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Preference prediction analysis based on graph model for environmental governance conflict

MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第6期19卷 6141-6156页

作者： Zhao, Jinshuai Yang, Baohua Jiangsu Normal Univ Sch Comp Sci & Technol 101 Shanghai Rd Xuzhou 221116 Jiangsu Peoples R China Jiangsu Normal Univ Sch Business 101 Shanghai Rd Xuzhou 221116 Jiangsu Peoples R China

A mathematical model for decision maker's preference prediction in environmental governance conflict is established based on the graph model for conflict resolution. The rapid economic development in many countries, over the past decades, has caused serious environmental pollution. Sewage companies are the main source of contamination since they are always wavering on the issue of environmental governance because of their profit-seeking nature. Environmental management departments cannot grasp the offending company preferences accurately. The problem of how to obtain decision maker's preference in environmental governance conflict is studied in this paper. The mathematical model established in this paper can obtain a preference set of one decision maker on the promise that the ideal conflict outcome and preference of the other decision makers are known. Then, preference value distribution information entropy is introduced to mine the preference information contained in the preference set, which means that it is possible to get the preference information of conflict opponent at their own ideal conflict outcome. All of these preference sets provide the possibility to choose the appropriate coping strategies and lead the conflict to the direction that some decision makers want. Finally, the effectiveness and superiority of the preference prediction analysis method is verified through a case study of "Chromium Pollution in Qujing County" which took place in China. The preference prediction analysis method in this paper can provide decision making support for the decision makers in environmental governance from strategic level.

关键词： environmental governance preference prediction environmental protection decision making graph model conflict analysis environmental pollution

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Video fingerprinting based on graph model

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MULTIMEDIA TOOLS AND APPLICATIONS 2014年第2期69卷 429-442页

作者： Nie, Xiushan Sun, Jiande Xing, Zhihui Liu, Xiaocui Shandong Univ Finance & Econ Sch Comp Sci & Technol Jinan 250014 Peoples R China Shandong Univ Sch Informat Sci & Engn Jinan 250100 Peoples R China

A robust video fingerprinting based on graph model is proposed in this paper, where two graph models are constructed for key frames selection and foreground extraction, respectively. First, the video is represented as a complete undirected graph and a binary tree is formed using normalized cut algorithm to select key frames. Then, the pixels of each key frame are modeled as a Markov Random Field and another graph model is formed to extract foreground by graph cut. Finally, the fourth-order cumulant of foreground is computed to generate video fingerprints. Experimental results show that the proposed algorithm has good robustness and discrimination.

关键词： Video fingerprinting Copy detection graph model Binary tree Foreground

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A graph model based feature set selection from short texts with application to document novelty detection

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INTELLIGENT DATA ANALYSIS 2017年第5期21卷 1117-1139页

作者： Rayan, Novino Nirmal Arul Sohn, Kyung-Ah Chung, Tae-Sun Ajou Univ Dept Comp Engn Suwon 16499 South Korea

Document novelty detection is a concept learning problem wherein the system gains its knowledge only from the positive documents under a concept and with that limited knowledge it attempts to detect the negative cases. This work focuses on learning author style as a concept from the given set of documents, particularly emails. Since author attribution for shorter texts such as emails is more complex compared to larger documents, the techniques originally used for the large documents prove inefficient for short texts. To address this shortcoming of existing algorithms in detecting aberration in author style, we have proposed a graph-model based technique for feature set extraction from short documents. Given the extracted feature set, we have also developed two probability based text representation schemes that could best represent a text document to an underlying one-class SVM classifier. The proposed models have been compared and evaluated on the public Enron email dataset. Applying graph based feature set extraction technique in combination with the inclusive compound probability based text representation has proved to be very efficient. The generality of the proposed method allows the approach to be applicable to all kind of text documents including emails.

