東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Advancements in applied metaheuristi...

Dey, Nilanjan, (1984-)

Linked to FindBook

Google Book

Amazon

博客來

Advancements in applied metaheuristic computing

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advancements in applied metaheuristic computing/ Nilanjan Dey, editor.
other author:	Dey, Nilanjan,
Published:	Hershey, Pennsylvania :IGI Global, : [2018],
Description:	1 online resource (xxi, 335 p.)
[NT 15003449]:	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.
Subject:	Systems engineering - Data processing. -
Online resource:	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:

1581530
Systems engineering
--Data processing.

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

Dewey Class. No.: 006.3

Advancements in applied metaheuristic computing
LDR:02609nmm a2200277 a 4500 001 2137986
003 IGIG
005 20181029175340.0
006 m o d
007 cr cn
008 181117s2018 pau fob 001 0 eng d
010 $z 2017028945
020 $a 9781522541523 (ebook)
020 $a 9781522541516 (hardcover)
035 $a (OCoLC)1011023965
035 $a 1071025357
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
050 4 $a TA168 $b .A286 2018e
082 0 4 $a 006.3 $2 23
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 $a Systems engineering $x Data processing. $3 1581530
650 0 $a Heuristic algorithms. $3 1066682
650 0 $a Mathematical optimization. $3 517763
650 0 $a Artificial intelligence. $3 516317
700 1 $a Dey, Nilanjan, $d 1984- $e editor. $3 3231517
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-4151-6