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Intelligent computing budget allocation 1

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On-road planning 1

Ordinal optimization 1

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evolutionary decision making 1

evolutionary robotics 1

gene familiy-candidate disease gene cloning 1

gene function study 1

gene mapping and cloning 1

genetic algorithms for ordering problem 1

genetic disease 1

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Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions Regular Article

Cai-hong Li, Chun Fang, Feng-ying Wang, Bin Xia, Yong Song,lich@sdut.edu.cn

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 11,   Pages 1530-1542 doi: 10.1631/FITEE.1800616

Abstract: We propose a algorithm to plan a complete coverage trajectory for a mobile robot to accomplish specific types of missions based on the Arnold dynamical system. First, we construct a chaotic mobile robot by combining the variable of the Arnold equation and the kinematic equation of the robot. Second, we construct the s including the initial points with a relatively high coverage rate of the constructed mobile robot. Then the trajectory is contracted to the current position of the robot based on the designed strategy, to form a continuous complete coverage trajectory to execute the specific types of missions. Compared with the traditional method, the designed algorithm requires no obstacle avoidance to the boundary of the given workplace, possesses a high coverage rate, and keeps the chaotic characteristics of the produced coverage trajectory relatively unchanged, which enables the robot to accomplish special missions with features of completeness, randomness, or unpredictability.

Keywords： 混沌机器人；Arnold动力学系统；压缩变换；全覆盖遍历路径；候选集    

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Evolutionary Decision Making Based on Candidates Ranking

Li Jianqi,Chen Huowang,Wang Bingshan

Strategic Study of CAE 2001, Volume 3, Issue 1,   Pages 62-70

Abstract:

Since the exact Expected Utility Functions (EUF) are not available in many circumstances, it is hard to make decision in environment characterized by incomplete information and uncertain decision results. Being aware of the defects of traditional decision analysis techniques, a new decision making method named Evolutionary Decision Making Based on Candidates Ranking is proposed. By selecting a set of indexes relevant to the expected utility of the candidates, the construction of decision rules can be reduced to finding the quantitative relationship between them. If all of the candidates are classified according to the indexes relevant to their expected utility, then Evolutionary Algorithms can be used to search for the expected utility ranking of the whole set of candidate classes, thus the optimal decision can be made based on the ranking. Some special considerations for Genetic Algorithms for ordering problem are also highlighted. The new method enjoys the advantages of weak dependence on expert knowledge, robustness in environment with random noise, no dependence on explicit EUF, effectively treating non-numerical, non-quantificational indexes and conflicts or correlation among indexes. The effectiveness of the proposed method is validated by its successful application in the controller design of certain simulated robot.

Keywords： evolutionary decision making     evolutionary robotics     genetic algorithms for ordering problem    

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Study on Family Collection, Gene Mapping, Gene Identification and Gene Function of Human Genetic Diseases

Xia Jiahui

Strategic Study of CAE 2000, Volume 2, Issue 11,   Pages 1-11

Abstract:

In this paper, the study on family collection, gene mapping, gene identification and gene function of human genetic diseases carried out in the National Laboratory of Medical Genetics of China, were described in detail. Using G-banding technique a marker chromosome t (1; 3) (q44; p11) associated with nasopharyngeal cancer was found in 1975 at first, and human TDF gene was mapped to chromosome Yp11. 32 in 1981. Since 1991, 590 families with 345 kind of genetic diseases were collected. In 1998, GJB3, a human genetic neurological deafness gene, was identified using a novel strategy of “Gene Family-Candidate Disease Gene Cloning”，and the paper was published in Nature Genetics (20： 370). In 1999, by linkage analysis and Genome Wide Scanning, a locus responsible for disseminated superficial actinic porokeratosis (DSAP) was identified at Chromosome 12q23. 2 - 24. 1; and at the same year a novel protein trafficking gene was also cloned from gene function study.

Keywords： genetic disease     gene mapping and cloning     gene familiy-candidate disease gene cloning     genome wide scan     gene function study    

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Intelligent computing budget allocation for on-road trajectory planning based on candidate curves Project supported by the National Natural Science Foundation of China (No. 61273039) Article

Xiao-xin FU,Yong-heng JIANG,De-xian HUANG,Jing-chun WANG,Kai-sheng HUANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 6,   Pages 553-565 doi: 10.1631/FITEE.1500269

Abstract: In this paper, on-road trajectory planning is solved by introducing intelligent computing budget allocation (ICBA) into a candidate-curve-based planning algorithm, namely, ordinal-optimization-based differential evolution (OODE). The proposed algorithm is named IOODE with ‘I’ representing ICBA. OODE plans the trajectory in two parts: trajectory curve and acceleration profile. The best trajectory curve is picked from a set of candidate curves, where each curve is evaluated by solving a subproblem with the differential evolution (DE) algorithm. The more iterations DE performs, the more accurate the evaluation will become. Thus, we intelligently allocate the iterations to individual curves so as to reduce the total number of iterations performed. Meanwhile, the selected best curve is ensured to be one of the truly top curves with a high enough probability. Simulation results show that IOODE is 20% faster than OODE while maintaining the same performance in terms of solution quality. The computing budget allocation framework presented in this paper can also be used to enhance the efficiency of other candidate-curve-based planning methods.

Keywords： Intelligent computing budget allocation     Trajectory planning     On-road planning     Intelligent vehicles     Ordinal optimization    

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Title Author Date Type Operation

Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions

Cai-hong Li, Chun Fang, Feng-ying Wang, Bin Xia, Yong Song,lich@sdut.edu.cn

Journal Article

Evolutionary Decision Making Based on Candidates Ranking

Li Jianqi,Chen Huowang,Wang Bingshan

Journal Article

Study on Family Collection, Gene Mapping, Gene Identification and Gene Function of Human Genetic Diseases

Xia Jiahui

Journal Article

Intelligent computing budget allocation for on-road trajectory planning based on candidate curves Project supported by the National Natural Science Foundation of China (No. 61273039)

Xiao-xin FU,Yong-heng JIANG,De-xian HUANG,Jing-chun WANG,Kai-sheng HUANG

Journal Article