Artificial Intelligence and Computational Intelligence, Part by Fu Lee Wang, Hepu Deng, Jingsheng Lei
By Fu Lee Wang, Hepu Deng, Jingsheng Lei
The 2010 foreign convention on synthetic Intelligence and Computational Intelligence (AICI 2010) was once held October 23–24, 2010 in Sanya, China. The AICI 2010 obtained 1,216 submissions from 20 international locations and areas. After rigorous reports, one hundred and five top of the range papers have been chosen for booklet within the AICI 2010 court cases. The recognition expense used to be 8%. the purpose of AICI 2010 used to be to compile researchers operating in lots of various parts of man-made intelligence and computational intelligence to foster the trade of latest rules and advertise foreign collaborations. as well as the massive variety of submitted papers and invited classes, there have been a number of across the world recognized keynote audio system. On behalf of the Organizing Committee, we thank Hainan Province Institute of computing device and Qiongzhou college for its sponsorship and logistics help. We additionally thank the individuals of the Organizing Committee and this system Committee for his or her labor. we're very thankful to the keynote audio system, invited consultation organizers, consultation chairs, reviewers, and scholar helpers. final yet now not least, we thank the entire authors and members for his or her nice contributions that made this convention attainable.
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Extra resources for Artificial Intelligence and Computational Intelligence, Part I
This program is carried out in two steps. Step one: optimization algorithm more suitable for the overall search is adopted to facilitate the search in the overall design space and initially determine the optimal design point. This paper applies adaptive simulated annealing algorithm (ASA) as the first step of the optimization algorithm. Step two: Adopting the numerical optimization techniques, one shortcoming of the adaptive simulated annealing algorithm (ASA) is lack of accuracy. In order to solve the problem, a numerical optimization algorithm is chosen to be combined with the global search optimization algorithm.
L. Wang et al. ): AICI 2010, Part I, LNAI 6319, pp. 18–24, 2010. © Springer-Verlag Berlin Heidelberg 2010 Formalizing Ontology-Based Hierarchical Modeling Process of Physical World 19 2 Introducing Ontology in the KRA Model The KRA model represents the world from four levels: Perception, Structure, Language and Theory (see  for details). In the G-KRA model, the abstraction model can be automatically constructed by using the abstraction objects database and the abstraction mapping defined manually.
Since every round may cost resource, so we cannot make the election round and round, never stop. So we want to know if we want have the leader only in two rounds, then which way is better. To solve the problem, we may model the two ways as below: u1 uj s1 s1 uj u1 si si 1/ 42 u1' (a) The Model of first way 1/ 4 2 u j' 1/ 4 2 1/ 4 2 s1 ' si' (b) The Model of second way Fig. 4. ,si means getting a leader successfully. Since the vote is random, the probability of arriving at u or s is 1/44, the same way for u1’,…,uj’, s1’…si’ with 1/42.