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2012 International Conference on Computer Science and Service System, CSSS 2012

作者： Wu, Hao Wang, Huiying Li, Huaiying Jiang, Miao School of Management Hefei University of Technology India Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei 230009 China

ISBN: (纸本)9780769547190

In data stream mining, sliding window can record the latest and most useful patterns, but the best size can not be accurately determined. To aim at data with the characteristics of data flow in some simulation systems, this paper proposes a method for mining the closed frequent patterns in the mixed window of data stream. The pattern of data stream could be completely recorded by scanning the stream only once. And the pruning method of T-Moment could reduce the space complexity of sliding window tree and the maintenance cost of the closed frequent patterns tree. To differentiate the historical and the latest patterns, a time decaying model was applied. The experimental results show that the algorithm has good efficiency and accuracy. © 2012 IEEE.

关键词： Forestry

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Multi agent negotiation model for distributed task allocation

Multi agent negotiation model for distributed task allocatio...

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2010 2nd IEEE International Conference on Information Management and Engineering, ICIME 2010

作者： Luo, He Hu, Xiao-Jian Hu, Xiao-Xuan School of Management Hefei University of Technology Hefei China Key Laboratory of Ministry of Education on Process Optimization and Intelligent Decision Making Hefei China

ISBN: (纸本)9781424452644

In the multi agent system, negotiation between different agents becomes more and more complex when the distributed tasks need to be allocated among them. Usually, this process has been done in the centralized way where agents have all the information of both the tasks and the environment. However, in the real application such as satellite scheduling problem or production scheduling problem, not all the information can be acquired, some of them even cannot be known. Therefore, in this paper, we propose a multi agent negotiation model for distributed task allocation in a priority based environment. This process is modeled as a finite Markov decision process (F-MDP), and a coordinated negotiation protocol is also suggested to support the model. The experiments show that tasks are allocated in an efficient way, and it can also reduce the communication cost. © 2010 IEEE.

关键词： Multi agent systems

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POLYNOMIAL DYNAMIC PROGRAMMING ALGORITHMS FOR LOT SIZING MODELS WITH BOUNDED INVENTORY AND STOCKOUT AND/OR BACKLOGGING

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Journal of Systems Science and Systems Engineering 2016年第3期25卷 370-397页

作者： Jinhong Zhong Feng Chu Chengbin Chu Shanlin Yang School of Management Hefei University of Technology Hefei 230009 China Laboratoire IBISC Universite d'Evry-Val d'Essone France Laboratoire Genie Industriel Ecole Centrale Paris France Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei China

This paper addresses a dynamic lot sizing problem with bounded inventory and stockout where both no backlogging and backlogging allowed cases are considered. The stockout option means that there is outsourcing in a period only when the inventory level at that period is non-positive. The production capacity is unlimited and production cost functions are linear but with fixed charges. The problem is that of satisfying all demands in the planning horizon at minimal total cost. We show that the no backlogging case can be solved in O（T^2） time with general concave inventory holding and outsourcing cost functions where T is the length of the planning horizon. The complexity can be reduced to O（T） when the inventory holding cost functions are also linear and have some realistic properties, even if the outsourcing cost functions remain general concave functions. When the inventory holding and outsourcing cost functions are linear, the backlogging case can be solved in O（ T^3 logT） time whether the outsourcing level at each period is bounded by the sum of the demand of that period and backlogging level from previous periods, or only by the demand of that period.

关键词： Dynamic lot sizing problem bounded inventory outsourcing backlogging stockout,dynamic programming

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Multi-Keyframe Guided Points Tracking Method for Enhanced Robotic Surgery

Multi-Keyframe Guided Points Tracking Method for Enhanced Ro...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Li, Xiaojian Li, Tongtong Ma, Xiang Li, Ling Mo, Hangjie Zheng, Jieyu School of Management Hefei University of Technology Hefei China Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei China

ISBN: (纸本)9781665481090

Points tracking provides target guidance for the basic tasks of robotic surgery, such as autonomous cutting, autonomous suturing, and surgical navigation. Existing invivo tracking algorithms mainly consider region-level tracking, making it difficult to achieve pixel-level accuracy. This paper proposes a multi-keyframe guided tracking method (MKTracking) for robotic surgery, which achieves long-term dynamic tracking of any point on endoscopic images. An incremental keyframe pool building block based on time interval and image appearance is proposed, which contains keyframe basic information, tracking patch and tracking points. Besides, an online multi-keyframe query mechanism is designed to efficiently retrieves the three most similar templates from the keyframe pool based on the number of feature matches within the target patch. This mechanism can realize the identification of target moving out and the re-tracking of target reappearance. Points tracking result is obtained by fusing the optical flow results within the target patch across multiple frames. We evaluated MKTracking using ground-truth data, and the results demonstrated that our approach achieved superior tracking performance. © 2024 IEEE.

