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SSRN 2024年

作者： Shao, Zhen Han, Yating Fu, Chao Zha, Jianrui Yang, Shanlin School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Anhui Hefei230009 China Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance Hefei University of Technology Ministry of Education Hefei230009 China Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies Hefei230009 China

Probabilistic electricity price forecasting (EPF) is paramount for stakeholder scheduling and trading in deregulated energy markets. However, during the process of establishing a probability prediction model, the consequential aleatoric and epistemic uncertainties are indistinguishable. Moreover, identifying epistemic uncertainty rather than aleatoric uncertainty is significant for conducting credible probabilistic EPF in cases with expected and unexpected fluctuations. This article proposes a hybrid approach under a Bayesian probability framework for performing reliable and accurate probabilistic forecasting. Specifically, it applies Bayesian deep learning model to convey the latent probability distribution of electricity prices, which represents the desirable epistemic uncertainty and inevitable aleatoric uncertainty. The embedded architecture employs a multi-head attention mechanism (MHAM) to allocate previous hidden states of long short-term memory (LSTM) cells, detecting both the local and global price patterns simultaneously. Considering the forecasting bias arising from aleatoric uncertainty in the process of establishing Bayesian networks, a new Wasserstein distance-based multi-distribution fusion mechanism driven by evidence theory is proposed and employed to identify and mitigate the aleatoric uncertainty of credible probabilistic EPF problems. The effectiveness of the proposed approach is evaluated on two real-world electricity price datasets and compared with twelve state-of-the-art models. © 2024, The Authors. All rights reserved.

关键词： Bayesian networks

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Face Tracking Strategy of 7-DOF Manipulator Using optimization Algorithm Based on Velocity Analysis

Face Tracking Strategy of 7-DOF Manipulator Using Optimizati...

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IEEE International Conference on Robotics and Biomimetics

作者： Shuai Zhang Cancan Zhao Xian He Bo Ouyang Shanlin Yang The School of Management Hefei University of Technology Hefei China The Key Laboratory of Process Optimization and Intelligent Decision-Making(Ministry of Education) Hefei University of Technology Hefei China

ISBN: (纸本)9781665481106

Patients' facial expressions can reflect their condition, but expressions cannot be captured like ECG or EEG monitor. Long-term monitoring will increase the workload of nurses. To tackle this issue, we develop a face tracking strategy using a 7-DOF robot manipulator with a camera mounted on the end-effector. First, we analyze the relationship between the manipulator's workspace and optimal tracking pose and design an optimization function to initialize the head position. By comparing the speed of the head and manipulator, knowledge of the maximum tracking limit of the head and the manipulator in the tracking process is given. Moreover, a configuration-based optimization algorithm is proposed to minimize the error with theoretical optimal pose by converting radian to arc length. We calculate the optimal configuration of the camera with the feedback of the head configuration while minimizing the difference between theoretical optimal pose. Simulation experimental results verified that the proposed face tracking strategy outperforms the visual servoing control strategy only based on the pseudo-inverse of the Jacobian matrix.

关键词： Jacobian matrices Tracking Robot kinematics Manipulators Cameras Visual servoing Trajectory

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Manipulating Constrained Soft Tissue while Avoiding Obstacles using Reinforcement Learning with Self-Attention

Manipulating Constrained Soft Tissue while Avoiding Obstacle...

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IEEE International Conference on Robotics and Biomimetics

作者： Xian He Shuai Zhang Shanlin Yang Bo Ouyang The School of Management Hefei University of Technology Hefei China The Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education) Hefei University of Technology Hefei China

ISBN: (纸本)9781665481106

The complexity of dynamics raises challenges in deformable object manipulation, particularly the soft tissue shape control in in vivo environment. Previous studies assume the soft tissue is in an obstacle-free space, and the constraints are constant. To go one step further, a Soft Actor-Critic (SAC) algorithm is presented to manipulate the soft tissue under external disturbances while avoiding obstacles. K-Means is applied to reduce the dimension of the state space. Furthermore, self-attention is introduced to focus on the external forces and the constraints. Experiment results show that the agent can shape the soft tissue into the target deformation with the proposed approach under unknown external force, where the agent can automatically increase attention to the external force. The agent can find an obstacle-free path while manipulating the soft tissue. Compared with the SAC algorithm, the proposed approach with self-attention requires less training time, and the critic network is more stable.

