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E-Commerce and Internet Technology (ECIT), International Conference on

作者： Jianmin He Tingting Liu Yuanchun Jiang Ying Li Hao Wu Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei China School of Management Hefei University of Technology Hefei China

ISBN: (数字)9781728159027

ISBN: (纸本)9781728159034

In this paper, we explore the method of measuring answerer service influence on Q & A community in order to provide decision support for communities to obtain paid consultation questioners and high service influence answerers. From the social capital measuring angle, this paper selects three-dimensional indicators which contain unpaid services, paid services and services quality to measure answerer service influence on Q & A community. Accordingly, we construct a social capital measurement model method for answerer service influence and demonstrate its practical effectiveness. This method can help communities discover high service influence answerers, and formulate service strategies that motivate answerers and questioners to improve the overall service efficiency and effectiveness of the community. The numerical study on the dataset from *** indicates that the proposed method can obtain reasonable measurement results.

关键词： Q & A community paid consulting services service influence social capital measurement method for service influence Social Capital Communities Quality factor Legal Services decision making support Quality of service Dataset

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Research on the Operational Efficiency of Subscription Accounts

Research on the Operational Efficiency of Subscription Accou...

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E-Commerce and Internet Technology (ECIT), International Conference on

作者： Jianmin He Hao Wu Tingting Liu Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei China School of Management Hefei University of Technology Hefei China

ISBN: (数字)9781728159027

ISBN: (纸本)9781728159034

The operation and profit of the subscription account is an important guarantee for maintaining its own high-quality development. It constructs an operation efficiency evaluation index system, with customer acquisition input and profit acquisition input as input indicators, and customer acquisition output and profit acquisition output as output indicators. On this basis, the DEA-BCC model was used to evaluate the operational efficiency of 28 subscription accounts. Based on the analysis results, this paper puts forward the improvement measures for non-DEA effective subscription accounts. Finally, this article uses Tobit regression to explore the influencing factors of operational efficiency. The results show that only 14 subscription accounts are DEA efficiency. The quality of average non-original articles has a negative impact on operational efficiency, and the quality of average original articles and the number of daily non-original articles have a positive impact on operational efficiency. Therefore, subscription accounts should pay attention to the quality of original articles and balance the quantity and quality of articles in operation management.

关键词： subscription accounts operational efficiency DEA Tobit Subscriptions DEAS operating efficiency

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Independent or Social Driven decision? A Counterfactual Refinement Strategy for Graph-Based Social Recommendation

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ACM Transactions on Information Systems 2025年第3期43卷

作者： Li, Dongyang Sun, Jianshan Gao, Chongming Feng, Fuli Yuan, Kun School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China University of Science and Technology of China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei China University of Science and Technology of China Hefei China Hefei University of Technology Hefei China Key Laboratory of Philosophy and Social Sciences for Cyberspace Behaviour and Management Hefei China

Social recommendation models have traditionally relied on social homophily to enhance user preference prediction by incorporating information from socially connected friends. However, this approach neglects the diverse nature of social relationships. Some individuals with independent personalities often prioritize their own interests over friends’ advice when making purchase decisions. Conversely, those who seek advice from others are more susceptible to social influence. Moreover, the existing methods tend to overlook redundant and noisy social relationships within the network, hindering their ability to achieve accurate recommendations. In response, this article proposes a novel counterfactual method to understand the causal factors driving purchase behaviors, thereby identifying the influence of users’ friends on their purchase decisions. By answering counterfactual questions about the influence of a friend’s purchase behavior on the user’s choices, we develop a causal model to represent social influence in the network. Our proposed refinement strategy, grounded in causal inference, generates counterfactual purchase behavior and guides the refinement of the social graph. Moreover, we present tailored graph refinement methods at various levels, ensuring fine-grained improvements. Experimental results on benchmark data demonstrate that the application of our strategy to different social recommendation models significantly enhances their predictive performance. The source code has been made available on https://***/LDY911/CFRSSR-Code. © 2025 Copyright held by the owner/author(s).

关键词： Sociology

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The Influencing Factors of sCER Price Dynamics Under the Clean Development Mechanism: Theory and Econometric Analysis

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Journal of Systems Science & Complexity 2018年第5期31卷 1244-1272页

作者： ZHANG Chen WU Yaqi YANG Yu School of Management Hefei University of Technology Hefei 230009 China Key Laboratory of Process Optimization & Intelligent Decision Making of Ministry of Education Hefei 230009 China

In order to explore the factors and their complex mechanism affecting the price dynamics under the clean development mechanism （CDM）, this article employs the secondary Certified Emission Reduction （sCER） carbon price as the study object, and analyzes its influencing factors from aspects of the international carbon-reduction policies, macroeconomic fluctuations, energy and similar carbon products prices. The innovation of this paper lies in： Introducing necessary factor （the developing countries pricing power） and the application of several international representative indicators to un- derline the ＂world＂ nature of CDM; utilizing different econometric models to obtain noteworthy and more robust results. The authors test the theoretical findings with multiple stationary time series from the launch of CDM to present （2008-2016）. The results reveal that sCER price fluctuation shows the characteristic of asymmetry and substantial persistence. There is a strong statistically significant relationship between macroeconomic conditions, coal and oil prices, with the price of sCER. The authors discover that the pricing power of developing countries indeed has a clear but small impact on the sCER price changes, whereas the price elasticity of supply under CDM is so weak. The interaction between EU emission allowances （EUAs） and sCER presents a shift from dependency to substitution.

