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Seismic vulnerability assessment of urban buildings using the rough set theory and weighted linear combination

Journal of Mountain Science 2022年第3期19卷 849-861页

作者： Yasaman ASADI Najmeh NEYSANI SAMANY Majid KIAVARZ MOQADAM Ata ABDOLLAHI KAKROODI Meysam ARGANY Department of Remote Sensing and GIS Faculty of GeographyUniversity TehranTehran 33137-67464Iran

Seismic vulnerability assessment of urban buildings is among the most crucial procedures to post-disaster response and recovery of infrastructure systems.The present study proceeds to estimate the seismic vulnerability of urban buildings and proposes a new framework training on the two objectives.First,a comprehensive interpretation of the effective parameters of this phenomenon including physical and human factors is done.Second,the rough set theory is used to reduce the integration uncertainties,as there are numerous quantitative and qualitative data.Both objectives were conducted on seven distinct earthquake scenarios with different intensities based on distance from the fault line and the epicenter.The proposed method was implemented by measuring seismic vulnerability for the seven specified seismic scenarios.The final results indicated that among the entire studied buildings,71.5%were highly vulnerable as concerning the highest earthquake scenario(intensity=7 MM and acceleration calculated based on the epicenter),while in the lowest earthquake scenario(intensity=5 MM),the percentage of vulnerable buildings decreased to approximately 57%.Also,the findings proved that the distance from the fault line rather than the earthquake center(epicenter)has a significant effect on the seismic vulnerability of urban buildings.The model was evaluated by comparing the results with the weighted linear combination(WLC)method.The accuracy of the proposed model was substantiated according to evaluation reports.Vulnerability assessment based on the distance from the epicenter and its comparison with the distance from the fault shows significant reliable results.

关键词： Seismic vulnerability Urban buildings rough set theory Earthquake scenarios WLC

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Half-global discretization algorithm based on rough set theory

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Journal of Systems Engineering and Electronics 2009年第2期20卷 339-347页

作者： Tan Xu Chen Yingwu School of Information Systems & Management National Univ. of Defense Technology Changsha 410073 P. R. China

It is being widely studied how to extract knowledge from a decision table based on rough set theory. The novel problem is how to discretize a decision table having continuous attribute. In order to obtain more reasonable discretization results, a discretization algorithm is proposed, which arranges half-global discretization based on the correlational coefficient of each continuous attribute while considering the uniqueness of rough set theory. When choosing heuristic information, stability is combined with rough entropy. In terms of stability, the possibility of classifying objects belonging to certain sub-interval of a given attribute into neighbor sub-intervals is minimized. By doing this, rational discrete intervals can be determined. rough entropy is employed to decide the optimal cut-points while guaranteeing the consistency of the decision table after discretization. Thought of this algorithm is elaborated through Iris data and then some experiments by comparing outcomes of four discritized datasets are also given, which are calculated by the proposed algorithm and four other typical algorithras for discritization respectively. After that, classification rules are deduced and summarized through rough set based classifiers. Results show that the proposed discretization algorithm is able to generate optimal classification accuracy while minimizing the number of discrete intervals. It displays superiority especially when dealing with a decision table having a large attribute number.

关键词： half-global discretization continuous condition attributes correlation coefficient rough entropy stability rough set theory

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Model-based diagnosis of incomplete discrete-event system with rough set theory

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Science China(Information Sciences) 2017年第1期60卷 190-200页

作者： Xuena GENG Dantong OUYANG Yonggang ZHANG Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of EducationJilin University College of Computer Science and Technology Jilin University

Fault diagnosis of discrete-event system(DES) is important in the preventing of harmful events in the system. In an ideal situation, the system to be diagnosed is assumed to be complete; however, this assumption is rather restrictive. In this paper, a novel approach, which uses rough set theory as a knowledge extraction tool to deal with diagnosis problems of an incomplete model, is investigated. DESs are presented as information tables and decision tables. Based on the incomplete model and observations, an algorithm called Optimizing Incomplete Model is proposed in this paper in order to obtain the repaired model. Furthermore, a necessary and sufficient condition for a system to be diagnosable is given. In ensuring the diagnosability of a system, we also propose an algorithm to minimize the observable events and reduce the cost of sensor selection.

