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Modeling and simulation of competition-cooperation and neutrality relations in SDN enterprises

Journal of Chemical and Pharmaceutical Research 2014年第5期6卷 1714-1724页

作者： Tai, Deyi Xu, Fuyuan Hu, Wei School of Management University of Shanghai for Science and Technology China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University China

Besides competition and cooperation, there also have neutrality relations, which is noncompetition and noncooperation, exists in Supply and Demand Network of Enterprises with Multi-function and Opening Characteristics (SDN). To reveal the evolution of cooperation, competition and neutrality relations among enterprises in SDN, an evolutionary model on node relations in SDN was build to solve the problem of real cooperative strategy selection. Base on evolutionary game theory, an enterprises relations evolutionary game model was established, and analyzed with numerical simulations in MATLAB. The results show that transferable and non-transferable incomes determined the choice of cooperation, competition and neutrality strategy. Opportunistic behavior and malicious competition exited in SDN, which reduced the overall revenue and destroyed the stability of SDN. Enhanced supervision and punishment in SDN will improve enterprises’ relations from neutrality to cooperation. © 2014, Journal of Chemical and Pharmaceutical Research. All right reserved.

关键词： Competition

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Relations' evolutionary in Supply and Demand Network of Enterprises with Multi-function and Opening Characteristics

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Biotechnology: An Indian Journal 2014年第12期10卷 6268-6279页

作者： Tai, Deyi Xu, Fuyuan Hu, Wei University of Shanghai for Science and Technology School of Management China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University China

There are three relations exist in Supply and Demand Network of Enterprises with Multifunction and Opening Characteristics (SDN) that are competition, cooperation and neutrality relations, which's evolutionary will effects the stability of SDN. To reveal the evolution process and interactive of the three relations among enterprises of SDN, an evolutionary game model in SDN was build to solve the problem of real cooperative strategy selection. The model of enterprises relations evolutionary was established base on evolutionary game theory, and analyzed with numerical simulations in MATLAB. The research shows that the strategy selection of cooperation, competition and neutrality in SDN were mainly determined by transferable and non-transferable incomes. Enhancing supervision and punishment to opportunistic behavior and malicious competition in SDN, will improve enterprises' relations from neutrality to cooperation. © Trade Science Inc.

关键词： Competition

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Modular design of adaptive controller for strict-feedback stochastic nonlinear systems with uncertain Wiener noise

Modular design of adaptive controller for strict-feedback st...

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International Conference on control, Automation, Robotics and vision (ICARCV)

作者： Jun Wang Tao Cai Yu Kang Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University Hefei China Department of Automation University of Science and Technology Hefei China

In this paper, a modular approach is proposed for a class of strict-feedback stochastic nonlinear systems with uncertain Wiener noises and constant unknown parameters. Both the adaptive Backstepping procedure and input-to-state stable(ISS) controller of global stabilization in probability are designed to guarantee that the system states are bounded and has adaptive stabilization while the covariance of Wiener noises is uncertain. According to Swapping technique, we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed.

关键词： Programmable control Adaptive control Nonlinear control systems control systems Stochastic systems Stochastic resonance Nonlinear systems Backstepping Filters Parametric statistics

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Modular design of adaptive tracking for a class of stochastic nonlinear systems

Modular design of adaptive tracking for a class of stochasti...

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International Conference on control, Automation, Robotics and vision (ICARCV)

In this paper, a modular design approach of adaptive tracking is proposed for parameter-strict-feedback stochastic nonlinear systems with standard Wiener noises and constant unknown parameters. Both the adaptive backstepping procedure and input-to-state stable (ISS) controller of global stabilization in probability are designed separately to ensure the output-feedback tracking can be achieved. According to swapping technique, we develop two filters and convert dynamic parametric models into a static one to which the gradient update law is chosen. The transient performance shows the tracking error is bounded.