关键词： Training Shape control Shape Biological tissues Force Surgery Reinforcement learning

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A Multimodal Data-driven Framework for Anxiety Screening

arXiv

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arXiv 2023年

作者： Mo, Haimiao Ding, Shuai Hui, Siu Cheung 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 School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

Early screening for anxiety and appropriate interventions are essential to reduce the incidence of self-harm and suicide in patients. Due to limited medical resources, traditional methods that overly rely on physician expertise and specialized equipment cannot simultaneously meet the needs for high accuracy and model interpretability. Multimodal data can provide more objective evidence for anxiety screening to improve the accuracy of models. The large amount of noise in multimodal data and the unbalanced nature of the data make the model prone to overfitting. However, it is a non-differentiable problem when high-dimensional and multimodal feature combinations are used as model inputs and incorporated into model training. This causes existing anxiety screening methods based on machine learning and deep learning to be inapplicable. Therefore, we propose a multimodal data-driven anxiety screening framework, namely MMD-AS, and conduct experiments on the collected health data of over 200 seafarers by smartphones. The proposed framework’s feature extraction, dimension reduction, feature selection, and anxiety inference are jointly trained to improve the model’s performance. In the feature selection step, a feature selection method based on the Improved Fireworks Algorithm is used to solve the non-differentiable problem of feature combination to remove redundant features and search for the ideal feature subset. The experimental results show that our framework outperforms the comparison methods. © 2023, CC BY-NC-SA.

关键词： Feature Selection

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Understanding Information Sensitivity Perceptions and its Impact on Information Privacy Concerns in E-Commerce Services: Insights from China

SSRN

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SSRN 2023年

作者： Tao, Shouzheng Liu, Yezheng Sun, Chunhua School of Management Hefei University of Technology Anhui Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Anhui Hefei230009 China Key Laboratory of Philosophy and Social Sciences for Cyberspace Behaviour and Management Anhui Hefei230009 China

Although research topics related to information privacy in e-commerce services have been extensively studied, we still lack knowledge about consumers' perceived information sensitivity to personal information disclosure at the information type level and its effect on information privacy concerns. This study focused on common personal information types required by e-commerce services and investigated 625 Chinese consumers based on an online questionnaire about their information sensitivity to disclosing these personal information types. Rooted in the literature on information sensitivity and privacy concerns, we explored the impact of individual and situational factors on information sensitivity and the impact of information sensitivity of different personal information types on e-commerce privacy concerns. Our research identified which personal information types are considered insensitive and which are mediumsensitive or high-sensitive in e-commerce services and found a consensus among consumers on which personal information types are more sensitive. At the individual level, privacy experience, risk propensity, and gender affect information sensitivity. At the situational level, website social presence, website familiarity, and perceived privacy control affect information sensitivity. Perceived information sensitivity of medium-sensitive and high-sensitive personal information types affect e-commerce privacy concerns. Our research deepens the understanding of information sensitivity and privacy concerns and provides practical insights for privacy policymakers and e-commerce service providers. © 2023, The Authors. All rights reserved.

关键词： Websites

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Regression model for estimation of attribute reliability

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Journal of Control and decision 2021年第2期8卷 201-212页

作者： Guangyan Lu Wenjun Chang Department of Operation Management CRRC Qishuyan Institute Co.LtdChangzhouPeople’s Republic of China School of Management Hefei University of TechnologyHefeiBox 270HefeiAnhui 230009People’s Republic of China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefeiAnhui 230009People’s Republic of China Ministry of Education Engineering Research Center for Intelligent Decision Making&Information System Technologies Hefei 230009People’s Republic of China

In this paper,a regression model is developed to estimate attribute reliability in the evidential reasoning(ER)*** analysing the difference between attribute weight and attribute reliability,a general qualitative definition of attribute reliability is *** reliability of an attribute is quantitatively measured in consistence with the qualitative definition in the context of the ER approach.A regression model is then constructed to generate attribute reliabilities by minimising the maximum differences between the real value of attribute reliability and its *** the post-optimal solution space of attribute reliabilities,an optimisation model is constructed to determine the expected utilities of each alternative in order to generate solutions to multiple attribute decision analysis *** place selection problem in Qingyang County of Chizhou in Anhui province of China is analysed using the proposed regression model to demonstrate its detailed implementation process,validity and applicability.