关键词： Novelty detection author attribution graph model feature extraction one class SVM email classification

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Preference uncertainty in the graph model for conflict resolution

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 2004年第4期34卷 507-520页

作者： Li, KW Hipel, KW Kilgour, DM Fang, LP Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Wilfrid Laurier Univ Dept Math Waterloo ON N2L 3C5 Canada Ryerson Univ Dept Mech & Ind Engn Toronto ON M5B 2K3 Canada

A new preference structure is introduced into the graph model for conflict resolution. This structure can handle a decision-maker's (DM) strict preference for one state or scenario over another, equal preference for states, and uncertain or unknown preference in the comparison of two states. Built upon this preference structure, four types of solution definitions modeling human behavior under conflict are extended to accommodate uncertainty in preferences. Four distinct ways to consider uncertain preference information are identified, producing sixteen extended stability definitions. Interrelationships of these definitions within and across the four definition sets are investigated. Illustrative examples of two-DM and multi-DM conflict models are presented to show how the new solution concepts can be applied in practice.

关键词： conflict graph model preference uncertainty solution concepts

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graph model Building for Red Tide Data Based on DWFCM Clustering Algorithm 15

Graph Model Building for Red Tide Data Based on DWFCM Cluste...

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15th IEEE International Conference on Networking, Sensing and Control (ICNSC)

作者： Huang, Dongmei Zhang, Yeyi Zhao, Danfeng Song, Wei Liu, Xinyang Shanghai Ocean Univ Coll Informat Technol Shanghai Peoples R China

ISBN: (纸本)9781538650530

Red tide is one of the most important ocean disasters in the world, which has a serious impact on human production and ecological environment. In order to reduce the impact of red tide, it is necessary to build a reasonable and effective storage model for red tide history data so that the forecasters can find out the required data for comparison, forecast the red tide stage, take measures to prevent and cure red tide quickly and accurately. Most people use relational database to store red tide data. This method has a stable table structure but ignores red tide own characteristics when it occurs, and the speed and precision of query red tide need to be improved. In this paper, we research the storage model of red tide data and proposed a method of graph model building for red tide based on DWFCM clustering algorithm. The FCM clustering algorithm was improved by clustering center selection, weighted Euclidean distance and objective function optimization. The improved DWFCM clustering algorithm was used to cluster the red tide data according to the stage, and the clustered data was stored in the graph model. Experiments show that the DWFCM algorithm can cluster red tide data accurately. The graph model builds relationships between each piece of data and each stage, increasing the speed and accuracy of queries and improving forecaster's ability of red tide forecast quickly and accurately.

关键词： DWFCM algorithm graph model red tide data

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Robust Spatial Consistency graph model for Partial Duplicate Image Retrieval

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IEEE TRANSACTIONS ON MULTIMEDIA 2013年第8期15卷 1982-1996页

作者： Chu, Lingyang Jiang, Shuqiang Wang, Shuhui Zhang, Yanyan Huang, Qingming Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China

Partial duplicate images often have large non-duplicate regions and small duplicate regions with random rotation, which lead to the following problems: 1) large number of noisy features from the non-duplicate regions;2) small number of representative features from the duplicate regions;3) randomly rotated or deformed duplicate regions. These problems challenge many content based image retrieval (CBIR) approaches, since most of them cannot distinguish the representative features from a large proportion of noisy features in a rotation invariant way. In this paper, we propose a rotation invariant partial duplicate image retrieval (PDIR) approach, which effectively and efficiently retrieves the partial duplicate images by accurately matching the representative SIFT features. Our method is based on the Combined-Orientation-Position (COP) consistency graph model, which consists of the following two parts: 1) The COP consistency, which is a rotation invariant measurement of the relative spatial consistency among the candidate matches of SIFT features;it uses a coarse-to-fine family of evenly sectored polar coordinate systems to softly quantize and combine the orientations and positions of the SIFT features. 2) The consistency graph model, which robustly rejects the spatially inconsistent noisy features by effectively detecting the group of candidate feature matches with the largest average COP consistency. Extensive experiments on five large scale image data sets show promising retrieval performances.

关键词： Combined orientation position graph model image retrieval partial duplicate rotation invariant.

