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Knowledge Search for Cloud Computing Industry Alliance: An Algorithm Based on Improved Particle Swarm Optimization |
Gao Changyuan1,2(), Yu Jianping1, He Xiaoyan1,2 |
1College of Management, Harbin University of Science and Technology, Harbin 150040, China 2High-tech Industrial Development Research Center, Harbin University of Science and Technology, Harbin 150040, China |
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Abstract [Objective] This paper uses an algorithm based on the improved particle swarm optimization to conduct knowledge search for cloud computing industry alliance, aiming to improve its accuracy and efficiency. [Methods] First, we utilized the Map function of the MapReduce model to process particle grouping. Secondly, we used the Reduce function to shorten the particle search result lists and search time. Lastly, the information interaction of the particles was decided by the average value of the optimal position within each group, which avoided the premature convergence of using a local optimal value. [Results] We compared the performance of the improved algorithm with the standard ones by three rounds of simulation experiments. We found that the improved particle swarm algorithm was superior in efficiency and accuracy. [Limitations] There is some noisy data in the sample. [Conclusions] The proposed algorithm could improve the accuracy and efficiency of knowledge search for the cloud computing industry alliance.
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Received: 27 June 2016
Published: 20 April 2017
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[1] |
翟丽丽, 柳玉凤, 王京, 等. 软件产业虚拟集群企业间信任进化博弈研究[J]. 中国管理科学, 2014, 22(12): 118-125.
|
[1] |
(Zhai Lili, Liu Yufeng, Wang Jing, et al.Research on Evolutionary Game on Trust Among Software Industrial Virtual Cluster’s Enterprises[J]. Chinese Journal of Management Science, 2014, 22(12): 118-125.)
|
[2] |
史恒亮, 任崇广, 白光一, 等. 自适应蚁群优化的云数据库动态路径查询[J]. 计算机工程与应用, 2010, 46(9): 10-12.
doi: 10.3778/j.issn.1002-8331.2010.09.004
|
[2] |
(Shi Hengliang, Ren Chongguang, Bai Guangyi, et al.Cloud Database Dynamic Route Query Based on Self-adaptive Ant Colony Optimization[J]. Computer Engineering and Applications, 2010, 46(9): 10-12.)
doi: 10.3778/j.issn.1002-8331.2010.09.004
|
[3] |
Hiremath N C, Sahu S, Tiwari M K.Multi Objective Outbound Logistics Network Design for a Manufacturing Supply Chain[J]. Journal of Intelligent Manufacturing, 2013, 24(6): 1071-1084.
doi: 10.1007/s10845-012-0635-8
|
[4] |
苏屹, 李柏洲, 刘晓静. 基于蚁群算法的R&D 支出拟合模型研究[J]. 情报杂志, 2012, 31(5): 198-201.
|
[4] |
(Su Yi, Li Baizhou, Liu Xiaojing.A Model Fitting Analysis of the R&D Expenditure Based on Ant Colony Algorithm[J]. Journal of Intelligence, 2012, 31(5): 198-201.)
|
[5] |
王洪峰, 王娜, 汪定伟, 等. 一种求解多峰优化问题的改进Species粒子群算法[J].系统工程学报, 2012, 27(6): 854-864.
doi: 10.3969/j.issn.1000-5781.2012.06.016
|
[5] |
(Wang Hongfeng, Wang Na, Wang Dingwei, et al.Improved Species-based Particle Swarm Optimizer for Multi-modal Optimization Problems[J]. Journal of Systems Engineering, 2012, 27(6): 854-864.)
doi: 10.3969/j.issn.1000-5781.2012.06.016
|
[6] |
Chatterjee A, Siarry P.Nonlinear Inertia Weight Variation for Dynamic Adaptation in Particle Swarm Optimization[J]. Computers & Operations Research, 2006, 33(3): 859-871.
doi: 10.1016/j.cor.2004.08.012
|
[7] |
Stefan J, Martin M.A Hierarchical Particle Swarm Optimizer and Its Adaptive Variant[J]. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 2005, 35(6): 1272-1282.
