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A Method to Make Classification of the Heat Treatment Processes Performed on Bronze Using Incomplete Knowledge

S. Kluska-Nawarecka, Z. Górny, K. Regulski, D. Wilk-Kołodziejczyk, Z. Jančíková, J. David
2014 Archives of Foundry Engineering  
A methodology for the construction of a classification model based on rough set theory is presented.  ...  The use of rough set theory allows for efficient inference also in areas that are not yet fully explored.  ...  Acknowledgements The work was financed in the framework of the international project No. 820/N-Czechy/2010/0 of 30 November.  ... 
doi:10.2478/afe-2014-0039 fatcat:j76zdoecqvgh3bmbhqm6d35iia

An Intelligent Mining Model for Medical Diagnosis of Heart Disease Based on Rough Set Data Analysis

Hossam A. Nabwey
2020 International journal of engineering research and technology  
Thus, the ultimate goal of this work is to present an intelligent model for mining and generating classification rules for medical diagnosis of heart disease based on rough sets theory.  ...  Rough sets with Boolean reasoning discretization algorithm is introduced to discretize the data, then the rough set reduction technique is applied to find all reducts.  ...  ACKNOWLEDGMENTS The author thank Prince Sattam bin Abdulaziz University, Deanship of Scientific Research at Prince Sattam bin Abdulaziz University for their continuous support and encouragement.  ... 
doi:10.37624/ijert/13.2.2020.355-363 fatcat:37soijzxxzdtdn2ivtdhd6ujb4

Core Reduct Based Preprocessing Approach to Incomplete Data

Pallab Dey, Sripati Mukhopadhyay
2017 International Journal of Intelligent Engineering and Systems  
Rough set approach to incomplete information system has been shown. Application of discernible matrix for incomplete information to compute core and reduct has been shown.  ...  Most of the data mining algorithm's application hampers due to missing attribute values. Inadequate treatment of missing values seriously affects the data mining and classification accuracy.  ...  IRMI Algo, Misssing value % → 5% 10% 15% 20% 25% 30% 35% Iris Data Set Ac 91% 87% 91% 87% 85% 87% 79%  ... 
doi:10.22266/ijies2017.1031.03 fatcat:jepleeh5pzhsfj727zispaoowe

Water Treatment Plant Decision Making Using Rough Multiple Classifier Systems

Lin Feng
2011 Procedia Environmental Sciences  
The authors thank the anonymous referees for their good comments.  ...  This paper is in part supported by the Scientific Research Fund of Sichuan Provincial Education Department under Grants No.09ZC079, and the Key Research Foundation of Sichuan Normal University, respectively  ...  Among data mining techniques, rough sets theory, proposed by Pawlak [5] , is a mathematical and suitable approach for handling imprecision, incompletion and uncertainty in data analysis.  ... 
doi:10.1016/j.proenv.2011.12.213 fatcat:gx5lsc2zcvgptlrelutzsk44em

Intelligent Concepts for the Management of Information in Workflow Systems

George Peters, Roger Tagg
2009 International Journal of Computational Intelligence Systems  
In this paper, we discuss the further potential of intelligent concepts, in particular rough set theory, for the support of the management of information in workflow systems.  ...  Since its introduction in the beginning of the nineteen eighties, rough set theory has gained increasing attention and has established itself as a useful intelligent concept and an important method within  ...  However, we limit our presentation to these three fundamentals of rough sets. For a basic introduction to rough set theory see 8 .  ... 
doi:10.2991/ijcis.2009.2.4.2 fatcat:5ecl762kmndzpop6g2ng4tpvp4

The First International Workshop on Rough Sets: State of the Art and Perspectives

Wojciech Ziarko
1993 The AI Magazine  
Acknowledgments Thanks are owed to Howard Hamilton, Zdzislaw Pawlak, Larry Saxton, Andrzej Skowron, and Roman Slowinski, whose detailed comments and remarks helped in the preparation of this article.  ...  The primary notions of the theory of rough sets are the approximation space and lower and upper approximations of a set.  ...  The theory was originated by The methodology is concerned with the classificatory analysis of imprecise, uncertain, or incomplete information or knowledge expressed in terms of data acquired from experience  ... 
doi:10.1609/aimag.v14i3.1059 dblp:journals/aim/Ziarko93 fatcat:ywwfzoigujfqjj6bqomuuq5mlu

Comparative Analysis of Student Psychology Prediction-Recommendation Two Phase Strategy

Bhakti Ratnaparkhi
2016 International Journal of Computer Applications  
In our proposed work we have used Rough sets to extract the rules for prediction of student's psychology.  ...  Big data analysis includes many theories and methods for prediction system.  ...  Rough set theory is useful for rule induction from incomplete data sets.  ... 
doi:10.5120/ijca2016912110 fatcat:fncxkw27pfgx5axo7wd2sjqqke

Thyroid Diagnosis based Technique on Rough Sets with Modified Similarity Relation

Elsayed Radwan, Adel M.A.
2013 International Journal of Advanced Computer Science and Applications  
In this paper, Rough sets theory is used in data discretization for continuous attribute values, data reduction and rule induction.  ...  Also, Rough sets try to cluster the Thyroid relation attributes in the presence of missing attribute values and build the Modified Similarity Relation that is dependent on the number of missing values  ...  Also, a great appreciation to Gravan Institute of Medical Research for providing the medical database. Also, we should express our deep appreciation for Mrs.  ... 
doi:10.14569/ijacsa.2013.041019 fatcat:kdgkrf5zyvgefl5orfevmrol3a

