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2nd International Conference on Advanced Design and Manufacturing Engineering (ADME 2012)

作者： Chen Jian-xue Shanghai Univ Engn Sci Coll Elect & Elect Engn Shanghai 201620 Peoples R China

ISBN: (纸本)9783037855027

Fault diagnosis is an important problem in the process of chemical industry and the artificial neural network is widely applied in fault diagnosis of chemical process. A hybrid algorithm combining ant colony optimization (ACO) algorithm with back-propagation (BP) algorithm, also referred to as ACO-BP algorithm, is proposed to train the neural network weights and thresholds. The basic theory and steps of ACO-BP algorithm are given, and applied in fault diagnosis of the continuous stirred-tank reactor (CSTR). Experimental results prove that ACO-BP algorithm has good fault diagnosis precision, and it can detect the fault in CSTR promptly and effectively.

关键词： Fault diagnosis ant colony optimization algorithm Back-propagation algorithm Neural network CSTR

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The analysis of the convergence of ant colony optimization algorithm

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Frontiers of Electrical and Electronic Engineering in China 2007年第3期2卷 268-272页

作者： ZHU Qingbao WANG Lingling Department of Computer Science Nanjing Normal UniversityNanjing 210097China

The ant colony optimization algorithm has been widely studied and many important results have been *** this algorithm has been applied to many fields,the analysis about its convergence is much less,which will influence the improvement of this ***,the convergence of this algorithm applied to the traveling salesman problem(TSP)was analyzed in *** conclusion that this algorithm will definitely converge to the optimal solution under the condition of 0

关键词： ant colony optimization algorithm convergence analysis heuristic function TSP

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An ant colony optimization approach for the preference-based shortest path search

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JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2011年第2期34卷 181-196页

作者： Ok, Seung-Ho Seo, Woo-Jin Ahn, Jin-Ho Kang, Sungho Moon, Byungin Kyungpook Natl Univ Sch Elect Engn Taegu 702701 South Korea Kyungpook Natl Univ Sch Elect Engn & Comp Sci Taegu 702701 South Korea Hoseo Univ Dept Elect Engn Asan 336795 Chungnam South Korea Yonsei Univ Dept Elect & Elect Engn Seoul 120749 South Korea

This article proposes a modified ant colony system algorithm for finding the shortest path with preferred links. Most of the shortest path search algorithms focus on finding the distance or time shortest paths. However, these shortest paths may not necessarily be the optimum path for drivers who prefer choosing a less short, yet more reliable or flexible path. Accordingly, a preference-based shortest path search algorithm is proposed that uses the properties of the links in a map, as specified by a set of data provided by the user of the car navigation system. The proposed algorithm is implemented in C and experiments are performed using maps that include 64, 128, 192, and 256 nodes with 118, 242, 362, and 484 links, respectively. The simulation results with various parameter sets confirm that the proposed algorithm is effective for finding the preference-based shortest path.

关键词： shortest path search algorithm car navigation system ant colony optimization algorithm artificial intelligence

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An Approach to Feature Selection Based on ant colony optimization and Rough Set

An Approach to Feature Selection Based on Ant Colony Optimiz...

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International Conference on Intelligent Computing and Information Science

作者： Wu, Junyun Qiu, Taorong Wang, Lu Huang, Haiquan Nanchang Univ Dept Comp Nanchang 330031 Jiangxi Peoples R China

ISBN: (纸本)9783642181283

Feature selection plays an important role in many fields. This paper proposes a method for feature selection which combined the rough set method and ant colony optimization algorithm. The algorithm used the attribute dependence and the attribute importance as the inspiration factor which applied to the transfer rules. For further, the quality of classification based on rough set method and the length of the feature subset were used to build the pheromone update strategy. Through the test of data set, results show that the proposed method is feasible.

关键词： Feature selection ant colony optimization algorithm Rough set

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The multi-objective routing optimization of WSNs based on an improved ant colony algorithm

The multi-objective routing optimization of WSNs based on an...

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6th International Conference on Wireless Communications, Networking and Mobile Computing (WICOM)

作者： Xuwei Lizhi Si Chuan Univ Sch Elect & Informat Engn Chengdu Si Chuan Peoples R China

ISBN: (纸本)9781424437092

At present most of the WSNs routing protocol only have a single research objective. The overall network performance lacks of multi-objective inspection and evaluation. The basic task of multi-objective routing is to find a route in the network which has sufficient resources to optimize some network parameters and satisfy multiple constrains. A multi-objective model, constrained of bandwidth, is put forward, which optimizes function such as energy consumption, network delay and data packet lost rate. By adjusting the weight of each function, the algorithm adapts well to various services whose requirements for energy cost, delay and lost are different. As it is difficult to optimize multi-objective problem, an advanced ant colony algorithm based on cloud model (AACOCM) is proposed, which can effectively restrict the algorithm to falling in local best. Simulation results show that this novel method has a certain validity and feasibility and be able to adapt to different services requirements.