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A New Approach to Coalition Analysis Within the graph model

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2020年第6期50卷 2231-2241页

作者： Zhu, Ziming Kilgour, D. Marc Hipel, Keith W. Tsinghua Univ Res Ctr Contemporary Management Beijing 100084 Peoples R China Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Wilfrid Laurier Univ Dept Math Waterloo ON N2L 3C5 Canada Ctr Int Governance Innovat Waterloo ON N2L 6C2 Canada Balsillie Sch Int Affairs Waterloo ON N2L 6C2 Canada

Within the framework of the graph model for conflict resolution, the concept of coalition improvement is generalized, resulting in new definitions of Nash, general metarational, symmetric metarational, and sequential stability applicable to coalitions. To illustrate how these generalized stability definitions can be applied to a real conflict, they are used to analyze an offshore oil exploration dispute that occurred in the South China Sea in 2014. The novel approach reveals which coalitions can upset a noncooperative equilibrium or support new cooperative equilibria, and which decision makers can benefit from joining a coalition.

关键词： Stability analysis Oils Analytical models Game theory Cybernetics System analysis and design Marine vehicles graph model offshore oil exploration dispute Pareto coalition analysis strategic analysis

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A Basic Hierarchical graph model for Conflict Resolution with Application to Water Diversion Conflicts in China

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INFOR 2013年第3期51卷 103-119页

作者： He, Shawei Kilgour, D. Marc Hipel, Keith W. Bashar, M. Abul Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Wilfrid Laurier Univ Dept Math Waterloo ON N2L 3C5 Canada Ctr Int Governance Innovat Waterloo ON N2L 6C2 Canada

A basic hierarchical graph model with three decision makers is developed and used to analyze a water diversion conflict in China. This hierarchical graph model combines two component graph models. The theoretical framework of the combined model is constructed using the decision makers, states, moves, and preference structures from the component models. Theorems are developed to relate stable states in the hierarchical model to stable states in local graph models. This novel approach can avoid direct calculation for four hierarchical stabilities. This methodology is applied to a water diversion conflict in China, consisting of conflicts at two locations where it is proposed to divert water from the south to the north of the country. The analytical results show how decision makers can obtain strategic resolutions for the entire conflict.

关键词： basic hierarchical model graph model conflict resolution water diversion conflict

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Fault Detection Based on graph model for Dead Zone of Steam Turbine Control Valve

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2022年第8期20卷 2759-2767页

作者： Zhang, Yi-Jing Yuan, Ye Hu, Li-Sheng Shanghai Jiao Tong Univ Dept Automat 800 Dongchuan Rd Shanghai 200240 Peoples R China

The abnormal control valve dead zone in the steam turbine causes system oscillation severely, affecting the stable power generation of the power plant. In this study, a graph model is developed, and it can not only detect multiple faults at a time but also reduce the dependence on statistics. The graph topology of the steam turbine is built, including the process nodes and fault node indicating process variables and valve dead zone. Moreover, the graph convolution operation is conducted to classify the faulty and normal conditions. As a result, the simulation and experimental examples demonstrate that the accuracy of dead zone detection reaches 90% and 89% respectively, surpassing Multilayer Perceptron and Principal Component Analysis. The high-precision dead zone detection rate ensures that the method can be effectively applied to industry and improve economic benefits and operation safety.

关键词： Control valve dead zone graph convolution graph model hidden fault node steam turbine

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3D object retrieval based on a graph model descriptor

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NEUROCOMPUTING 2011年第17期74卷 3486-3493页

作者： Xiao, Qinkun Wang, Haiyun Li, Fei Gao, Yue Xian Technol Univ Dept Elect Informat Engn Xian 710032 Peoples R China STMicroelect R&D Asia Pacific Singapore 554574 Singapore Fujitsu Res & Dev Ctr Co Ltd Beijing 100025 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

A new 3D object retrieval approach is proposed based on a novel graph model descriptor and a fast graph matching method. Our methodology is made up of two steps. Firstly, a Bayesian network lightfield descriptor (BLD) is built, based on graph model learning, to overcome the disadvantages of the existing view-based methods. The 3D object is put into the lightfield, multi-view images are obtained;then features of the new multi-view images are extracted. Based on the extracted features, a Bayesian network learning algorithm is used to construct the BLD. Secondly, the 3D object is efficiently retrieved, based on graph model matching and learning from relevant feedback. Experimental results demonstrate that our algorithm has better performance and efficiency than the existing view-based methods. (C) 2011 Elsevier B.V. All rights reserved.

关键词： 3D object retrieval graph model Bayesian network Feedback learning

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