关键词： Stochastic systems Nonlinear systems Adaptive control control systems Nonlinear control systems Programmable control Automatic control Robust control Error correction Sliding mode control

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Green Manufacturing Based on SDN

Green Manufacturing Based on SDN

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The 4th International Conference on Environmental technology and Knowledge Transfer

作者： TAI Deyi XU Fuyuan School of Management University of Shanghai for Science & Technology Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University

To realize an energy-saving and resource-sharing green manufacturing,a new cooperation model of green manufacturing based on supply and demand network of enterprises with multifunction and opening characteristics（SDN） was *** essential attribute of green manufacturing was *** with dynamic,diversity,fully open and inclusive cooperation concepts was introduced as a new paradigm of manufacturing *** model of green manufacturing cooperation based on SDN was proposed,from three-dimension of lever,function and ***,Green manufacturing for automobile enterprises based on SDN was discussed.

关键词： green manufacturing SDN manufacturing cooperation energy saving

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Lycopene Content Prediction Based on Support Vector machine with Particle Swarm Optimization

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Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural machinery 2012年第4期43卷 143-147+155页

作者： Liu, Wei Wang, Jianping Liu, Changhong Ying, Tiejin School of Electrical Engineering and Automation Hefei University of Technology Hefei 230009 China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University Hefei 230601 China School of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310058 China

Color-difference was presented to assess the lycopene content conveniently and non-destructively. Due to excessive affecting factors and strong correlation among the parameters in the process, the support vector machine (SVM) was used to set up the predict model. The selection and simplification of the feature parameters was discussed. A compound optimal objective function based on Akaike information criterion (AIC) was constructed. The particle swarm optimization (PSO) algorithm was used to search the optimal value of the objective function and enhance the efficiency. The predictable method had good performance in assessing the lycopene content of different maturity stages.

关键词： Support vector machines

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Data protection and provenance in cloud of things environment: Research challenges

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International Journal of Information and Computer Security 2020年第4期12卷 416-435页

作者： Wang, Chundong Yang, Lei Guo, Hao Wan, Fujin Key Laboratory of Computer Vision and System Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Ministry of Education Tianjin University of Technology Tianjin China Global Energy Internet Research Institute Beijing University of Technology Tianjin China Department of College of Computer and Control Engineering Nankai University Tianjin China

Internet of things are increasingly being deployed over the cloud (also referred to as cloud of things) to provide a broader range of services. However, there are serious challenges of CoT in the data protection and security provenance. This paper proposes a data privacy protection and provenance model (DPSPM) based on CoT. It can protect the privacy data of the users and trace the source of leaked data. In detail, security encryption and watermarking algorithms are proposed. Meanwhile, we use the improved k-anonymity data masking algorithm and pseudo-row watermarking algorithm in this scheme. Those algorithms can carry out security control over the whole process of data publishing, especially in data encryption, data masking and provenance verification. Finally, the experimental results show that our scheme has good efficiency. It is proved that the data masking time is proportional to the parameters k and L, the results also show good robustness to the common database watermarking attacks. © 2020 Inderscience Enterprises Ltd.

关键词： Data privacy

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DeepGCN based on variable multi‐graph and multimodal data for ASD diagnosis

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CAAI Transactions on intelligence technology 2024年第4期9卷 879-893页

作者： Shuaiqi Liu Siqi Wang Chaolei Sun Bing Li Shuihua Wang Fei Li College of Electronic and Information Engineering Hebei UniversityBaodingChina Machine Vision Technology Innovation Center of Hebei Province BaodingChina The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science and Technology Henan Polytechnic UniversityJiaozuoChina