关键词： Multiple attribute decision analysis attribute reliability regression model evidential reasoning rule evidential reasoning approach

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A Lite Fireworks Algorithm for optimization

arXiv

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arXiv 2023年

作者： Mo, Haimiao Zeng, Min 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 College of Computer Science Guangdong University of Science and Technology Guangdong Province Dongguan China

The fireworks algorithm is an optimization algorithm for simulating the explosion phenomenon of fireworks. Because of its fast convergence and high precision, it is widely used in pattern recognition, optimal scheduling, and other fields. However, most of the existing research work on the fireworks algorithm is improved based on its defects, and little consideration is given to reducing the number of parameters of the fireworks algorithm. The original fireworks algorithm has too many parameters, which increases the cost of algorithm adjustment and is not conducive to engineering applications. In addition, in the fireworks population, the unselected individuals are discarded, thus causing a waste of their location information. To reduce the number of parameters of the original Fireworks Algorithm and make full use of the location information of discarded individuals, we propose a simplified version of the Fireworks Algorithm. It reduces the number of algorithm parameters by redesigning the explosion operator of the fireworks algorithm and constructs an adaptive explosion radius by using the historical optimal information to balance the local mining and global exploration capabilities. The comparative experimental results of function optimization show that the overall performance of our proposed LFWA is better than that of comparative algorithms, such as the fireworks algorithm, particle swarm algorithm, and bat algorithm. © 2023, CC BY.

关键词： Scattering parameters

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An intuitionistic fuzzy similarity measurement method considering orientation 8

An intuitionistic fuzzy similarity measurement method consid...

引用

8th International Symposium on Project Management, ISPM 2020

作者： Pei, Feng He, Yuwei Yan, An Liu, Lin School of Management Hefei University of Technology China Key Laboratory of Process Optimization and Intelligent Decision Making Ministry of Education China

ISBN: (纸本)9781921712722

Similarity of intuitionistic fuzzy sets (IFSs) is an important tool for determining the similarity degree between two objects, which is often used in the fields of pattern recognition, medical diagnosis and so on. Although many intuitionistic fuzzy similarity measurement (IFSM) methods have been proposed, those methods ignore the effect of the hesitancy part's orientation on similarity degree, which causes partial information loss and reduces the reasoning accuracy. In this paper, an improved IFSM method considering the orientation of hesitancy part on membership part, non-membership part and hesitancy part, is established by introducing the protection degrees of membership, non-membership and hesitancy. Finally, this method is applied to pattern recognition problems to demonstrate the effectiveness and applicability of the proposed method. © 8th International Symposium on Project Management, ISPM 2020. All rights reserved.

关键词： Pattern recognition

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The Pricing Strategy of Software: Vulnerability and Patch 20

The Pricing Strategy of Software: Vulnerability and Patch

引用

4th International Conference on Computer Science and Application Engineering, CSAE 2020

作者： Yang, Wujuan Qian, Xiaofei School of Management and Key Laboratory of Process Optimization and Intelligent Decision-making of the Ministry of Education Hefei University of Technology Hefei China

ISBN: (纸本)9781450377720

The ubiquity of vulnerability in software products poses a serious threat to network security and user system. Patching for the software is a common tool to ease the security issue. Whereas, not all users will choose to patch due to the consideration on compatibility and inconvenience. Thus, it is significant to induce users to patch for the software. Based on the background of this practical problem, this paper proposes two models (a benchmark model and a price discount model) to analyze the user's buying and patching behavior, the pricing strategy of the software vendor, and the vendor's benefits. By comparing the results of the benchmark model and the price discount model, we find that the price discount policy will result in a higher group security level and more benefits for the vendor. © 2020 ACM.

关键词： Game theory

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Optimal Operation Of Battery Energy Storage System In Industrial Park

Optimal Operation Of Battery Energy Storage System In Indust...

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

作者： Kaile Zhou Zenghui Zhang Xinhui Lu Key Laboratory of Process Optimization and Intelligent Decision-making Schoolof Management Hefei University of Technology Hefei China

ISBN: (纸本)9781665434263

An industrial park containing distributed generations (DGs) can be seen as a microgrid. Due to the uncertainty and intermittency of the output of DGs, it is necessary to add battery energy storage system (BESS) in industrial parks. The battery state of health (SOH) is an important indicator of battery life. It is necessary to fully consider the battery SOH during the energy optimization of industrial parks. In this work, a two-stage model suitable for charge and discharge optimization of BESSs in industrial park microgrids is proposed. The first stage of the model is a charge and discharge scheduling of a BESS considering the SOH. This stage mainly schedules the charge and discharge time and the total amount of time. The second stage of the model is employed to further determine the charge and discharge allocation of all battery packs to achieve BESS life prolongation. The experimental results show that the introduction of SOH makes the scheduling results more realistic. Also, it balances the changes in the SOHs of all battery packs.

关键词： Schedules Job shop scheduling Uncertainty Rain Microgrids System integration Discharges (electric)

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