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第27届中国控制与决策会议

作者： He Luo Jie Cao Yongkang Wang Xiaoxuan Hu School of Management Hefei University of Technology Key Laboratory of the Ministry of Education on Process Optimization & Intelligent Decision Making

ISBN: (纸本)9781479970186

The data center Energy Consumption(EC) and the user Quality of Service(QoS) are two important influencing factors,which the cloud service provider must balance in the process of providing virtual cloud services resources(VCSR).For the VCSR over-deployment phenomenon happening in cloud computing Infrastructure as a Service(IAAS),a user-oriented deployment constraint of VCSR is proposed,and the definition of user's Service Level Agreements(SLA) and the energy consumption of data center are also *** the basis of that,the model of dynamic migration of the virtual nodes is given,solved by simulated annealing *** the experiments,different strategies are compared using *** results show that the suggested strategy has advantages on balancing the energy consumption of data center and user's QoS.

关键词： Cloud computing Virtualization Dynamic consolidation Service Level Agreements

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An improved discrete optimization algorithm based on artificial fish swarm and its application for attribute reduction

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Journal of Information and Computational Science 2015年第6期12卷 2143-2154页

作者： Ni, Zhiwei Zhu, Xuhui Ni, Liping Cheng, Meiying Wang, Yiling School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei China

The discrete Artificial Fish Swarm Algorithm (AFSA) has some defectives, such as falling into local optimum value, converging slowly. In order to overcome these shortcomings, an improved discrete optimization algorithm based on artificial fish swarm (IDAFSA) is proposed by improving swarming and preying behavior and moving way for making it discrete, and introducing a strategy of overcoming the local optimum. In addition, the paper strengthens the theoretical basis of the algorithm by proving the global convergence. And then, this algorithm which was combined with fractal dimension is applied to attribute reduction problem. Finally, analyzing the parameters in detail and comparing with other literatures by testing six UCI datasets, and the experimental results show that the method has relatively high feasibility and effectiveness. Copyright © 2015 Binary Information Press.

关键词： Fractal dimension

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Binary ant colony algorithm with particle optimization feature for attribute reduction problem

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Journal of Information and Computational Science 2015年第8期12卷 3051-3061页

作者： Ni, Zhiwei Cheng, Meiying Wu, Zhangjun Xiao, Hongwang Zhu, Xuhui School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei China

According to the lack of initial pheromone which leads to the long searching time of the Binary Ant Colony algorithm (BACO), a novel method named Binary Ant Colony Algorithm with Particle optimization Feature (PBACO) is proposed in this paper. Starting from one-dimensional cellular automata model, the initial solution is produced by Binary Particle Swarm optimization (BPSO). Then mapping mechanism is introduced to convert the position of particle into pheromone, in this way, a path with distinct discrepancy level of pheromone is generated in the shortest time, and the total searching time of BACO is greatly reduced. At last, PBACO combined with fractal dimension is utilized to solve attribute reduction problem. Six datasets are used to conduct experiments. Experimental results show that our proposed method has comparatively high classification accuracy. Copyright © 2015 Binary Information Press.

关键词： Cellular automata

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Fuzziness parameter selection in fuzzy c-means: The perspective of cluster validation

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Science China(Information Sciences) 2014年第11期57卷 252-259页

作者： ZHOU KaiLe FU Chao YANG ShanLin School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education

Fuzzy c-means(FCM) algorithm is an important clustering method in pattern recognition, while the fuzziness parameter, m, in FCM algorithm is a key parameter that can significantly affect the result of clustering. Cluster validity index(CVI) is a kind of criterion function to validate the clustering results, thereby determining the optimal cluster number of a data set. From the perspective of cluster validation, we propose a novel method to select the optimal value of m in FCM, and four well-known CVIs, namely XB, VK, VT, and SC, for fuzzy clustering are used. In this method, the optimal value of m is determined when CVIs reach their minimum values. Experimental results on four synthetic data sets and four real data sets have demonstrated that the range of m is [2, 3.5] and the optimal interval is [2.5, 3].

关键词： clustering fuzziness parameter fuzzy c-means(FCM) cluster validation cluster validity index

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Empirical analysis of the factors of government administrative preparation of China

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Journal of Computational and Theoretical Nanoscience 2015年第11期12卷 4352-4357页

作者： Long, Zhu Jiang, Dai Changyong, Liang Management School of Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei230009 China

A previous study conducted in Anhui Province by collecting data from 56 county-level governments in 2009 has shown that the factors of demographic, financial and geographical area have linear relationship with government administrative preparation. The administrative preparation of county-level government increased with the size of population, expenditure and geographical area. Geographical area has great impact on administrative preparation, followed by least impact of financial and population. Taking a county government for example, the geographical area is unchanged but household population changed slowly. So the main factor affected the total administrative preparation is financial expenditure. In the process of approving the county government administrative preparation should consider several factors, such as population movements around. The main objective of this study is to prove that administrative preparation should be based on resident population rather than household population. © 2015 American Scientific Publishers.

