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The Resource Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource)
Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource)
Resource Information
The item Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Manitoba Libraries.This item is available to borrow from all library branches.
Resource Information
The item Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Manitoba Libraries.
This item is available to borrow from all library branches.
- Summary
- This book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application
- Language
-
- eng
- eng
- Edition
- 1st ed. 2014.
- Extent
- 1 online resource (XXIV, 510 p. 162 illus.)
- Note
- Bibliographic Level Mode of Issuance: Monograph
- Contents
-
- Novel swarm-based search methods
- Novel optimization algorithm
- Particle swarm optimization
- Ant colony optimization for travelling salesman problem
- Artificial bee colony algorithms
- Artificial immune system
- Evolutionary algorithms
- Neural networks and fuzzy methods
- Hybrid methods
- Multi-objective optimization
- Multi-agent systems
- Evolutionary clustering algorithms
- Classification methods
- GPU-based methods
- Scheduling and path planning
- Wireless sensor networks
- Power system optimization
- Swarm intelligence in image and video processing
- Applications of swarm intelligence to management problems
- Swarm intelligence for real-world application
- Isbn
- 9783319118574
- Label
- Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I
- Title
- Advances in Swarm Intelligence
- Title remainder
- 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I
- Statement of responsibility
- edited by Ying Tan, Yuhui Shi, Carlos Coello Coello
- Language
-
- eng
- eng
- Summary
- This book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application
- Dewey number
- 005.1
- http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsedt
-
- 7q7Qi6xONNo
- C9U_DpGMAWI
- moWeceBpKns
- Image bit depth
- 0
- Language note
- English
- LC call number
- QA76.9.A43
- Literary form
- non fiction
- http://library.link/vocab/relatedWorkOrContributorName
-
- Tan, Ying.
- Shi, Yuhui.
- Coello Coello, Carlos.
- Series statement
- Theoretical Computer Science and General Issues
- Series volume
- 8794
- http://library.link/vocab/subjectName
-
- Computer software
- Electronic data processing
- Computational complexity
- Data mining
- Artificial intelligence
- Algorithm Analysis and Problem Complexity
- Numeric Computing
- Discrete Mathematics in Computer Science
- Data Mining and Knowledge Discovery
- Artificial Intelligence
- Label
- Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource)
- Note
- Bibliographic Level Mode of Issuance: Monograph
- Antecedent source
- mixed
- Carrier category
- online resource
- Carrier category code
- cr
- Color
- not applicable
- Content category
- text
- Content type code
- txt
- Contents
- Novel swarm-based search methods -- Novel optimization algorithm -- Particle swarm optimization -- Ant colony optimization for travelling salesman problem -- Artificial bee colony algorithms -- Artificial immune system -- Evolutionary algorithms -- Neural networks and fuzzy methods -- Hybrid methods -- Multi-objective optimization -- Multi-agent systems -- Evolutionary clustering algorithms -- Classification methods -- GPU-based methods -- Scheduling and path planning -- Wireless sensor networks -- Power system optimization -- Swarm intelligence in image and video processing -- Applications of swarm intelligence to management problems -- Swarm intelligence for real-world application
- Dimensions
- unknown
- Edition
- 1st ed. 2014.
- Extent
- 1 online resource (XXIV, 510 p. 162 illus.)
- File format
- multiple file formats
- Form of item
- online
- Isbn
- 9783319118574
- Level of compression
- uncompressed
- Media category
- computer
- Media type code
- c
- Other control number
- 10.1007/978-3-319-11857-4
- Quality assurance targets
- absent
- Reformatting quality
- access
- Specific material designation
- remote
- System control number
-
- (CKB)3710000000228652
- (SSID)ssj0001354029
- (PQKBManifestationID)11773475
- (PQKBTitleCode)TC0001354029
- (PQKBWorkID)11317611
- (PQKB)10337096
- (DE-He213)978-3-319-11857-4
- (EXLCZ)993710000000228652
- Label
- Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource)
- Note
- Bibliographic Level Mode of Issuance: Monograph
- Antecedent source
- mixed
- Carrier category
- online resource
- Carrier category code
- cr
- Color
- not applicable
- Content category
- text
- Content type code
- txt
- Contents
- Novel swarm-based search methods -- Novel optimization algorithm -- Particle swarm optimization -- Ant colony optimization for travelling salesman problem -- Artificial bee colony algorithms -- Artificial immune system -- Evolutionary algorithms -- Neural networks and fuzzy methods -- Hybrid methods -- Multi-objective optimization -- Multi-agent systems -- Evolutionary clustering algorithms -- Classification methods -- GPU-based methods -- Scheduling and path planning -- Wireless sensor networks -- Power system optimization -- Swarm intelligence in image and video processing -- Applications of swarm intelligence to management problems -- Swarm intelligence for real-world application
- Dimensions
- unknown
- Edition
- 1st ed. 2014.
- Extent
- 1 online resource (XXIV, 510 p. 162 illus.)
- File format
- multiple file formats
- Form of item
- online
- Isbn
- 9783319118574
- Level of compression
- uncompressed
- Media category
- computer
- Media type code
- c
- Other control number
- 10.1007/978-3-319-11857-4
- Quality assurance targets
- absent
- Reformatting quality
- access
- Specific material designation
- remote
- System control number
-
- (CKB)3710000000228652
- (SSID)ssj0001354029
- (PQKBManifestationID)11773475
- (PQKBTitleCode)TC0001354029
- (PQKBWorkID)11317611
- (PQKB)10337096
- (DE-He213)978-3-319-11857-4
- (EXLCZ)993710000000228652
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.lib.umanitoba.ca/portal/Advances-in-Swarm-Intelligence--5th/Le9Kf5GyiFk/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.lib.umanitoba.ca/portal/Advances-in-Swarm-Intelligence--5th/Le9Kf5GyiFk/">Advances in Swarm Intelligence : 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I, edited by Ying Tan, Yuhui Shi, Carlos Coello Coello, (electronic resource)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.lib.umanitoba.ca/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.lib.umanitoba.ca/">University of Manitoba Libraries</a></span></span></span></span></div>
