By Zhi-xiang Yin, Jian-zhong Cui, Jin Yang (auth.), De-Shuang Huang, Laurent Heutte, Marco Loog (eds.)
The foreign convention on clever Computing (ICIC) used to be shaped to supply an annual discussion board devoted to the rising and hard issues in man made intelligence, computing device studying, bioinformatics, and computational biology, and so forth. It goals to deliver - gether researchers and practitioners from either academia and to proportion rules, difficulties and ideas relating to the multifaceted features of clever computing. ICIC 2007, held in Qingdao, China, August 21–24, 2007, constituted the 3rd - ternational convention on clever Computing. It outfitted upon the good fortune of ICIC 2006 and ICIC 2005 held in Kunming and Hefei, China, 2006 and 2005, respectively. This 12 months, the convention centred commonly at the theories and methodologies in addition to the rising purposes of clever computing. Its goal used to be to unify the image of up to date clever computing strategies as an critical idea that highlights the traits in complicated computational intelligence and bridges theoretical examine with purposes. hence, the subject matter for this convention used to be “Advanced clever Computing know-how and Applications”. Papers targeting this topic have been solicited, addressing theories, methodologies, and purposes in technological know-how and technology.
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Extra info for Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues: Third International Conference on Intelligent Computing, ICIC 2007 Qingdao, China, August 21-24, 2007 Proceedings
Progress Toward Demonstration of A Surface Based DNA Computation: A One Word Approach to Solve A Model Satisfiability Problem. Biosystems, (1999), 52, 25-33 12. : Molecular Computation by DNA Hairpin Formation. Science, (2000), 288, 1223-1226 13. : Solution of A 20-Variable 3-SAT Problem on A DNA Computer. Science, (2002), 296, 499-502 14. : The General Form of 0-1 Programming Problem Based on DNA Computing. Biosystems, (2003), 70, 73-78 15. : DNA Solution of Integer Linear Programming. Applied Mathematics and Computation, (2005) 16.
Shin, S. Y. , Lee, I. , Kim, D. M. , Zhang, B. : Multiobjective Evolutionary Optimization of DNA Sequences for Reliable DNA Computing. IEEE Transactions on Evolutionary Computation, 9(2) (2005) 143-158 3. Faulhammer, D. , Cukras, A. R. , Lipton, R. J. , Landweber, L. : Molecular Computation: RNA Solutions to Chess Problems. , 97 (2000)1385-1389 4. Tuplan, D. : Stochastic Local Search Algorithms for DNA Word Design, Proceedings of the 8th International. Workshop on DNA Based Compuing, (2002) 229-241 5.
However, many problems still exist and are being addressed by researchers concentrating on DNA sequence generation systems. In order to solve the problems in combinatorial optimization problems using DNA computing, a DNA sequence generation system using an evolution model is proposed. The system model is composed of a pre-processing and post-processing stage for generating DNA sequences. The pre-processing stage applies an evolutionary DNA coding model to Adleman’s DNA computing algorithm  to generate DNA sequences suitable for biological experiments.
Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues: Third International Conference on Intelligent Computing, ICIC 2007 Qingdao, China, August 21-24, 2007 Proceedings by Zhi-xiang Yin, Jian-zhong Cui, Jin Yang (auth.), De-Shuang Huang, Laurent Heutte, Marco Loog (eds.)