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Advancements in applied metaheuristi...

Dey, Nilanjan, (1984-)

Advancements in applied metaheuristic computing

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advancements in applied metaheuristic computing/ Nilanjan Dey, editor.
其他作者:	Dey, Nilanjan,
出版者:	Hershey, Pennsylvania :IGI Global, : [2018],
面頁冊數:	1 online resource (xxi, 335 p.)
提要註:	"This book considers the foremost optimization algorithms in several applications. It deals primarily with methods and approaches that include meta-heuristics for further systems improvements. It grants substantial frameworks and the most contemporary empirical research outcomes in employing optimization algorithms"--
標題:	Artificial intelligence. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-4151-6
ISBN:	9781522541523 (ebook)

Advancements in applied metaheuristic computing
Advancements in applied metaheuristic computing[electronic resource] /Nilanjan Dey, editor. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xxi, 335 p.)

Includes bibliographical references and index.

Section 1. Meta-heuristic optimization-algorithms-based advanced applications. Chapter 1. Multi-objective optimal power flow using metaheuristic optimization algorithms with unified power flow controller to enhance the power system performance ; Chapter 2. Analyzing and predicting the QoS of traffic in wiMAX network using gene expression programming ; Chapter 3. Chaotic differential-evolution-based fuzzy contrast stretching method ; Chapter 4. Protein motif comparator using bio-inspired two-way K-means ; Chapter 5. Metaheuristics in manufacturing: predictive modeling of tool wear in machining using genetic programming ; Chapter 6. Intelligent computing in medical imaging: a study ; Chapter 7. Effect of SMES unit in AGC of an interconnected multi-area thermal power system with ACO-tuned PID controller ; Chapter 8. Meta-heuristic algorithms in medical image segmentation: a review -- Section 2. Genetic algorithm applications. Chapter 9. Optimized crossover jumpX in genetic algorithm for general routing problems: a crossover survey and enhancement ; Chapter 10. On developing and performance evaluation of adaptive second order neural network with GA-based training (ASONN-GA) for financial time series prediction ; Chapter 11. Hybrid non-dominated sorting genetic algorithm: II-neural network approach.

Restricted to subscribers or individual electronic text purchasers.

"This book considers the foremost optimization algorithms in several applications. It deals primarily with methods and approaches that include meta-heuristics for further systems improvements. It grants substantial frameworks and the most contemporary empirical research outcomes in employing optimization algorithms"--

ISBN: 9781522541523 (ebook)Subjects--Topical Terms:

233060
Artificial intelligence.

LC Class. No.: TA168 / .A286 2018e

Dewey Class. No.: 006.3

Advancements in applied metaheuristic computing
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050 4 $a TA168 $b .A286 2018e
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245 0 0 $a Advancements in applied metaheuristic computing $h [electronic resource] / $c Nilanjan Dey, editor.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xxi, 335 p.)
504 $a Includes bibliographical references and index.
505 0 $a Section 1. Meta-heuristic optimization-algorithms-based advanced applications. Chapter 1. Multi-objective optimal power flow using metaheuristic optimization algorithms with unified power flow controller to enhance the power system performance ; Chapter 2. Analyzing and predicting the QoS of traffic in wiMAX network using gene expression programming ; Chapter 3. Chaotic differential-evolution-based fuzzy contrast stretching method ; Chapter 4. Protein motif comparator using bio-inspired two-way K-means ; Chapter 5. Metaheuristics in manufacturing: predictive modeling of tool wear in machining using genetic programming ; Chapter 6. Intelligent computing in medical imaging: a study ; Chapter 7. Effect of SMES unit in AGC of an interconnected multi-area thermal power system with ACO-tuned PID controller ; Chapter 8. Meta-heuristic algorithms in medical image segmentation: a review -- Section 2. Genetic algorithm applications. Chapter 9. Optimized crossover jumpX in genetic algorithm for general routing problems: a crossover survey and enhancement ; Chapter 10. On developing and performance evaluation of adaptive second order neural network with GA-based training (ASONN-GA) for financial time series prediction ; Chapter 11. Hybrid non-dominated sorting genetic algorithm: II-neural network approach.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book considers the foremost optimization algorithms in several applications. It deals primarily with methods and approaches that include meta-heuristics for further systems improvements. It grants substantial frameworks and the most contemporary empirical research outcomes in employing optimization algorithms"-- $c Provided by publisher.
650 0 $2 96060 $a Artificial intelligence. $3 233060
650 0 $2 96060 $a Mathematical optimization. $3 251669
650 0 $a Heuristic algorithms. $3 433694
650 0 $a Systems engineering $x Data processing. $3 433693
700 1 $a Dey, Nilanjan, $d 1984- $e editor. $3 433692
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-4151-6

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