Methodology for the Construction of a Rule-Based Knowledge Base Enabling the Selection of Appropriate Bronze Heat Treatment Parameters Using Rough Sets

Z. Górny, S. Kluska-Nawarecka, D. Wilk-Kołodziejczyk, K. Regulski
2015 Archives of Metallurgy and Materials  
This study gives an example of the construction of a knowledge base with application of the rough set theory.  ...  Decisions regarding appropriate methods for the heat treatment of bronzes affect the final properties obtained in these materials.  ...  Acknowledgements The work was financed in the framework of the international project No. 820/N-Czechy/2010/0 of 30 November.  ... 
doi:10.1515/amm-2015-0050 fatcat:6pjcukwwhrexnjujzp74idgqra

Prediction of Missing Values for Decision Attribute

T. Medhat
2012 International Journal of Information Technology and Computer Science  
These values can be calculated by d istance function between the conditions attributes values for the complete informat ion system and incomplete informat ion system.  ...  The process of determining missing values in informat ion system is an important issue for decision making especially when the missing values are in the decision attribute.  ...  Kozae, for his encouragement and support, and sincerely thank the anonymous reviewers whose comments have greatly helped clarify and improve this paper.  ... 
doi:10.5815/ijitcs.2012.11.08 fatcat:bkm65ugtzvf5jbofcwl6dueoia

A Bit-Chain Based Algorithm for Problem of Attribute Reduction [chapter]

Thanh-Trung Nguyen, Viet-Long Huu Nguyen, Phi-Khu Nguyen
2012 Lecture Notes in Computer Science  
One of key problems of knowledge acquisition in theoretical study of rough sets is attribute reduction.  ...  The algorithm for seeking maximal random prior set are proposed with linear complexity, contributes to solve absolutely problems in attribute reduction and significantly improve the speed of calculation  ...  To contribute to treatments for the problem, fuzzy-rough reductions or fuzzy-rough feature selection is created and also a noticeably concept.  ... 
doi:10.1007/978-3-642-28487-8_44 fatcat:ydns5mo65nfqxcabv4b6bmu5jq

Rough Set Model Based on the Dual-limited Symmetric Similarity Relation

Yu-Ming Zhai, Rui-Xia Yan, Zhen-Yu Huang, Bin Guo
2013 Applied Mathematics & Information Sciences  
An example presented illustrates the effectiveness and practicality of the rough set model based on the dual-limited symmetric similarity relation.  ...  Information systems are often incomplete in object world. This paper puts forward a new rough set model in incomplete information system.  ...  Acknowledgments The authors are grateful to the anonymous referee for a careful checking of the details and for helpful comments that improved this paper.  ... 
doi:10.12785/amis/071l03 fatcat:h63svqj3lrfrbdoyoczseb67am

A Modal Characterization of Indiscernibility and Similarity Relations in Pawlak's Information Systems [chapter]

Dimiter Vakarelov
2005 Lecture Notes in Computer Science  
I Variable Precision Fuzzy Rough Sets Model in the Analysis of Process Data Alicja Mieszkowicz-Rolka, Leszek Rolka 354 CRST: A Generalization of Rough Set Theory Hong Tian, Pixi Zhao, Xiukun Wang 364  ...  Approximation Spaces Piotr Wasilewski 114 Rough Sets over the Boolean Algebras Gui-Long Liu 124 Algebraic Approach to Generalized Rough Sets Michiro Kondo 132 Logic for Rough Sets with Rough  ... 
doi:10.1007/11548669_2 fatcat:izzj5s3t6nffzelnlkvdbn2qk4

Rough Set Theory — Fundamental Concepts, Principals, Data Extraction, and Applications [chapter]

Silvia Rissino, Germano Lambert-Torres
2009 Data Mining and Knowledge Discovery in Real Life Applications  
The subject of this chapter is to present the Rough Set Theory, important concepts, and Rough Set Theory used with tools for data mining, special applications in analysis of data in dengue diagnosis.  ...  The rough set approach to processing of incomplete data is based on the lower and the upper approximation, and the theory is defined as a pair of two crisp sets corresponding to approximations.  ...  Below is presented and described the types of approximations are followed using in Rough Set Theory; the approximations concepts are applied in the Table 3 , shown to proceed: attribute that is different  ... 
doi:10.5772/6440 fatcat:wn2dgx5u3rdk5egnzzmq7ko4my

Breast Tissue Classification via Interval Type 2 Fuzzy Logic Based Rough Set

Wan Noor Aziezan Baharuddin, Siti Norul Huda Sheikh Abdullah, Shahnorbanun Sahran, Ashwaq Qasem, Rizuana Iqbal Hussain, Azizi Abdullah
2018 International Journal on Advanced Science, Engineering and Information Technology  
The sensitivity using expert rules is 98.24% whereas rough set rules obtained 93.94%. Specificity for using expert rules and rough set rules are 73.33%, 84.34% consecutively.  ...  Among the rules that used by the model were obtained from experts as well as generated automatically by the system using rough set theory.  ...  Besides, rough set theory also can evaluate the data clearly. For example, while generating rules, rough set will identify pattern and relationship of the data to yield a sound rule.  ... 
doi:10.18517/ijaseit.8.4-2.6821 fatcat:rhivcirvufayhcwfxb3dn5uu2i
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