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第十届（2015）中国管理学年会

作者： Zhang Xin Lu Xiao-mei Du Li-yan School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

This paper firstly builds a comprehensive evaluation of the development level of tourism industry about the cities of Anhui,then it uses AHP to determine the weight and TOPSIS method to analyze the development level of tourism industry about the cities of Anhui in 2004,2008 and 2012. The method of the Markov chain analyzes the time pattern evolution of the development level of tourism industry,and the spatial autocorrelation analysis of Arc GIS10.0 software explores the temporal-spatial evolution of the development level of tourism industry about the cities. The results show that the tourism industry of Anhui province has been initially formed agglomeration effect,the region's tourism industry development in southern Anhui is always strong,the growth of tourism industry development level in the middle area of Anhui is most prominent,and the region's tourism industry development in northern Anhui is always weak.

关键词： Tourism Industry Temporal-spatial Evolution TOPSIS Method Markov Chain The Spatial Autocorrelation Analysis

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The Dynamic Migration Model for Cloud Service Resource Balancing Energy Consumption and QoS

The Dynamic Migration Model for Cloud Service Resource Balan...

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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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Distributionally Robust optimization for Internet Data Center with Renewable Energy

Distributionally Robust Optimization for Internet Data Cente...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Kaile Zhou Zhineng Fei Xinhui Lu Key Laboratory of Process Optimization and Intelligent Decision-making School of Management Hefei University of Technology Hefei China

ISBN: (纸本)9781665434263

More and more internet data centers (IDCs) are trying to use renewable energy sources (RESs). However, powering IDCs with intermittent RESs presents a significant challenge. In addition, power and workload management in IDCs has great potential to reduce energy consumption, carbon footprints and energy cost. This study proposes an optimal load dispatch model for an IDC with battery energy storage system (BESS), which aims to lower the total costs. To accommodate the uncertainties of wind power, a data-driven distributionally robust optimization (DDRO) method is adopted. Then the column-and-constraint generation method (C&CG) is used to solve the corresponding optimization problem. In the experiment with the real-world traces of workload arrival and wholesale electricity price, three scheduling scenarios are investigated. Moreover, robust optimization and stochastic programming are implemented for comparison. Experimental results reveal that total costs of the IDC can be effectively reduced by adopting BESS and implementing workload dispatch. Meanwhile, the results also demonstrate the effectiveness of DDRO approach.

关键词： Renewable energy sources Data centers Costs Uncertainty Stochastic processes System integration Wind power generation

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Notice of Retraction: Research of fractal dimension calculation algorithm based on Mobile Box-Counting Method

Notice of Retraction: Research of fractal dimension calculat...

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International Conference on Natural Computation (ICNC)

作者： Feng-gang Li Wei-feng Gong Ying Li Yu Liang Xiao-lu Wang Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei China

This article has been retracted by the publisher.

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Photovoltaic Power Forecasting Based on SVM Optimized by Improved ABC

Photovoltaic Power Forecasting Based on SVM Optimized by Imp...

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作者： Lin Liu Yanyun Lu Shuqin Li School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

In order to improve the accuracy of photovoltaic power output prediction, a photovoltaic power prediction method based on similar days and improved artificial bee colony support vector machine is proposed. Firstly, through calculating the Euclidean distance of history day and measured day meteorological factors to determine similar days. Secondly, select historical data of photovoltaic power output, temperature, humidity and daily radiation on the slope of similar days and temperature, humidity and daily radiation on the slope of test date as input variables of support vector machine. And we adopt the improved artificial bees colony to optimize kernel function parameters and the penalty factor of support vector machine. Finally get the output in each period of photovoltaic power prediction. The experimental results showed that the proposed method can effectively improve the prediction accuracy of photovoltaic power.

关键词： Photovoltaic Power Forecasting Based on SVM Optimized by Improved ABC

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Novel correlation coefficients for hesitant fuzzy sets and their applications to supplier selection and medical diagnosis

Novel correlation coefficients for hesitant fuzzy sets and t...