关键词： Optical flows

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Energy storage resources management:Planning,operation,and business model

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Frontiers of Engineering Management 2022年第3期9卷 373-391页

作者： Kaile ZHOU Zenghui ZHANG Lu LIU Shanlin YANG School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei University of TechnologyHefei 230009China

With the acceleration of supply-side renewable energy penetration rate and the increasingly diversified and complex demand-side loads,how to maintain the stable,reliable,and efficient operation of the power system has become a challenging issue requiring *** of the feasible solutions is deploying the energy storage system(ESS)to integrate with the energy system to stabilize ***,considering the costs and the input/output characteristics of ESS,both theinitial configuration process and the actual operation process require efficient *** study presents a comprehensive reviewof managing ESs from the perspectives of planning,operation,and business *** of all,in terms of planning and configuration,it is investigated from capacity planning,location planning,as well as capacity and location combined *** process is generally the first step in deploying ***,it explores operation management of ESS from the perspectives of state assessment and operation *** so-called state assessment refers to the assessment of three aspects:The state of charge(SOC),the state of health(SOH),and the remaining useful life(RUL).The operation optimization includes ESS operation strategy optimization and joint operation ***,it discusses the business models of *** business models involve ancillary services and load transfer,while emerging business models include electric vehicle(EV)as energy storage and shared energy storage.

关键词： energy storage system energy storage resources management planning configuration operational management business model

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Application of blockchain in the field of intelligent manufacturing:Theoretical basis,realistic plights,and development suggestions

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Frontiers of Engineering Management 2020年第4期7卷 578-591页

作者： Qiang ZHANG Baoyu LIAO Shanlin YANG School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Intelligent Decision-making(Ministry of Education) Hefei University of TechnologyHefei 230009China

Blockchain technology is considered one of the promising technologies of the information technology *** core features of blockchain,such as decentralization,transparency,high security,and tamper-proof nature,bring great convenience for large-scale social cooperation and data *** has a broad application prospect in the field of intelligent *** key issues of this field,such as distributed collaborative production,industrial big data sharing and security,transparent logistics,and supply chain,are naturally consistent with the core characteristics of the blockchain *** study aims to analyze the application of blockchain in the field of intelligent ***,we introduce the basic connotation and applications of ***,we propose the theoretical basis for the application of blockchain in the field of intelligent ***,we point out the realistic plights and provide some suggestions to promote the application of blockchain in the field of intelligent manufacturing.

关键词： blockchain technology intelligent manufacturing networked collaborative manufacturing full lifecycle management manufacturing model innovation

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Photovoltaic Power Forecasting Based on SVM Optimized by Improved ABC 2

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

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2nd International Conference on Environmental Prevention and Pollution Control Technologies, EPPCT 2020

作者： Liu, Lin Lu, Yanyun Li, Shuqin School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei230009 China

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. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Support vector machines

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Industrial False Signal Recognition Based on Deep Learning with Focal Loss

Industrial False Signal Recognition Based on Deep Learning w...

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作者： Xu, Qifa Cheng, Qiliang Jiang, Cuixia Wang, Xiangxiang School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei230009 China

False signals often occur in actual industrial environments. They are however treated as abnormal ones, which will lead to unexpected equipment downtime and production loses. Consider the memory limitations of edge computing, how to recognize them accurately with lightweight models is an important but difficult work. To this end, we develop a novel scheme based on deep learning with focal loss. This scheme first converts original one-dimensional waveform signals into time-frequency graphs through continuous wavelet transform. These graphs are then fed into a convolutional neural network (CNN) for binary classification. Finally, focal loss function is introduced into the CNN model to solve the problem of different types of misclassification costs in recognizing false signals. We verify the effectiveness of this scheme on a real-world application. The results show that our scheme is a high-quality classifier with an accuracy of 98.42%, a Precision of 98.68%, a Recall of 98.18%, and a specificity of 98.68%, which is efficient in recognizing false signals and performs better than several competing models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolutional neural networks

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Short-term power load forecasting based on self-adapting PSO-BP neural network model

Short-term power load forecasting based on self-adapting PSO...

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4th International Conference on Computational and Information Sciences, ICCIS 2012

作者： He, Yaoyao Xu, Qifa School of Management Hefei University of Technology Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei 230009 China

ISBN: (纸本)9780769547893

To resolve the problem of short-term power load forecasting, we propose a self-adapting particle swarm optimization (PSO) algorithm to optimize the error back propagation (BP) neural network model. The proposed model is called PSO-BP model which employs PSO to adjust control parameters of BP neural network. In order to verify the performance of PSO-BP, the practical datum of a city in China are selected in the experiments. Simulation results show that our approach outperforms simple BP neural network. © 2012 IEEE.

关键词： Neural network models

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Mining organizational structure from workflow logs

Mining organizational structure from workflow logs

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2011 International Conference on e-Education, Entertainment and e-Management, ICEEE 2011

作者： Ni, Zhiwei Wang, Sha Li, Huaiying School of Management Hefei University of Technology Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei 230009 China

ISBN: (纸本)9781457713811

Workflow mining is a concept in early era, it analyzes the workflow log in the control flow dimensions, to mining the actual process model, but ignores relationships among executors in workflow, hence it fails to effectively excavate the workflow log to find the implicit structure. In this paper, the organizational dimensions of workflow log will be the main focuses to be researched. The paper introduces executor similarity metrics and grid clustering to demonstrate the methods of the organizational structure mining based on executor similarity and organization mining based on grid clustering. Both of them are effective to extract the actual organizational structure from the workflow logs. © 2011 IEEE.

关键词： grid clustering organizational structure workflow mining

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