摘要：
To overcome the deficiencies of weak local search ability in genetic algorithms (GA) and slow global convergence speed in ant colony optimization (ACO) algorithm in solving complex optimization problems, the chaotic optimization method, multi-population collaborative strategy and adaptive control parameters are introduced into the GA and ACO algorithm to propose a genetic and ant colony adaptive collaborative optimization (MGACACO) algorithm for solving complex optimization problems. The proposed MGACACO algorithm makes use of the exploration capability of GA and stochastic capability of ACO algorithm. In the proposed MGACACO algorithm, the multi-population strategy is used to realize the information exchange and cooperation among the various populations. The chaotic optimization method is used to overcome long search time, avoid falling into the local extremum and improve the search accuracy. The adaptive control parameters is used to make relatively uniform pheromone distribution, effectively solve the contradiction between expanding search and finding optimal solution. The collaborative strategy is used to dynamically balance the global ability and local search ability, and improve the convergence speed. Finally, various scale TSP are selected to verify the effectiveness of the proposed MGACACO algorithm. The experiment results show that the proposed MGACACO algorithm can avoid falling into the local extremum, and takes on better search precision and faster convergence speed.
作者机构：
[阳小华; 闫仕宇; 刘朝晖] School of Computer Science and Technology, University of South China, Hengyang, 421001, China;[刘华; 于涛; 刘朝晖; 谢金森; 李萌; 阳小华; 闫仕宇] CNNC Key Laboratory on High Trusted Computing, Hengyang, 421001, China
通讯机构：
School of Computer Science and Technology, University of South China, Hengyang, China
期刊：
Revista de la Facultad de Ingeniería Universidad Central de Venezuela,2016年31(5):89-99 ISSN：0798-4065
作者机构：
[Zheng, Jianguo; Li, Kang] School of Management, Donghua University, Shanghai, 200051, China;[Wu, Daqing] School of Computer Science and Technology, University of South China, Hengyang, 421001, China
摘要：
In order to solve cold logistics network problem under uncertain demand environment, this paper proposes a novel location inventory routing model to optimize costs in cold logistics. The goal of the proposed model is to determine the inventory strategy, numbers of location facilities and vehicle routing decisions. A new discrete particle swarm optimization (DPSO) is introduced to solve this integrated model. Its performance is tested over a real case for the proposed problems. Results indicate that it is considerably efficient and effective to solve the problem.
期刊：
Journal of Communications,2016年11(12):1088-1094 ISSN：1796-2021
通讯作者：
Ding, Lin(linding1981@163.com)
作者机构：
[Tan, Minsheng; Ding, Lin] School of Computer Science and Technology, University of South China, Hengyang, 421001, China;[Ding, Lin] Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, V6T 1Z4, Canada
通讯机构：
School of Computer Science and Technology, University of South China, Hengyang, China
作者机构：
[刘朝晖; 刘曜; 阳小华] School of Computer Science and Technology, University of South China, Hengyang;Hunan;421001, China;[陈智; 吴志强] Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chendu;610041, China
通讯机构：
[Yang, Xiao-Hua] U;Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Peoples R China.
会议名称：
第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)
会议时间：
2016-12-02
会议地点：
昆明
会议主办单位：
Kunming Univ Sci & Technol
会议论文集名称：
第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)论文集
关键词：
Feature selection;Information gain;Relative document frequency distribution;Low-frequency characteristic
摘要：
Feature selection algorithm plays an important role in text categorization. Considering some drawbacks proposed from traditional and recently improved information gain (IG) approach, an improved IG feature selection method based on relative document frequency distribution is proposed, which combines reducing the impact of unbalanced data sets and low-frequency characteristics, the frequency distribution of features within category and the relative frequency document distribution of features among different categories. The experimental results of NLPCC-ICCPOL 2016 stance detection in Chinese microblogs show that the performance of the improved method is better than traditional IG approach and another improved method in feature selection.
作者机构：
[刘立; 罗扬; 汪琳霞; 刘芳菊; 李悛] School of Computer Science and Technology, University of South China, Hengyang;Hunan;421001, China;[刘立; 罗扬; 汪琳霞; 刘芳菊; 李悛] Hunan;[刘立; 罗扬; 汪琳霞; 刘芳菊; 李悛] 421001, China
通讯机构：
[Luo, Y.] S;School of Computer Science and Technology, University of South China, Hengyang, Hunan, China
期刊：
Advances in modelling and analysis. A, general mathematical and computer tools,2016年53(1):145-159 ISSN：1258-5769
通讯作者：
Tang, Lixiang(Tanglx0731@126.com)
作者机构：
[Li, Haiyan; Ouyang, LiJun; Wu, Daqing] Computer Science and Technology Institute, University of South China, Hangyang, Hunan, China;[Tang, Lixiang] Department of Business Administration, Hunan University of Finance and Economics, Hunan, 410205, China;[Wu, Daqing] Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei, Anhui Province, 230039, China;[Wu, Daqing] Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence, Guangxi University for Nationalities, Nanning, 530006, China;[Wu, Daqing] Artificial Intelligence Key Laboratory of Sichuan Province (Sichuan University of Science and Engineering), Zigong, 643000, China
通讯机构：
[Tang, L.] D;Department of Business Administration, Hunan University of Finance and Economics, Hunan, China
关键词：
Diversity;Multi-objective optimization;Particle swarm optimizer;Two local best solutions
期刊：
International Journal of Distributed Sensor Networks,2015年2015(10):437678:1-437678:13 ISSN：1550-1477
通讯作者：
Liu, Fangju
作者机构：
[Liu, Fangju] Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Ma, Xingpo] Xinyang Normal Univ, Sch Comp & Informat Technol, Xinyang 464000, Henan, Peoples R China.;[Liang, Junbin] Guangxi Univ, Sch Comp & Elect Informat, Nanning 530004, Guangxi, Peoples R China.;[Lin, Mugang] Hengyang Normal Univ, Dept Comp Sci, Hengyang 421008, Hunan, Peoples R China.
