By Mohammad Taheri, Elham Chitsaz, Seraj D. Katebi, Mansoor Z. Jahromi (auth.), Hamid Sarbazi-Azad, Behrooz Parhami, Seyed-Ghassem Miremadi, Shaahin Hessabi (eds.)
This e-book constitutes the revised chosen papers of the thirteenth overseas CSI laptop convention, CSICC 2008 hung on Kish Island, Iran, in March 2008. The eighty four standard papers offered including sixty eight poster displays have been conscientiously reviewed and chosen from a complete of 426 submissions.
The papers are prepared in topical sections on learning/soft computing, set of rules conception, SoC and NoC, wireless/sensor networks, video processing and comparable issues, processor structure, AI/robotics/control, scientific snapshot processing, p2p/cluster/grid structures, cellular advert hoc networks, net, sign processing/speech processing, misc, safety, snapshot processing functions in addition to VLSI.
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Additional info for Advances in Computer Science and Engineering: 13th International CSI Computer Conference, CSICC 2008 Kish Island, Iran, March 9-11, 2008 Revised Selected Papers
The structure of a Bayesian network encodes variable independencies. Since H. Sarbazi-Azad et al. ): CSICC 2008, CCIS 6, pp. 25–32, 2008. R. M. B. Menhaj the number of possible structures is extremely huge, structure learning often has high computational complexity. Finding the optimal structure of a BN from data has been shown to be NP-hard . Thus, heuristic and approximate learning algorithms are the realistic solution. Therefore, greedy score-based algorithms  have been developed to provide more efficient structure learning at an accuracy tradeoff.
It sorts the ants offspring of AS and then the trails are updated by only the first ω 1 ants according to (4). , Where Δτ , and Δτ , . , ∑ . , . , (4) . Stüzle and Hoos introduced MAX-MIN Ant System (MMAS) . In MMAS trails τ , so it help ants not to converge to local optiare limited to an interval τ mum. Further, in MMAS, only the best ant (iteration-best or global-best) is allowed to deposit pheromone. Sometimes, for more exploration an additional mechanism called Pheromone Trail Smoothing is applied to MMAS.
Automatic acquisition of hyponyms from large text corpora. In: 4th International Conference on Computational Linguistics, pp. 539–545 (1992) 6. : Finding parts in very large corpora. In: 37th Annual Meeting of the ACL, pp. 57–64 (1999) 7. : Text mining for causal relations. In: Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference, pp. R. M. B. ir Abstract. This paper describes the theory and implementation of Bayesian networks in the context of data classification.
Advances in Computer Science and Engineering: 13th International CSI Computer Conference, CSICC 2008 Kish Island, Iran, March 9-11, 2008 Revised Selected Papers by Mohammad Taheri, Elham Chitsaz, Seraj D. Katebi, Mansoor Z. Jahromi (auth.), Hamid Sarbazi-Azad, Behrooz Parhami, Seyed-Ghassem Miremadi, Shaahin Hessabi (eds.)