Opposition based computing - A survey

Fares S. Al-Qunaieer; Hamid R. Tizhoosh; Shahryar Rahnamayan

doi:10.1109/IJCNN.2010.5596906

Opposition based computing - A survey

Fares S. Al-Qunaieer, Hamid R. Tizhoosh, Shahryar Rahnamayan

Artificial Intelligence and Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In algorithms design, one of the important aspects is to consider efficiency. Many algorithm design paradigms are existed and used in order to enhance algorithms' efficiency. Opposition-based Learning (OBL) paradigm was recently introduced as a new way of thinking during the design of algorithms. The concepts of opposition have already been used and applied in several applications. These applications are from different fields, such as optimization algorithms, learning algorithms and fuzzy logic. The reported results confirm that OBL paradigm was promising to accelerate or to enhance accuracy of soft computing algorithms. In this paper, a survey of existing applications of opposition-based computing is presented.

Original language	English (US)
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781424469178
DOIs	https://doi.org/10.1109/IJCNN.2010.5596906
State	Published - 2010
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain Duration: Jul 18 2010 → Jul 23 2010

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks

Conference

Conference	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
Country/Territory	Spain
City	Barcelona
Period	7/18/10 → 7/23/10

ASJC Scopus subject areas

Software
Artificial Intelligence

Access to Document

10.1109/IJCNN.2010.5596906

Cite this

Al-Qunaieer, F. S., Tizhoosh, H. R., & Rahnamayan, S. (2010). Opposition based computing - A survey. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 Article 5596906 (Proceedings of the International Joint Conference on Neural Networks). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2010.5596906

Opposition based computing - A survey. / Al-Qunaieer, Fares S.; Tizhoosh, Hamid R.; Rahnamayan, Shahryar.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010. Institute of Electrical and Electronics Engineers Inc., 2010. 5596906 (Proceedings of the International Joint Conference on Neural Networks).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Al-Qunaieer, FS, Tizhoosh, HR & Rahnamayan, S 2010, Opposition based computing - A survey. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010., 5596906, Proceedings of the International Joint Conference on Neural Networks, Institute of Electrical and Electronics Engineers Inc., 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 7/18/10. https://doi.org/10.1109/IJCNN.2010.5596906

Al-Qunaieer FS, Tizhoosh HR, Rahnamayan S. Opposition based computing - A survey. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010. Institute of Electrical and Electronics Engineers Inc. 2010. 5596906. (Proceedings of the International Joint Conference on Neural Networks). doi: 10.1109/IJCNN.2010.5596906

Al-Qunaieer, Fares S. ; Tizhoosh, Hamid R. ; Rahnamayan, Shahryar. / Opposition based computing - A survey. 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010. Institute of Electrical and Electronics Engineers Inc., 2010. (Proceedings of the International Joint Conference on Neural Networks).

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abstract = "In algorithms design, one of the important aspects is to consider efficiency. Many algorithm design paradigms are existed and used in order to enhance algorithms' efficiency. Opposition-based Learning (OBL) paradigm was recently introduced as a new way of thinking during the design of algorithms. The concepts of opposition have already been used and applied in several applications. These applications are from different fields, such as optimization algorithms, learning algorithms and fuzzy logic. The reported results confirm that OBL paradigm was promising to accelerate or to enhance accuracy of soft computing algorithms. In this paper, a survey of existing applications of opposition-based computing is presented.",

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AB - In algorithms design, one of the important aspects is to consider efficiency. Many algorithm design paradigms are existed and used in order to enhance algorithms' efficiency. Opposition-based Learning (OBL) paradigm was recently introduced as a new way of thinking during the design of algorithms. The concepts of opposition have already been used and applied in several applications. These applications are from different fields, such as optimization algorithms, learning algorithms and fuzzy logic. The reported results confirm that OBL paradigm was promising to accelerate or to enhance accuracy of soft computing algorithms. In this paper, a survey of existing applications of opposition-based computing is presented.

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Opposition based computing - A survey

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