通讯机构：
[Liu, Fangju] U;Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
摘要：
Verifiable top-k query processing in tiered sensor networks, which refers to verifying the authenticity and the completeness of top-k query results received by the network owner in tiered sensor networks, has received attention in very recent years. However, the existing solutions of this problem are only fit for static sensor network. In this paper, we try to solve the problem in a tiered mobile sensor network model, where not only static sensor nodes but also mobile sensor nodes existed. Based on the tiered mobile sensor network model, we propose a novel verifiable scheme named VTMSN for fine-grained top-k queries. The main idea of VTMSN is as follows: it maps each of the positions where sensor nodes are in a static state to a virtual node and then establishes relationships among data items of each virtual node with their score orders, which are encrypted along with the scores of the data items and the time epochs using the distinct symmetric keys kept by each sensor node and the network owner. Both theory analysis and simulation results show the efficiency and the security of VTMSN.
作者机构：
[刘朝晖; 刘华; 阳小华] School of Computer Science and Technology, University of South China, Hengyang;421001, China;[陈智; 吴志强] Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chendu;610041, China;[刘朝晖; 刘华; 阳小华] 421001, China
关键词：
STAMP模型;STPA方法;反应堆紧急停堆系统
摘要：
随着数字化技术及软件系统的广泛应用,很多事故是由于部件间异常的交互所引起,传统的分析方法已经力不从心,基于STAMP（Systems-Theoretic Accident Model and Processes）的安全性分析方法STPA（System Theoretic Process Analysis）,可以有效解决这一困难。首先介绍STPA方法及分析步骤,将该方法应用到反应堆紧急停堆子系统,得到了引起停堆失败的可能原因及设计中所应遵守的安全约束,这些约束有益于提高设计的安全性。
期刊：
Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015,2015年:1975-1979 ISSN：1948-9439
通讯作者：
Wu, Daqing
作者机构：
[Wu, Daqing] Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China.;[Liu, Li; Gong, XiangJian; Wu, Daqing] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Hunan, Peoples R China.;[Deng, Li; Wu, Daqing] DongHua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China.
通讯机构：
[Wu, Daqing] A;Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China.
会议名称：
27th Chinese Control and Decision Conference (CCDC)
会议时间：
MAY 23-25, 2015
会议地点：
Qingdao, PEOPLES R CHINA
会议主办单位：
[Wu, Daqing] Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China.^[Wu, Daqing;Liu, Li;Gong, XiangJian] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Hunan, Peoples R China.^[Wu, Daqing;Deng, Li] DongHua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China.
会议论文集名称：
Chinese Control and Decision Conference
关键词：
Multi-objective Optimization;Particle Swarm Optimizer;Neighborhood Best Particle;Dynamic Swamis;Economic Environmental Dispatch
摘要：
An efficient co-evolutionary multi-objective particle swarm optimizer named ECMPSO was proposed.ECMPSO uses dynamic multiple swarms to deal with multiple objectives,taking one objective is optimized b
期刊：
The Journal of Information and Computational Science,2015年12(1):121-131 ISSN：1548-7741
通讯作者：
Liu, Yang
作者机构：
[Yu, Jie; Xue, Yunlan; Liu, Yang; Xu, Lingyu] School of Computer Engineering and Science, Shanghai University, Shanghai, China;[Dong, Han] National Marine Data and Information Service, State Oceanic Administration, Tianjin, China;[Liu, Yang] School of Computer Science and Technology, University of South China, Hengyang, China
通讯机构：
School of Computer Engineering and Science, Shanghai University, Shanghai, China
关键词：
Impacted domain;Influence power;Information domain;Knowledge tree
作者：
Chunping, Ouyang;Yongbin, Liu;Shuqing, Zhang;Xiaohua, Yang
期刊：
International Journal of Database Theory and Application,2015年8(6):1-12 ISSN：2005-4270
通讯作者：
Yongbin, Liu(qingbinliu@163.com)
作者机构：
[Yongbin, Liu; Shuqing, Zhang; Chunping, Ouyang; Xiaohua, Yang] School of Computer Science and Technology, University of South China, Hunan Hengyang, China
摘要：
现有组信任模型在维护信任关系的稳定性与负载均衡能力方面存在局限性。为解决这些问题,提出一种稳定性增强的组信任模型SEGTM(stability enhanced group based trust model),以动态组构造与管理为基础,划分同组及跨组节点间的信任关系并给予了各自的度量方法,较好地解决了信任模型因信任网络拓扑动态改变而难以有效维护信任关系度量的准确性问题。仿真实验结果表明,该模型在应对网络拓扑动态变化时具有较好的稳定性和负载均衡能力,同时也能有效抵抗恶意节点的攻击。