关键词： Clean development mechanism econometric analysis influencing factors sCER carbonprice.

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Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm

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Journal of Systems Science and Information 2018年第5期9卷 399-420页

作者： Ye ZHANG Xiaoxuan HU Waiming ZHU Peng JIN School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling *** on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the *** results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.

关键词： Earth observation satellite integrated scheduling quantum genetic algorithm

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Collaborative Three-Tier Architecture Non-contact Respiratory Rate Monitoring using Target Tracking and False Peaks Eliminating Algorithms

arXiv

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arXiv 2020年

作者： Mo, Haimiao Ding, Shuai Yang, Shanlin Vasilakos, Athanasios V. Zheng, Xi The School of Management Hefei University of Technology Anhui Hefei23009 China The Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education China The National Engineering Laboratory of Big Data Distribution and Exchange Technologies China Grimstad Norway The College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China The School of Computing Macquarie University Sydney Australia

Monitoring the respiratory rate is crucial for helping us identify respiratory disorders. Devices for conventional respiratory monitoring are inconvenient and scarcely available. Recent research has demonstrated the ability of non-contact technologies, such as photoplethysmography and infrared thermography, to gather respiratory signals from the face and monitor breathing. However, the current non-contact respiratory monitoring techniques have poor accuracy because they are sensitive to environmental influences like lighting and motion artifacts. Furthermore, frequent contact between users and the cloud in real-world medical application settings might cause service request delays and potentially the loss of personal data. We proposed a non-contact respiratory rate monitoring system with a cooperative three-layer design to increase the precision of respiratory monitoring and decrease data transmission latency. To reduce data transmission and network latency, our three-tier architecture layer-by-layer decomposes the computing tasks of respiration monitoring. Moreover, we improved the accuracy of respiratory monitoring by designing a target tracking algorithm and an algorithm for eliminating false peaks to extract high-quality respiratory signals. By gathering the data and choosing several regions of interest on the face, we were able to extract the respiration signal and investigate how different regions affected the monitoring of respiration. The results of the experiment indicate that when the nasal region is used to extract the respiratory signal, it performs experimentally best. Our approach performs better than rival approaches while transferring fewer data. © 2020, CC BY.

关键词： Edge computing

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Can constraint energy-saving policy facilitate industrial green production performance in China? 3

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

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3rd International Conference on Advances in Energy and Environment Research, ICAEER 2018

作者： Yao, Yue Jiao, Jianling Han, Xiaofei School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Anhui230009 China

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. © The Authors, published by EDP Sciences, 2018.

关键词： Energy conservation

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Photovoltaic Power Forecasting Based on SVM Optimized by Improved ABC

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IOP Conference Series: Earth and Environmental Science 2020年第5期474卷

作者： Lin Liu Yanyun Lu Shuqin Li 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

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.

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Forecasting of electricity price subsidy based on installed cost of distributed photovoltaic in China

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Energy Procedia 2019年 158卷 3393-3398页

作者： Changhui Yang Rui Yao Kaile Zhou School of Management Hefei University of Technology Baohe District Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making ( Ministry of Education) Hefei University of Technology Baohe District Hefei 230009 China Department of Public Policy City University of Hong Kong Kowloon Hong Kong

In China, the installed cost of distributed photovoltaic (DPV) is declining rapidly. However, the level of subsidy per kWh for DPV is adjusted less frequently by the Chinese government. This paper proposed a linkage model to forecast subsidy per kWh of DPV based on net present value (NPV) method. The results show that the increase of subsidy duration, internal consumption proportion and sunshine hours will reduce subsidy level. Therefore, it is suggested that the Chinese government should take varied and targeted measures, such as reducing different subsidies for new DPV users who install DPV in different years, choosing a longer subsidy duration and setting different subsidy levels in different regions. These varied and targeted measures are beneficial to both government and users, because they can reduce the annual financial burden for the government and the surcharges of electricity purchase for users.

关键词： Distributed photovoltaic subsidy NPV method China

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Optimal search for moving targets with sensing capabilities using multiple UAVs

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Journal of Systems Engineering and Electronics 2017年第3期28卷 526-535页

作者： Xiaoxuan Hu Yanhong Liu Guoqiang Wang School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefei 230009China

This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.

关键词： unmanned air vehicle (UAV) moving target search model predictive control path planning hybrid particle swarm optimization

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