Results 111 to 120 of about 405 (144)
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2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010
In an ordered decision information system, dominance-based rough set approach (DRSA) were used to compute reducts of the system which preserve the lower and upper approximations of upward union and downward union of decision classes. Recently, class-based reducts (L-reduct and U-reduct) which preserve respectively lower and upper approximates of each ...
Shujin Li, Yanyong Guan
exaly +2 more sources
In an ordered decision information system, dominance-based rough set approach (DRSA) were used to compute reducts of the system which preserve the lower and upper approximations of upward union and downward union of decision classes. Recently, class-based reducts (L-reduct and U-reduct) which preserve respectively lower and upper approximates of each ...
Shujin Li, Yanyong Guan
exaly +2 more sources
A fuzzy set extension of DRSA on the better life in happiness
2012 International conference on Fuzzy Theory and Its Applications (iFUZZY2012), 2012The desire of human beings and the goal of government policy basically have a common point, i.e., the better life in happiness. However, the common point composed of multi-criteria from objective and subjective living causes difficulty in decision making. This research applies the fuzzy set extensions of dominance-based rough set approach (FSE-DRSA) on
Yu-Chien Ko, Gwo-Hshiung Tzeng
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On Performance of DRSA-ANN Classifier
Lecture Notes in Computer Science, 2011Rule-based and connectionist classifiers are typically named as two different approaches to recognition tasks. The first relies on induction of a set of rules that list conditions to be met for a decision to be applicable, while the latter means distribution of data and processing.
Urszula Stańczyk, Stańczyk Urszula
exaly +2 more sources
Incremental method of updating approximations in DRSA under variations of multiple objects
International Journal of Machine Learning and Cybernetics, 2015Dominance-based rough sets approach (DRSA) uses dominance relations to substitute equivalence relations in conventional rough set models so that it can handle preference-ordered information. Up to date, DRSA has been widely used in multi-criteria decision-making problems.
Yan Li, Yongfei Jin, Xiaodian Sun
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VC-DRSA for knowledge retrieval based on technical analysis and investment practice
2014 International Conference on Fuzzy Theory and Its Applications (iFUZZY2014), 2014This study aims to retrieve useful knowledge from commonly adopted technical indicators, based on a soft computing model, to support investment decisions. Though the validity of technical analysis (TA) has been examined extensively by various statistical models in financial literature, a practical approach that may consider the inconsistency among ...
Kao-Yi Shen, Gwo-Hshiung Tzeng
exaly +2 more sources
DRSA Decision Algorithm Analysis in Stylometric Processing of Literary Texts
Lecture Notes in Computer Science, 2010When the indiscernibility relation, fundamental to Classical Rough Set Approach, is substituted with dominance relation, it results in Dominance-Based Rough Set Approach to data analysis. It enables support not only for nominal classification tasks, but also when ordinal properties on attribute values can be observed [1], making DRSA methodology well ...
Urszula Stańczyk, Stańczyk Urszula
exaly +2 more sources
A refined DRSA model for the financial performance prediction of commercial banks
2013 International Conference on Fuzzy Theory and Its Applications (iFUZZY), 2013In this study, an integrated soft computing method is proposed to solve the performance prediction of commercial banks. The proposed model not only shows how to explore the implicit patterns from historical data, but also supports to provide guidance regarding the performance categorization of banks on each attribute.
Kao-Yi Shen, Gwo-Hshiung Tzeng
exaly +2 more sources
On Preference Order of DRSA Conditional Attributes for Computational Stylistics
Lecture Notes in Computer Science, 2013Computational stylistics (or stylometry) advocates that any writing style can be uniquely defined by quantitative measures. The patterns observed in textual descriptors are specific to authors in such high degree that it enables their recognition. In processing there can be employed techniques from artificial intelligence domain such as Dominance-Based
Urszula Stańczyk, Stańczyk Urszula
exaly +2 more sources
Application of DRSA-ANN Classifier in Computational Stylistics
Lecture Notes in Computer Science, 2011Computational stylistics or stylometry deals with characteristics of writing styles. It assumes that each author expresses themselves in such an individual way that a writing style can be uniquely defined and described by some quantifiable measures. With help of contemporary computers the stylometric tasks of author characterisation, comparison, and ...
Urszula Stańczyk, Stańczyk Urszula
exaly +2 more sources
Fuzzy Inference-Enhanced VC-DRSA Model for Technical Analysis: Investment Decision Aid
International Journal of Fuzzy Systems, 2015To support investment decision based on technical analysis (TA), this study aims to retrieve the knowledge or rules of various indicators by a hybrid soft computing model. Although the validity of TA has been examined extensively by various statistical methods in literature, previous studies mainly explored the effectiveness of each technical indicator
Kao-Yi Shen +2 more
exaly +2 more sources