doi: 10.1109/TSMCB.2005.850530
pmid: 16366251
|
[8] |
Doctor S, Venayagamoorthy G K.Improving the Performance of Particle Swarm Optimization Using Adaptive Critics Designs[J]. Swarm Intelligence Symposium, 2005, 9(9): 393-396.
doi: 10.1109/SIS.2005.1501649
|
[9] |
王燕燕, 葛洪伟, 王娟娟, 等. 一种动态分组的粒子群优化算法[J]. 计算机工程, 2015, 41(1): 180-185, 189.
doi: 10.3969/j.issn.1000-3428.2015.01.033
|
[9] |
(Wang Yanyan, Ge Hongwei, Wang Juanjuan, et al.A Particle Swarm Optimization Algorithm of Dynamic Grouping[J]. Computer Engineering, 2015, 41(1): 180-185, 189.)
doi: 10.3969/j.issn.1000-3428.2015.01.033
|
[10] |
李志洁, 刘向东, 段晓东. 改进粒子群算法在网格资源分配中的优化[J]. 计算机集成制造系统, 2009, 15(12): 2375-2382.
doi: 10.1109/IFITA.2010.330
|
[10] |
(Li Zhijie, Liu Xiangdong, Duan Xiaodong.Optimization of Grid Resource Allocation Using Improved Particle Swarm Optimization Algorithm[J]. Computer Integrated Manufacturing Systems, 2009, 15(12): 2375-2382.)
doi: 10.1109/IFITA.2010.330
|
[11] |
李媛媛, 曲雯毓, 栗志扬, 等. 一种快速收敛粒子群优化算法在云计算中应用[J]. 华中科技大学学报: 自然科学版, 2012, 40(S1): 34-37.
|
[11] |
(Li Yuanyuan, Qu Wenyu, Li Zhiyang, et al.Particle Swarm Optimization Algorithm with Fast Convergence Applied in Cloud Computing[J]. Journal of Huazhong University of Science and Technology: Natural Science Edition, 2012, 40(S1): 34-37.)
|
[12] |
Shelokar P S, Siarry P, Jayaraman V K.Particle Swarm and Ant Colony Algorithms Hybridized for Improved Continuous Optimization[J]. Applied Mathematics and Computation, 2007, 188(1): 129-142.
doi: 10.1016/j.amc.2006.09.098
|
[13] |
范成礼, 邢清华, 付强, 等. 求解非线性双层规划问题的混合变邻域粒子群算法[J]. 系统工程理论与实践, 2015, 35(2): 473-480.
|
[13] |
(Fan Chengli, Xing Qinghua, Fu Qiang, et al.A Hybrid Intelligent Algorithm by Combining Particle Swarm Optimization with Variable Neighborhood Search for Solving Nonlinear Bilevel Programming Problems[J]. Systems Engineering-Theory & Practice, 2015, 35(2): 473-480.)
|
[14] |
罗宏. 基于改进粒子群算法的图书封面搜索引擎研究[J]. 情报科学, 2014, 32(4): 106-108, 121.
|
[14] |
(Luo Hong.Research on the Book Covers Search Engine Based on Improved PSO[J]. Information Science, 2014, 32(4): 106-108, 121.)
|
[15] |
李国辉, 冯明月, 易先清. 基于分群粒子群优化的传感器调度方法[J]. 系统工程与电子技术, 2010, 32(3): 598-602.
|
[15] |
(Li Guohui, Feng Mingyue, Yi Xianqing.Sensor Scheduling Method Based on Grouping Particle Swarm Optimization[J]. Systems Engineering and Electronics, 2010, 32(3): 598-602.)
|
[16] |
叶晓国. 基于NS-2的无线传感器网络仿真模块扩展方法的研究[J]. 计算机研究与发展, 2011, 48(S2): 302-306.
|
[16] |
(Ye Xiaoguo.NS-2- Based Simulation Module Extension Method for Wireless Sensor Networks[J]. Journal of Computer Research and Development, 2011, 48(S2): 302-306.)
|
[17] |
Liu Y, Chen J, Wang J.On Counting 3-D Matching of Size K[J]. Algorithmic, 2009, 54(10): 530-543.
doi: 10.1007/s00453-008-9207-x
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