東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Applications of flower pollination a...

Dey, Nilanjan.

FindBook

Google Book

Amazon

博客來

Applications of flower pollination algorithm and its variants

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applications of flower pollination algorithm and its variants/ edited by Nilanjan Dey.
其他作者:	Dey, Nilanjan.
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	xi, 239 p. :ill., digital ;24 cm.
內容註:	Flower Pollination Algorithm: Basic Concepts, Variants and Applications -- Optimization of Non-rigid Demons Registration using Flower Pollination Algorithm -- Adaptive Neighbour Heuristics Flower Pollination Algorithm Strategy for Sequence Test Generation -- Implementation of flower pollination algorithm to the design optimization of planar antennas -- Flower Pollination Algorithm for Slope Stability Analysis -- Optimum Sizing of Truss Structures Using A Hybrid Flower Pollination -- Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm -- Multi-Objective Flower Pollination Algorithm and its Variants to Find Optimal Golomb Rulers for WDM System -- Applications of Flower Pollination algorithm in Wireless Sensor Networking and Image processing: A detailed study -- Flower pollination algorithm tuned PID controller for multi-source interconnected multi area power system.
Contained By:	Springer Nature eBook
標題:	Computer algorithms. -
電子資源:	https://doi.org/10.1007/978-981-33-6104-1
ISBN:	9789813361041

Applications of flower pollination algorithm and its variants
Applications of flower pollination algorithm and its variants[electronic resource] /edited by Nilanjan Dey. - Singapore :Springer Singapore :2021. - xi, 239 p. :ill., digital ;24 cm. - Springer tracts in nature-inspired computing,2524-552X. - Springer tracts in nature-inspired computing..

Flower Pollination Algorithm: Basic Concepts, Variants and Applications -- Optimization of Non-rigid Demons Registration using Flower Pollination Algorithm -- Adaptive Neighbour Heuristics Flower Pollination Algorithm Strategy for Sequence Test Generation -- Implementation of flower pollination algorithm to the design optimization of planar antennas -- Flower Pollination Algorithm for Slope Stability Analysis -- Optimum Sizing of Truss Structures Using A Hybrid Flower Pollination -- Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm -- Multi-Objective Flower Pollination Algorithm and its Variants to Find Optimal Golomb Rulers for WDM System -- Applications of Flower Pollination algorithm in Wireless Sensor Networking and Image processing: A detailed study -- Flower pollination algorithm tuned PID controller for multi-source interconnected multi area power system.

This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.

ISBN: 9789813361041

Standard No.: 10.1007/978-981-33-6104-1doiSubjects--Topical Terms:

523872
Computer algorithms.

LC Class. No.: QA76.9.A43 / A675 2021

Dewey Class. No.: 005.13

Applications of flower pollination algorithm and its variants
LDR:03144nmm a2200337 a 4500 001 2239192
003 DE-He213
005 20210713145615.0
006 m d
007 cr nn 008maaau
008 211111s2021 si s 0 eng d
020 $a 9789813361041 $q (electronic bk.)
020 $a 9789813361034 $q (paper)
024 7 $a 10.1007/978-981-33-6104-1 $2 doi
035 $a 978-981-33-6104-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A43 $b A675 2021
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 005.13 $2 23
090 $a QA76.9.A43 $b A652 2021
245 0 0 $a Applications of flower pollination algorithm and its variants $h [electronic resource] / $c edited by Nilanjan Dey.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a xi, 239 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer tracts in nature-inspired computing, $x 2524-552X
505 0 $a Flower Pollination Algorithm: Basic Concepts, Variants and Applications -- Optimization of Non-rigid Demons Registration using Flower Pollination Algorithm -- Adaptive Neighbour Heuristics Flower Pollination Algorithm Strategy for Sequence Test Generation -- Implementation of flower pollination algorithm to the design optimization of planar antennas -- Flower Pollination Algorithm for Slope Stability Analysis -- Optimum Sizing of Truss Structures Using A Hybrid Flower Pollination -- Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm -- Multi-Objective Flower Pollination Algorithm and its Variants to Find Optimal Golomb Rulers for WDM System -- Applications of Flower Pollination algorithm in Wireless Sensor Networking and Image processing: A detailed study -- Flower pollination algorithm tuned PID controller for multi-source interconnected multi area power system.
520 $a This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.
650 0 $a Computer algorithms. $3 523872
650 0 $a Swarm intelligence. $3 577800
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Algorithms. $3 536374
650 2 4 $a Optimization. $3 891104
650 2 4 $a Mathematics of Computing. $3 891213
700 1 $a Dey, Nilanjan. $3 2200043
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Springer tracts in nature-inspired computing. $3 3443947
856 4 0 $u https://doi.org/10.1007/978-981-33-6104-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)