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Evaluation of Rough Set Theory Based Network TrafficData Classifier Using Different Discretization Method

Nandita Sengupta
2012 International Journal of Information and Electronics Engineering  
In the paper, network traffic data is classified using rough set theory where discretization of data is a necessary preprocessing step.  ...  It has been observed that supervised discretization yields best accuracy for rough set classification and provides system adaptability.  ...  ROUGH SET THEORY A. Information System Information system [8] is nothing but Data table.  ... 
doi:10.7763/ijiee.2012.v2.110 fatcat:4f57wh3eg5es7bsrelsrkfeuma

Attribute Reduction Based on Consistent Covering Rough Set and Its Application

Jianchuan Bai, Kewen Xia, Yongliang Lin, Panpan Wu
2017 Complexity  
Covering rough set, as a generalization of classical rough set theory, has attracted wide attention on both theory and application.  ...  As an important processing step for rough set theory, attribute reduction aims at eliminating data redundancy and drawing useful information.  ...  E2016202341) and Hebei Province Foundation for Returned Scholars (no. C2012003038).  ... 
doi:10.1155/2017/8986917 fatcat:ncxw6ovd6zds3ba4s7v4ey7i2u

Fault diagnosis using Rough Sets Theory

Lixiang Shen, Francis E.H. Tay, Liangsheng Qu, Yudi Shen
2000 Computers in industry (Print)  
In this paper, a new method, Rough Sets Theory, is used to diagnose the valve fault for a multi-cylinder diesel engine.  ...  Through the analysis of the final reducts generated using Rough Sets Theory, it is shown that this new method is effective for valve fault diagnosis.  ...  There is a need to have a method that can diagnose more than one category of faults in a generic manner. In this paper, a method based on Rough Sets Theory is proposed and implemented. Ž . Z.  ... 
doi:10.1016/s0166-3615(00)00050-6 fatcat:jemtr2lff5eelng2bzbfddfb7e

The Method of Complex Maneuvering Event Detection Based on Rough Sets

Di ZHANG, Wei CHEN, Yi-jun CHEN, Zhen-zhou BAI
2017 DEStech Transactions on Materials Science and Engineering  
The article proposes a complex motor incident detection algorithm based on rough sets, extracted by rough set theory learning in the training sample covers the basic characteristics of typical data, at  ...  the same time use x combined optimal discretization of continuous attribute values in optimization, get the minimalist rule set, this method can effectively improve the accuracy of air combat in the complex  ...  The Basic Ideas of Method Firstly, establish a training sample set, and then the rough set theory is utilized to extract the training sample data of typical characteristics, constructing rough set decision  ... 
doi:10.12783/dtmse/amsee2017/14296 fatcat:ut6w7c3rfbedblipsnsn6zzfmu

On Quasi Discrete Topological Spaces in Information Systems

Tutut Herawan
2012 International Journal of Artificial Life Research  
Using the concept of an indiscernibility relation in rough set theory, it is shown that the topology constructed is a quasi-discrete topology.  ...  Rough set theory for reasoning about data in information systems is used to construct the topology.  ...  Rough set theory may therefore be considered as a method for constructing a topological space using indiscernibility relation on the universe.  ... 
doi:10.4018/jalr.2012040104 fatcat:7jcwuhtq6vdf7ide6sdyio2rke

Bayesian Network Structure Learning Based On Rough Set and Mutual Information

Zuhong Feng, Xiujuan Gao, Long Wang
2014 TELKOMNIKA Indonesian Journal of Electrical Engineering  
In Bayesian network structure learning for incomplete data set, a common problem is too many attributes causing low efficiency and high computation complexity.  ...  In this paper, an algorithm of attribute reduction based on rough set is introduced.  ...  Rough Set Theory Rough set theory was presented for boundary region by Polish professor Pawlak in the 1980s [3] . This method has strong objectivity due to its mathematical formula.  ... 
doi:10.11591/telkomnika.v12i2.3768 fatcat:x2p3vmr6xrfb3atpnb24mfrcqy

Comparative Overview of Rough Set Toolkit Systems for Data Analysis

Piotr Pięta, Tomasz Szmuc, Krzysztof Kluza, M. Kulisz, M. Szala, M. Badurowicz, W. Cel, M. Chmielewska, Z. Czyż, K. Falkowicz, J. Kujawska, T. Tulwin
2019 MATEC Web of Conferences  
and Rough Set Toolkit for Analysis of Data.  ...  In this paper, we present an analysis of existing rough set tools, namely: Rough Set Exploration System, Rough Sets Data Explorer, Rough Set Data Analysis Framework, Waikato Environment for Knowledge Analysis  ...  ROSE extends the methods of the classic rough set theory by a similarity relation.  ... 
doi:10.1051/matecconf/201925203019 fatcat:x4qnthjoljdmrm7lpntmdfoajm

A two level approach to discretize cosmetic data using Rough set theory

P.M. Prasuna, Dr.Y. Ramadevi, Dr. A. Vinay Babu
This paper proposes a two level discretization method which is a combination of traditional k means clustering technique and rough set theory to discretize continuous features of cosmetic data.  ...  Existing traditional discretization techniques are not sufficient for deriving discretized data from continuous valued cosmetic data as it has to balance the loss of information intrinsic to process adapted  ...  This step discretizes the data into specified number of intervals .The results are then given to the second phase which uses Rough set theory [5] Rough Set Theory Rough set theory was proposed by  ... 
doi:10.24297/ijct.v14i10.1826 fatcat:ikwe4z6vcfdz3knlqmxgmlkal4