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作者： Yang, Jinxin Tang, Xiaoan Yang, Shanlin School of Management Hefei University of Technology Box 270 Hefei Anhui230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Anhui China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

Hesitant fuzzy set theory provides an effective technique for researchers and engineers to cope with vagueness and uncertainty. In recent years, to explore the correlation between hesitant fuzzy sets, traditional correlation measure in statistics has been constantly studied in hesitant fuzzy environments. In this study, extant studies of correlation measures in hesitant fuzzy contexts are recalled and analyzed. In view of the forgoing analysis, we find out that the extant correlation coefficients have some limitations. Moreover, a few correlation coefficients are not in line with the traditional definition of correlation coefficients. In order to address the flaws of the existing proposals, a novel hesitant fuzzy correlation coefficient is proposed in this study. The new proposal of this study can not only overcome the flaws of the old hesitant fuzzy correlation coefficients, but it also shows several desirable characteristics. The weighted form of the newly defined correlation coefficient and its features are also investigated. Finally, three numerical examples concerning supplier selection and medical diagnosis are examined using the developed correlation coefficients to demonstrate their applicability. Comparison analyses with existing proposals highlight the efficiency of our proposals. © 2018 - IOS Press and the authors. All rights reserved.

关键词： decision making

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The forecasting of weekly tourists visiting a scenic area in off-season by using goodness of fit weight

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International Journal of Smart Home 2016年第3期10卷 21-30页

作者： Ma, Yin-Chao Liang, Chang-Yong Lu, Cai-Hona School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China

Due to the impact of external objective factors, the weekly number of tourist distribution is imbalance and shows strong nonlinear characteristics, especially more obvious in the off-season. Aiming at this problem, this paper built two different forecasting models by SVR and BP neural network in order to guess about the weekly tourist numbers and then, put forward the Goodness of Fit Weight (GFW) and used it to make three SVR-BP combination models (LCM, GEOM-WTD, and HARM). In order to support the results empirically, Data of the Huangshan Scenic Area has been used and the dynamic virtual variable was adopted to deal with the objective factors that influence the weekly visitor numbers. Finally, we compare the results with the two combination models that based on the VARW and MSEW, it shows that the GFW combination model is helpful for the combination forecasting and can be used as one of selections just like other weights, and the use of dynamic virtual variables can further improve the forecasting precision. © 2016 SERSC.

关键词： Forecasting

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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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The selection of project management software by FAHP and FMCDM in automobile R&D process

The selection of project management software by FAHP and FMC...

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International Conference on Networking and Digital Society, ICNDS

作者： Lei Fu Li Shi Ying Yang Bengong Yu Key Laboratory of Process Optimization & Intelligent Decision-making of Ministry of Education School of Management Hefei University of Technology Hefei China

ISBN: (纸本)9781424451623;9781424451616

The selection of project management (PM) software is a complex issue and has significant impacts to the efficiency of the automobile research & development (R&D) process. Given two alternatives based on critical path method (CPM) and critical chain project management (CCPM) respectively, decision-makers usually cause confusion. This paper analyzed the characteristic of automobile R&D project and developed an evaluation model based on the fuzzy analytic hierarchy process (FAHP) and fuzzy multiple criteria decision making (FMCDM) methods, which can help the managers in automobile industry to select more appropriate software in the course of product R&D. In particular, the FAHP method is used to obtain the weights of evaluation criteria, and the FMCDM method is used to determine the final rank of the software. The uncertainty and vagueness in evaluation procedure were presented as the fuzzy triangular numbers. The proposed method is applied to the case study of evaluating the performance of PM software based on CPM and CCPM respectively for a car manufacturer. The result of evaluation not only assisted managers in choosing suitable software but also outline the trend in development of CCPM software.

关键词： Project management Automobiles Research and development Research and development management Software development management decision making Computer industry Software performance Application software Job shop scheduling

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