonEntity: Name: NameFull: Choi-Hong Lai – PersonEntity: Name: NameFull: Xiao-Jun Wu – PersonEntity: Name: NameFull: Jun Sun – PersonEntity: Name: NameFull: Choi-Hong Lai – PersonEntity: Name: NameFull: Xiao-Jun Wu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2012 – D: 04 M: 02 Type: profile Y: 2014 Identifiers: – Type: isbn-print Value: 9781439835760 – Type: isbn-print Value: 9780367381936 – Type: isbn-print Value: 9780367269357 – Type: isbn-electronic Value: 9781439835777 – Type: isbn-electronic Value: 9780429105999 – Type: isbn-electronic Value: 9781040057704 Titles: – TitleFull: Particle Swarm Optimisation : Classical and Quantum Perspectives Type: main |
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