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Interesting Rules Mining with Deductive Method
Wenxiang Dou,Jinglu Hu,Gengfeng Wu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, we propose a novel rule deductive method to mine the real demanded association rules for any given user. This method does not like the most existing methods that mine frequent itemsets starting from candidate two-itemsets to candidate (n-1)-itemsets with inductive method and produce huge rough rules on these frequent itemsets. On the contrary, it avoids producing huge amounts of frequent itemsets contained by their upper long frequent itemsets and can interact with users by making them pick up their interested items to deduce the final interesting association rules. Moreover, it can do dynamic response to users in any time when users want to check whether their interested frequent itemsets have been founded. Its several dynamic response strategies have been proposed. These dynamic response algorithms can find most long frequent itemsets in initial time. Therefore, users can find their interested rules in short time with high probability. So, our method also can be used applied in online data mining.
An Improvement of Quasi-ARX Predictor to Control of Nonlinear Systems Using Nonlinear PCA network
Lan Wang,Jinglu Hu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, a nonlinear principal component analysis(NPCA) is introduced to improve the quasi-ARX modeling. One part of the quasi-ARX model is an or dinary neurofuzzy network to parameterize the coefficients which faces to a problem of high dimension. NPCA is used for this part to deal with the problem. The processes of modeling, parameter estimating and control are given detailedly. Some simulations of systems controlling are provided to illustrate the effectiveness of the proposed modeling approach.
An Improved Backtracking Method for ED As Based Protein Folding
Benhui CHEN,Long LI,Jinglu HU 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Many Evolutionary Algorithm(EA) based methods have been proposed to solve protein structure prediction(PSP) problem in HP-lattice model. One of common difficulties of those methods is the existence of invalid individuals produced by geometrical constraints in the conformation of proten(i.e. self-avoidance in the chain). A backtracking method is often used to repair the invalid individuals of genetic search in those methods. However, there is a disadvantage in basic back tracking method, the repairing computational costis very heavy for long sequence instances. This paper proposes an improved back tracking-based repairing method for long sequence protein folding. A detection procedure is added in back tracking method to a void entering invalid closed are as when selecting directions for the residues. Experi-mental results show that the proposed method can significantly reduce the number of back tracking searching operations and the computational cost for the long protein sequences.
Yu CHENG,Yongjie JIN,Jinglu HU 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper presents an adaptive epsilon non-dominated sorting method for multi-objective evolution aryop-timization which has the ability to preserve both the efficiency and diversity. In NSGA-II, a fast non-dominated sorting mechanism is applied to sort solutions in an efficient way. However, it may suffer from deterioration and diversity in population is not as great as expected. To solve this problem, the concept of epsilon-dominance is applied for updating solutions in non-dominate sorted layers according to adaptive epsilon value, and the novel update strategy could preventde terioration and keep diversity well. Areal-world city map with 410 nodes and 1334 arcsisused in experiment, and the result shows that the proposed algorithm(AENSGA) performs better than NSGA-IIinmulti-objective shortest path problem.