关键词： model-based diagnosis diagnosability discrete-event system finite state machine rough set theory

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Research on knowledge acquisition method about the IF/THEN rules based on rough set theory

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Journal of Systems Engineering and Electronics 2008年第3期19卷 628-634,F0003页

作者： Liu Daohua Yuan Sicong Zhang Xiaolong Wang Fazhan School of Mechanical & Electronic Engineering Xi'an Univ. of Architecture & Technology Xi'an 710055 P. R. China Dept. of Computer Science Xinyang Normal Univ. Xinyang 464000 P. R. China

The basic principles of IF/THEN rules in rough set theory are analyzed first, and then the automatic process of knowledge acquisition is given. The numerical data is qualitatively processed by the classification of membership functions and membership degrees to get the normative decision table. The regular method of relations and the reduction algorithm of attributes are studied. The reduced relations are presented by the multi-representvalue method and its algorithm is offered. The whole knowledge acquisition process has high degree of automation and the extracted knowledge is true and reliable.

关键词： rough set theory knowledge＇s automatic gain IF/THEN rule attribute reduction multi-dimensionalrepresentative value.

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New heuristic method for data discretization based on rough set theory

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The Journal of China Universities of Posts and Telecommunications 2009年第6期16卷 113-120页

作者： ZHAO Jun ZHOU Ying-hua Institute of Computer Science and Tcchnology Chongqing University of Posts and Telecommunications Chongqing 400065 China

Data discretization contributes much to the induction of classification rules or trees by machine learning methods. The rough set theory is a valid tool for discretizing continuous information systems. Herein, a new method is proposed to improve those typical rough set based heuristic algorithms for data discretization, by utilizing decision information to reduce the scales of candidate cuts, and by more reasonably measuring cut significance with a new conception of cut selection probability. Simulations demonstrate that compared with other typical discretization algorithms based on the rough set theory, the proposed method is more capable and valid to discretize continuous information systems. It can effectively improve the predictive accuracies of information systems while still conceptually keeping their consistency.

关键词： data discretization rough set theory cut cut significance selection probability

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Two kinds of average approximation accuracy

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 481-490页

作者： Qingzhao Kong Wanting Wang Dongxiao Zhang Wenbin Zhang Department of Science Jimei UniversityXiamenChina Digital Fujian Big Data Modeling and Intelligent Computing Institute Jimei UniversityXiamenChina Department of Computer Science Michigan Technological UniversityHoughtonMichiganUSA

rough set theory places great importance on approximation accuracy,which is used to gauge how well a rough set model describes a target concept.However,traditional approximation accuracy has limitations since it varies with changes in the target concept and cannot evaluate the overall descriptive ability of a rough set model.To overcome this,two types of average approximation accuracy that objectively assess a rough set model’s ability to approximate all information granules is proposed.The first is the relative average approximation accuracy,which is based on all sets in the universe and has several basic properties.The second is the absolute average approximation accuracy,which is based on undefinable sets and has yielded significant conclusions.We also explore the relationship between these two types of average approximation accuracy.Finally,the average approximation accuracy has practical applications in addressing missing attribute values in incomplete information tables.

