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检索条件"机构=The Key Laboratory of Process Optimization and Intelligent Decision-Making"

共 221 条记录，以下是111-120 订阅

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A Simple Manner of Dynamic Gesture Recognition Based on Kinect

A Simple Manner of Dynamic Gesture Recognition Based on Kine...

引用

2016 International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2016)

作者： Fenggang Li Xiangfei Jiang Xiaobo Xia School of management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

ISBN: (纸本)9781510820524

The paper develops a simple method of dynamic gesture recognition based on the Kinect which is a new sensor from Microsoft in the environment of VS2010 combining Kinect for Windows SDK *** sensors can track human bodies within their effective scope in real-time and obtain the depth of the corresponding information and bones at the same ***,we separated each dynamic hand gesture to be a combination of several micro-gestures which were from predefined eight micro-gestures with eight different *** Dynamic Time Warping algorithm was adopted to find the most similar template gesture,then the system realized corresponding control instruction of the matched template gesture,and consequently,we can achieve somatosensory interaction by recognizing dynamic hand gestures,and the total recognition rate isn't less than 90%.

关键词： Kinect Somatosensory interaction depth information gesture recognition

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An Inventory Control Model for Perishable Items with Stochastic Replenishment Interval and Stock-dependent Selling Rate

An Inventory Control Model for Perishable Items with Stochas...

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第26届中国控制与决策会议

作者： Guang-fan Xu Xiao-jia Wang Yan-yan Wu Shan-lin Yang School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

ISBN: (纸本)9781479937097

Periodic replenishment inventory models are widely used in practice, especially for inventory systems in which many different goods are purchased from the same supplier. However, most of periodic replenishment inventory models have assumed a fixed length of the replenishment periods. In practice, it is possible that the replenishment periods are of a stochastic length. This paper presents an inventory control model for deteriorating items in the case of random replenishment intervals and stock-dependent selling rate. The replenishment interval is assumed to obey from two different distributions, namely, exponential and uniform distributions. Also, shortages are allowed in the term of partial backordering. For this model, we provide the necessary and sufficient conditions of the existence and uniqueness of the optimal solutions and a procedure is also developed to determine the optimal solution for the proposed models. At last, numerical example is shown to illuminate the presented model.

关键词： stochastic replenishment interval,stock-dependent selling rate,inventory control,partial backlogging,deteriorating items

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Two-stage charge and discharge optimization of battery energy storage systems in microgrids considering battery state of health

Two-stage charge and discharge optimization of battery energ...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Zenghui Zhang Kaile Zhou Shanlin Yang Key Laboratory of Process Optimization and Intelligent Decision-Making School of Management Hefei University of Technology Hefei China

An important figure-of-merit for battery energy storage systems (BESSs) is their battery life, which is measured by the state of health (SOH). In this study, we propose a two-stage model to optimize the charging and discharging process of BESS in an industrial park microgrid (IPM). The first stage is used to optimize the charging and discharging time and the corresponding amount of the charging and discharging energy from the BESS, in which the SOH is considered. Subsequently, all battery packs need to be coordinated to ensure a reasonable BESS operation. In order to prolong the service life of the BESS, the second stage of the model allocates the charging and discharging of all battery packs on the basis of the first stage scheduling results. The proposed loss-calculation method is used to calculate the battery pack loss and then to calculate the SOHs of battery packs. It can be seen from the simulation results that the scheduling results considering the SOH are more realistic. Furthermore, the proposed charging and discharging allocation strategy can effectively coordinate the SOH change of all battery packs without causing a significant increase in the battery pack loss of the battery packs.

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The Utility Frequent Pattern Mining Based on Slide Window in Data Stream

The Utility Frequent Pattern Mining Based on Slide Window in...

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International Conference on intelligent Computation Technology and Automation, ICICTA

作者： Feng-gang Li Ying-jia Sun Zhi-wei Ni Yu Liang Xue-ming Mao Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei China

In traditional study of mining data stream, each item in the data stream is of equal importance. However, in practice, each item has a different significance, which is known as utility. This paper combines frequent mining item sets with utility and proposes an efficient algorithm for utility frequent pattern mining (UFPM). It combines bitmap with tree structure that can store and update the pattern of data stream quickly and completely by scanning only once. The algorithm generated by lexicographic order, proposes a novel tree U-tree and makes convenience for pattern updating and user reading. With a pattern growth approach in mining, the algorithm can effectively avoid the problem of a mass candidacy generation by level-wise searching. The experiments results show that our algorithm which is in high efficiency and good scalability outperforms the existing analogous algorithm.

关键词： Data mining Itemsets Algorithm design and analysis Scalability Focusing Automation

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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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Can constraint energy-saving policy facilitate industrial green production performance in China?

Can constraint energy-saving policy facilitate industrial gr...

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第三届能源与环境研究进展国际学术会议（ICAEER 2018）

作者： Yue Yao Jianling Jiao Xiaofei Han School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

The role of constraint energy-saving policy(ESP) playing in the coordinated development of energy conservation, emission reduction, and economic growth is of great significance to the country's sustainable progress. Applying a non-radial and non-oriented DEA model incorporating innovation output and multiple undesirable outputs, this paper measures the green production performance(GPP) of China's industrial sectors from 2002 to 2015. And then the effect of implementing energy-saving policy on GPP is investigated through Quasi-difference-in-differences(Quasi-DID) method. The results show that China's industrial GPP rises during 2002-2004 and then declines with fluctuations. Technology change(TC) is the dominant driver. Energy-saving policy positively affects industrial GPP in general yet further dynamic analysis reveals that such a positive effect remains unstable and finally manifests a reverse impact at the end of every five-year-plan period. Therefore, China should properly introduce market mechanisms, formulate comprehensive policy mix strategies to balance sustainable improvement of industrial economy and ecological environment.

关键词： ESP GPP Can constraint energy-saving policy facilitate industrial green production performance in China

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Comprehensive Evaluation and Temporal-spatial Evolution of the Development Level of Tourism about the Cities of Anhui

Comprehensive Evaluation and Temporal-spatial Evolution of t...

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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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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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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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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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