Artificial bee colony algorithm to minimal time cost reduction

Journal of Computational Information Systems

Volumn 9, Issue 21, 2013, Pages 8725-8734

  Cai, Jinling ^a   Ding, Haijun ^a   Zhu, William ^a,b   Zhu, Xiaozhong ^a  

^a HOHAI UNIVERSITY   (China)

^b MINNAN NORMAL UNIVERSITY   (China)

Author keywords

Artificial bee colony algorithm; Attribute reduction; Testing time cost; Waiting cost

Indexed keywords

ARTIFICIAL BEE COLONY ALGORITHMS; ATTRIBUTE REDUCTION; COST-SENSITIVE LEARNING; HEURISTIC INFORMATION; POSITIVE REGION; REDUCTION PROBLEM; SEARCH PROCESS; TESTING TIME;

COST REDUCTION; ROUGH SET THEORY;

EVOLUTIONARY ALGORITHMS;

EID: 84889601207     PISSN: 15539105     EISSN: None     Source Type: Journal    
DOI: 10.12733/jcis7479     Document Type: Article

References (26)

1. L. X. Jiang, C. Q. Li, An empirical study on attribute selection measures in decision tree learning, Journal of Computational Information Systems, 6 (1), 2010, 105-112.
2. Z. L. Xu, F. Min, W. Zhu, Cost-sensitive decision trees with post-pruning and competition for numeric data, to appear in Journal of Computational Information Systems, 9 (20), 2013.
3. Z. H. Zhou, X. Y. Liu, Training cost-sensitive neural networks with methods addressing the class imbalance problem, Knowledge and Data Engineering, IEEE Transactions on, 18 (1), 2006, 63-77.
4. F. Min, Q. H. Liu, A hierarchical model for test-cost-sensitive decision systems, Information Sciences, 179 (2009), 2442-2452.
5. Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences, 11 (1982), 341-356.
6. F. Min, H. P. He, Y. H. Qian, W. Zhu, Test-cost-sensitive attribute reduction, Information Sciences, 181 (2011), 4928-4942.
7. F. Min, Q. H. Hu, W. Zhu, Feature selection with test cost constraint, International Journal of Approximate Reasoning (doi: 10.1016/j.ijar.2013.04.003), 2013.
8. G. Y. Pan, F. Min, W. Zhu, A genetic algorithm to the minimal test cost reduct problem, in: Proceedings of IEEE International Conference on Granular Computing, 2011, 539-544.
9. Z. L. Xu, F. Min, J. B. Liu, W. Zhu, Ant colony optimization to minimal test cost reduction, in: Proceedings of the 2011 IEEE International Conference on Granular Computing, 2012, 688-693.
10. V. S. Sheng, C. X. Ling, Feature value acquisition in testing: a sequential batch test algorithm, in: Proceedings of the 23rd International Conference on Machine Learning, ACM, 2006, 809-816.
11. D. A. Cromwell, Waiting time information services: an evaluation of how well clearance time statistics can forecast a patient's wait, Social Science and Medicine, 59 (9), 2004, 1937-1948.
12. D. A. Cromwell, D. A. Griffiths, I. A. Kreis, et al., Surgery dot. com: the quality of information disseminated by web-based waiting time information services, Medical Journal of Australia, 177 (5), 2002, 253-255.
13. C. B. Schoonhoven, K. M. Eisenhardt, K. Lyman, Speeding products to market: waiting time to first product introduction in new firms, Administrative Science Quarterly, 1990, 177-207.
14. D. Karaboga, An idea based on honey bee swarm for numerical optimization, Techn. Rep. TR06, Erciyes Univ. Press, Erciyes, 2005.
15. D. Karaboga, B. Basturk, Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems, Foundations of Fuzzy Logic and Soft Computing, 2007, 789-798.
16. F. Min, W. Zhu, Attribute reduction of data with error ranges and test costs, Information Sciences, 211 (2012), 48-67.
17. Z. Pawlak, Rough sets and intelligent data analysis, Information Sciences, 147 (12), 2002, 1-12.
18. D. Karaboga, B. Akay, A comparative study of artificial bee colony algorithm, Applied Mathematics and Computation, 214 (1), 2009, 108-132.
19. D. Karaboga, B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of Global Optimization, 39(3), 2007, 459-471.
20. F. Min, W. Zhu, H. Zhao, G. Y. Pan, J. B. Liu, Z. L. Xu, Coser: cost-senstive rough sets, http://grc.fjzs.edu.cn/~fmin/coser/, 2012.
21. Y. Y. Yao, A partition model of granular computing, LNCS, 3100 (2004), 232-253.
22. Z. Pawlak, Rough set theory and its applications to data analysis, Cybernetics and Systems, 29 (7), 1998, 661-688.
23. Y. Y. Yao, Y. Zhao, Attribute reduction in decision-theoretic rough set models, Information Sciences, 178 (17), 2008, 3356-3373.
24. W. Zhu, Relationship among basic concepts in covering-based rough sets, Information Sciences, 179 (14), 2009, 2478-2486.
25. W. Zhu, F. Wang, Reduction and axiomization of covering generalized rough sets, Information Sciences, 152 (1), 2003, 217-230.
26. C. L. Blake, C. J. Merz, UCI repository of machine learning databases, http://www.ics.uci.edu/mlearn/mlrepository.html, 1998.