Multispectral remote sensing image classification algorithm based on rough set theory

Ying Wang, Xiaoyun Liu, Zhensong Wang, Wufan Chen
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
Rough set theory is a relatively new mathematical tool to deal with imprecise, incomplete and inconsistent data. A method of multispectral image classification using rough set theory is proposed.  ...  First, to decrease computational time and complexity, band reduction of multispectral image using attribute reduct concept in rough set theory and information entropy is performed.  ...  Documents about discrete threshold in rough set theory, one may refer to [7] and [8] .  ... 
doi:10.1109/icsmc.2009.5346054 dblp:conf/smc/WangLWC09 fatcat:2b3chwcgifhddjzkkpovyn2jmi

A fuzzy neighborhood rough set method for anomaly detection in large scale data

EL Meziati Marouane, Ziyati Elhoussaine
2020 IAES International Journal of Artificial Intelligence (IJ-AI)  
This approach involves a neighborhood fuzzy rough set theory to rank outlier according to fuzzy membership function computed in rough approximation space.  ...  In this paper, we propose a novel approach for outlier detection with voluminous data.  ...  ACKNOWLEDGEMENTS The authors are very much thankful to the unanimous reviewers of the paper and editors of the journal for their constructive and helpful comments that improved the quality of the paper  ... 
doi:10.11591/ijai.v9.i1.pp1-10 fatcat:5ueczwvckvgufh4sgc7foeapfy

Research on the Data Pre-Processing in the Network Abnormal Intrusion Detection

Xiang Cui, Guisheng Yin, Xuyang Teng
2014 Open Automation and Control Systems Journal  
Second, Aiming to the problem of the continuous data discretization in the rough set theory, an adaptive discrete algorithm for the data characteristics is proposed, and the algorithm determines the intervals  ...  set theory.  ...  Another notices the features of the rough set theory, such as the discrete method based on the Boolean Logic and the rough set theory.  ... 
doi:10.2174/1874444301406011228 fatcat:bhv3nt6f7jf75dkmqzll2ndgue

Discretization method based on binary ant colony and variable precision rough set

Jian Song, Yu Jiang, Dong Li, Yangwanying Bao
2019 IOP Conference Series: Materials Science and Engineering  
A new discretization algorithm based on binary ant colony and variable precision rough set is proposed in this paper.  ...  This method is compared with other algorithms using C4.5 classifier on the WEKA (Waikato Environment for Knowledge Analysis) platform and seven UCI data sets.  ...  These methods include discretization based on information entropy [6] , discretization based on binary ant and rough sets [13] and three methods in Rosetta (a software based on rough set).  ... 
doi:10.1088/1757-899x/569/5/052027 fatcat:xqjwqxxrlva57khlxtrjfjvhfi

An Evaluation Study on Information System Based on Rough Set and Condition Information Entropy

Sha Fu, Guang Sun, Hangjun Zhou, Feng Yan
2016 Journal of software engineering  
Based on the incompleteness and conceptual uncertainty of information in management decision making and evaluation, the rough set theory and condition information entropy were introduced to build a comprehensive  ...  Through real case analysis, the feasibility and effectiveness of the rough set intelligent evaluation model were verified.  ...  ., 10 (1): [129] [130] [131] [132] [133] [134] [135] [136] [137] 2016 Rough set theory: Rough set theory was proposed by Pawlak (1982) , a Polish mathematician, in 1982 as a new theory method to express  ... 
doi:10.3923/jse.2016.129.137 fatcat:4xev5bhzd5hjjisrnbabvml6yu

Assessment of Rough Set Theory in Relation to Risks Regarding Hydraulic Engineering Investment Decisions

Jihong Qu, Xiao Bai, Jiajun Gu, Farhad Taghizadeh-Hesary, Ji Lin
2020 Mathematics  
Rough set theory is a mathematics tool specifying imperfection and uncertainty. Based on the knowledge theory of the rough set, the numerical values of some features or attributes are not required.  ...  the rough set method are discrete, and, unlike other methods, this theory can solve the discrete phenomenon of data.  ...  To explain the application method based on the knowledge theory of the rough set, a method for processing the information of the decision table is proposed, and the main steps of the method are as follows  ... 
doi:10.3390/math8081308 fatcat:y3hdz3xuo5f2tnmtdakmn5ypnu

Rough Neuron network for Fault Diagnosis

Yueling Zhao, Hui Jin, Lihong Wang, Shuang Wang
2011 International Journal of Image Graphics and Signal Processing  
Lastly, according to the optimal decision system, rough neuron network is designed for fault diagnosis. A practical example is given , the method is feasible and available.  ...  Considering training time of traditional BP neural network is too long and it cannot solve the problems in the input vector with multiple-valued, a new method of BP neural network based on rough neuron  ...  with a rough set theory.  ... 
doi:10.5815/ijigsp.2011.02.08 fatcat:gndwx6gy2vaa5dlbfsbthr4psi
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