关键词： Finance

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Software project management based on dynamic programming algorithm

Software project management based on dynamic programming alg...

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International Conference on Information Sciences,Machinery,Materials and Energy（ICISMME 2015）

作者： Zhidong Li Xiaohuan Yu School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Nanjing University of Posts and Telecommunications

With the rapid development of computer technology,software engineering disciplines has developed rapidly not only in the aspect of theory,but is increasingly important in the practical application,and gradually formed methodologies,tools and management of three *** these three factors,the study of software project management is relatively backward,and even become a major obstacle in the development of software engineering ***,in view of software engineering discipline facing the problem,this paper proposed dynamic programming algorithm should be applied to software engineering management.

关键词： computer technology software engineering management dynamic programming

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Approximation algorithms for two-stage supply chain scheduling of production and distribution

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International Journal of Systems Science: Operations and Logistics 2015年第2期2卷 78-89页

作者： Cheng, Bayi Li, Kai Hu, Xiaoxuan School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China

In this paper, we investigate a class of two-stage optimisation problems for manufacturers in supply chains. The objective is to optimise production and outbound distribution. In the production part, the manufacturer has identical batch-processing machines with limited capacity in size. The processing times and sizes of jobs are determined by the customer. As long as the total size of jobs in a batch does not exceed the machine capacity, the batch can be processed on any machine. The processing of a batch cannot be interrupted until all the jobs in the batch have been completed. In the distribution part, the manufacturer assigns the completed jobs in groups and delivers them to the customer with its own vehicles. We propose the model of minimising service span, which lasts from the processing of the first job to the delivery of the last job. We investigate two types of machine configuration, including single machine and parallel machines. In the vehicle configuration, we consider two cases including infinite vehicles and a fixed number of vehicles. We show all the problems under investigation are NP-hard. For each problem, we design an effective polynomial time algorithm. We analyse the time complexity and show the performance guarantees of the algorithms. © 2014, © 2014 Taylor & Francis.

关键词： approximation algorithm arbitrary-size jobs batch-processing machines supply chain scheduling

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Electricity load forecasting in smart grid based on residual GM (1, 1) model

Electricity load forecasting in smart grid based on residual...

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2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013

作者： Shen, Jianxin Wang, Haijiang Yang, Shanlin Key Lab of Process Optimization and Intelligent Decision-making Hefei University of Technology Hefei China

ISBN: (纸本)9783319012728

The construction of smart grid has put forward higher requirements on deployment accuracy of the energy. Power generation and electricity sectors have carried out more accurate data analysis and forecasting. In this context, a residual GM (1, 1) model is proposed. This model can overcome the lack of traditional grey model and make accurate forecasting of electricity consumption in smart grid. Finally, numerical examples demonstrate that this method can efficiently improve the prediction accuracy. © Springer International Publishing Switzerland 2014.

关键词： Smart power grids

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Electricity consumption prediction based on non-stationary time series GM (1, 1) model and its application in power engineering

Electricity consumption prediction based on non-stationary t...

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2013 International Conference on Mechatronics and Automatic Control Systems, ICMS 2013

作者： Wang, Xiaojia China Key Lab of Process Optimization and Intelligent Decision-making Hefei University of Technology Hefei China

ISBN: (纸本)9783319012728

The construction of smart grid will comprehensively enhance the intelligent level of every step in the power grid of our country. The data prediction ability determines the quality of smart grid. This paper addresses situations in which the prediction accuracy of the Grey Model (GM (1, 1) model) is high for non-negative smooth monotonic sequences but inadequately low for non-stationary sequences, and isolates the trending sequence from the non-stationary time series using a numerical filtering algorithm, which is then used to make predictions. Numerical examples demonstrate that this method can improve the prediction accuracy of the GM (1, 1) model. © Springer International Publishing Switzerland 2014.

关键词： Forecasting

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Disagreement-based semi-supervised learning method for enterprise credit risk assessment

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ICIC Express Letters 2015年第6期9卷 1671-1676页

作者： Wang, Gang Li, Ningning School of Management Hefei University of Technology No. 193 Tunxi Road Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei University of Technology No. 193 Tunxi Road Hefei China

The enterprise credit risk assessment problem has long been regarded as an important and widely studied issue in both academia and industry. However, unla-beled data problem is paid less attention to in the credit risk assessment community. To fill in this research gap, one of popular disagreement semi-supervised learning methods, co-training, is introduced to exploit the unlabeled data to improve the enterprise credit risk assessment performance. Co-training allows one to start with just a few labeled instances to produce an initial weak classifier and then use unlabeled data to improve the performance. Experiments based on two credit datasets reveal that co-training SVM&DT (Support Vector Machine & decision Tree) gets the better performance than the compared methods. Based on these results, we can conclude that co-training SVM&DT can be used as an alternative method for enterprise credit risk assessment. © 2015 ICIC International.

关键词： decision trees

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