关键词： rough sets rough set theory

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Two Hybrid Methods Based on rough set theory for Network Intrusion Detection

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Journal of Harbin Institute of Technology(New Series) 2014年第6期21卷 22-27页

作者： Na Jiao Dept.of Information Science and Technology East China University of Political Science and Law

In this paper,we propose two intrusion detection methods which combine rough set theory and Fuzzy C-Means for network intrusion detection.The first step consists of feature selection which is based on rough set theory.The next phase is clustering by using Fuzzy C-Means.rough set theory is an efficient tool for further reducing redundancy.Fuzzy C-Means allows the objects to belong to several clusters simultaneously,with different degrees of membership.To evaluate the performance of the introduced approaches,we apply them to the international Knowledge Discovery and Data mining intrusion detection dataset.In the experimentations,we compare the performance of two rough set theory based hybrid methods for network intrusion detection.Experimental results illustrate that our algorithms are accurate models for handling complex attack patterns in large network.And these two methods can increase the efficiency and reduce the dataset by looking for overlapping categories.

关键词： rough set theory Fuzzy C-Means network security intrusion detection

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Warship detection in Smoke Screen Interference Based on Fractal and rough set theory 11th

Warship detection in Smoke Screen Interference Based on Frac...

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2012 IEEE 11th International Conference on Signal Processing(ICSP 2012)

作者： LI Zhiguo Yan Xiaoke Bai Yudong Unit 91404 PLA

ISBN: (纸本)9781467321969

In IR images, the same kind of natural scenes are self-similarity statistically, namely their fractal dimension remains unchanged approximately. At edges, however, the dimension is underestimated, because edges add a deterministic component to the surface which is not assumed to be presented for the purpose of calculation of the fractal dimension. Thus, the local degree of ’fractality’ is used to differentiate the regions-of-interest （ROI） from the clutter background. Then, the warship is detected based on indiscemibility relation of rough sets （RS） theory and is recognized based on the geometric characters of warship. Experiments on the image tracker based on TMS320C6416 were conducted, and the results demonstrated that the approach performs well in automatic recognition accuracy and computational efficiency.

关键词： Warship Smoke Screen Fractal rough set theory

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Study of Weight Determination Based on rough set theory in Desulfuration Projects Decision

Study of Weight Determination Based on Rough Set Theory in D...

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2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop(KAM 2008)

作者： Li Wei Department of Economic Management North China Electric Power University Baoding Hebei Province China 071003Shang Yumin Department of Economic Management North China Electric Power University Baoding Hebei Province China 071003

rough set theory could availably analysis and the processing the incomplete information problems.Cited the rough set theory into desulfuration projects decision,through the analysis and extraction of each desulfuration method evaluation index,and according to the importance index of each desulfuration method evaluation index to the order of alternatives is sorted to get thus consistent and completed decision rule.This method based on the actual application background,combined the objective weight and the subjective weight which is decided by the experts’ experience knowledge to assured the final weight value.This method makes up for the shortness of the subjective weight decided by the experts’ experience knowledge.Through the study of actual application based on rough set theory,confirmed the rationality and feasibility of the rough set theory that used in the decision making of desulfuration projects.

关键词： weight determination rough set theory condition attributes desulfuration projects knowledge reduction

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Study on Happiness Index Based on rough set theory and Grey Correlation Analysis

Study on Happiness Index Based on Rough Set Theory and Grey ...

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2011 3rd IEEE International Conference on Information Management and Engineering(ICIME 2011)

作者： Xiao-jin Yang Mathematical Modeling Innovative Practice Base,International business school Jinan University,Zhuhai,China 519070 Yuan-Biao Zhang 1,a,Han Qi 1,b 1 Mathematical Modeling Innovative Practice Base,Zhuhai Campus Jinan University,Zhuhai,China 519070

To evaluate the happiness indexes of citizens quantitatively and objectively,this paper built up a new happiness evaluation system in view of difficulties of indicator quantification in existing ones.Based on rough set theory and grey relational analysis,a comprehensive evaluation model of happiness index was put forward.The empirical test of the proposed model was conducted using the data of Zhuhai in recent years.Finally the happiness indexes of representative cities—Zhuhai,Shenzhen,Guangzhou,Dalian,Xiamen,Ningbo,Jinan,Qingdao and Nanjing—were measured and compared.

关键词： happiness index evaluating indicators rough set theory grey relational analysis

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