关键词： WSNs ant colony optimization algorithm Multi-object routing Cloud model

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Fault diagnosis based on support vector machines with parameter optimization by an ant colony algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2010年第C1期224卷 217-229页

作者： Zhang, X. L. Chen, X. F. He, Z. J. Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Peoples R China

Since support vector machines (SVM) exhibit a good generalization performance in the small sample cases, these have a wide application in machinery fault diagnosis. However, a problem arises from setting optimal parameters for SVM so as to obtain optimal diagnosis result. This article presents a fault diagnosis method based on SVM with parameter optimization by ant colony algorithm to attain a desirable fault diagnosis result, which is performed on the locomotive roller bearings to validate its feasibility and efficiency. The experiment finds that the proposed algorithm of ant colony optimization with SVM (ACO-SVM) can help one to obtain a good fault diagnosis result, which confirms the advantage of the proposed ACO-SVM approach.

关键词： fault diagnosis support vector machines ant colony optimization algorithm parameter optimization

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RATE: A RSU-Aided Scheme for Data-Centric Trust Establishment in VANETs

RATE: A RSU-Aided Scheme for Data-Centric Trust Establishmen...

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7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM)

作者： Wu, Aifeng Ma, Jianqing Zhang, Shiyong Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China

ISBN: (纸本)9781424462520

In the research area of vehicular ad-hoc networks (VANETs), a novel notion named data-centric trust establishment is introduced recently, which means the trustworthiness of data is evaluated according to the data's intrinsic properties instead of the reputation of providing entities. In this paper, we propose a Roadside-unit Aided Trust Establishment scheme (RATE) that aims to execute data-centric trust establishment in VANET efficiently(1). Compared to existing trust establishment approaches, RATE is completely data-centric, making RATE appropriate for rapidly changing environment. In addition, through the employment of ant colony optimization algorithm, RATE has ability to integrate direct observed data with feedback information when evaluating the trustworthiness of data, eventually improves the accuracy of evaluation result. Lastly, RATE decouples data-consuming and data-providing entities, thus enables vehicles to mitigate the attacks launched by malicious nodes through directly-linked communications. Simulation shows that RATE can effectively analyze data provided in VANET and correctly establish trust on data.

关键词： Aging Computational fluid dynamics Delay Educational institutions RSU-aided scheme Resilience Roads VANET Vehicles ant colony optimization algorithm data-centric trust establishment directly-linked communications malicious nodes optimisation roadside-unit aided trust establishment scheme vehicular ad hoc networks vehicular ad-hoc networks

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Study on the application of simulated evolutionary optimization algorithm in optimizing the combination of unit commitments in power system

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3rd International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2011)

作者： Liu Qing-song Tong Jia Li Yi-feng Jiaxing Univ Jiaxing 314001 Zhejiang Peoples R China Guangdong Ocean Univ Zhanjiang Guangdong 524088 Peoples R China

ISBN: (纸本)9783037850190

This study adopted a simulated evolutionary optimization algorithm, ant colony optimization algorithm to find the optimal unit commitment operation. The concepts such as status, strategy, and path, etc. were introduced to devise the optimization of unit commitment operation by ant colony optimization algorithm mode, so that the optimal unit commitment operation could be found by ant colony optimization algorithm. To cope with different constraints by additional penalties and restrict the statuses not satisfying the constraints by tabu table, the retrieval of ant colony optimization algorithm could always be performed in feasible region and the retrieval process of the algorithm was effectively conducted. It is feasible and efficient to find the optimal unit commitment operation by ant colony optimization algorithm, which was proved by stimulation.

关键词： Power system Optimal operation Optimal unit commitment operation Evolutionary optimization algorithm ant colony optimization algorithm

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Analyzing the Chaotic Behavior of an ACO Based Artificial Stock Market

Analyzing the Chaotic Behavior of an ACO Based Artificial St...

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第三十届中国控制会议

作者： TANG Maoning~1,SUN Yongzheng~(2*),LI Wang~2,LIU Maoxing~3 1.Department of Mathematics,Huzhou University,Huzhou 313000,P.R.China 2.School of Sciences,China University of Mining and Technology,Xuzhou 221008,P.R.China 3.Department of Mathematics,North University of China,Taiyuan 030051,P.R.China

An evolution model based on the ant colony optimization algorithm for investment behavior in the stock market is *** largest Lyapunov exponents of the stock price time series created from the model are *** simulation results show that this model can not only create stock price trends rather similar to the real stock market,but also show the chaotic behavior like the real stock *** observed that the more speculators among the investors the bigger the largest Lyapunov exponent and the stronger the chaotic behavior in stock markets.

关键词： ant colony optimization algorithm Stock market Chaos

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Parallel ant colony optimization algorithm

Parallel ant colony optimization algorithm

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6th World Congress on Intelligent Control and Automation

作者： Liu, Hong Li, Ping Wen, Yu Zhejiang Univ Natl Lab Ind Control Technol Res Ctr Intelligent Transportat Syst Hangzhou 310027 Zhejiang Provin Peoples R China

ISBN: (纸本)1424403316

ant colony optimization algorithm is a good way to solve complex multi-stage decision problems. But the construction graph and computation steps for an ant to construct a solution in the construction graph will be exponentially increased, if the stage number and decision variable dimension of complex multi-stage decision problem are increasing. It will cause the ant colony optimization algorithm can not be computed by a single PC. Therefore, a parallel ant colony optimization algorithm based on the construction graph decomposition is presented to solve this problem. The parallel ant colony optimization algorithm decomposes the construction graph into some parts and each part is placed on different PC. The whole computation task is accomplished by mutual cooperation in the PCs which join in the computation. Experiment has verified that it can solve this problem and improve the computation efficiency.

关键词： parallel computing ant colony optimization algorithm multi-stage decision construction graph decomposition

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