Diagnosing individuals with autism spectrum disorder(ASD)accurately faces great chal-lenges in clinical practice,primarily due to the data's high heterogeneity and limited sample *** tackle this issue,the authors constructed a deep graph convolutional network(GCN)based on variable multi‐graph and multimodal data(VMM‐DGCN)for ASD ***,the functional connectivity matrix was constructed to extract primary ***,the authors constructed a variable multi‐graph construction strategy to capture the multi‐scale feature representations of each subject by utilising convolutional filters with varying kernel ***,the authors brought the non‐imaging in-formation into the feature representation at each scale and constructed multiple population graphs based on multimodal data by fully considering the correlation between *** extracting the deeper features of population graphs using the deep GCN(DeepGCN),the authors fused the node features of multiple subgraphs to perform node classification tasks for typical control and ASD *** proposed algorithm was evaluated on the Autism Brain Imaging Data Exchange I(ABIDE I)dataset,achieving an accuracy of 91.62%and an area under the curve value of 95.74%.These results demon-strated its outstanding performance compared to other ASD diagnostic algorithms.

关键词： machine learning medical image processing medical signal processing

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Lithology Classification Based on Set-Valued Identification Method

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Journal of Systems Science & Complexity 2022年第5期35卷 1637-1652页

作者： LI Jing WU Lifang LU Wenjun WANG Ting KANG Yu FENG Deyong ZHOU Hansheng Department of Automation University of Science and Technology of ChinaHefei 230027China Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100190China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China Shengli Geophysical Research Institute SINOPEC GroupDongying 257022China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China

Lithology classification using well logs plays a key role in reservoir *** paper studies the problem of lithology identification based on the set-valued method(SV),which uses the SV model to establish the relation between logging data and lithologic types at a certain depth *** particular,the system model is built on the assumption that the noise between logging data and lithologic types is normally distributed,and then the system parameters are estimated by SV method based on the existing identification *** logging data of Shengli Oilfield in Jiyang Depression are used to verify the effectiveness of SV *** results indicate that the SV model classifies lithology more accurately than the Logistic Regression model(LR)and more stably than uninterpretable models on imbalanced ***,the Macro-F1 of the SV models(i.e.,SV(3),SV(5),and SV(7))are higher than 85%,where the sandstone samples account for only 22%.In addition,the SV(7)lithology identification system achieves the best stability,which is of great practical significance to reservoir exploration.

关键词： DT lithology classification LR RF set-valued model SVM

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Cooperative Classification and Rationalization for Graph Generalization 24

Cooperative Classification and Rationalization for Graph Gen...

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33rd ACM Web Conference, WWW 2024

作者： Yue, Linan Liu, Qi Liu, Ye Gao, Weibo Yao, Fangzhou Li, Wenfeng Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of China State Key Laboratory of Cognitive Intelligence University of Science and Technology of China Hefei China Douyin Vision Co. Ltd Beijing China

ISBN: (纸本)9798400701719

Graph Neural Networks (GNNs) have achieved impressive results in graph classification tasks, but they struggle to generalize effectively when faced with out-of-distribution (OOD) data. Several approaches have been proposed to address this problem. Among them, one solution is to diversify training distributions in vanilla classification by modifying the data environment, yet accessing the environment information is complex. Besides, another promising approach involves rationalization, extracting invariant rationales for predictions. However, extracting rationales is difficult due to limited learning signals, resulting in less accurate rationales and diminished predictions. To address these challenges, in this paper, we propose a Cooperative Classification and Rationalization (C2R) method, consisting of theclassification and therationalization module. Specifically, we first assume that multiple environments are available in theclassification module. Then, we introduce diverse training distributions using an environment-conditional generative network, enabling robust graph representations. Meanwhile, therationalization module employs a separator to identify relevant rationale subgraphs while the remaining non-rationale subgraphs are de-correlated with labels. Next, we align graph representations from theclassification module with rationale subgraph representations using the knowledge distillation methods, enhancing the learning signal for rationales. Finally, we infer multiple environments by gathering non-rationale representations and incorporate them into theclassification module for cooperative learning. Extensive experimental results on both benchmarks and synthetic datasets demonstrate the effectiveness of C2R. Code is available at https://***/yuelinan/Codes-of-C2R. © 2024 ACM.

关键词： Classification (of information)

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