This paper presents an approach to the discovery of association rules for fuzzy spatial data. Association rules provide information of value in assessing significant correlations that can be found in large databases. Here we are interested in correlations of spatially related data such as soil types...
In this paper we describe and discuss the main contributions of the representation by levels approach to fuzzy data mining Representation by levels is an alternative representation of fuzziness in information and data, which is complementary to fuzzy sets in the sense that it provides tools and alge...
Investigation on influence of the deposition parameters on the properties of CdS thin film prepared by the chemical bath deposition method An Approach to the Diagnosis of Transformer’s Insulating Oil Enhancing Resource Sharing Through Digital Knowledge Accessibility In The Modern Era In Developing Countri...
I. A. Chen. Query answering using discovered rules. In S. Y. W. Su, editor,Proceedinds of the 12th International Conference on Data Engineering Knowledge discovery and data mining X. Hu and N. Cercone. Mining knowledge rules from databases: A rough set approach. In S. Y. W. Su, edi...
Modelling fuzzy interval-based temporal information: a temporal\ndatabase perspective Its major aim is to be used as a basic framework to incorporate fuzzy time in temporal databases. The approach is based on Zadeh's fuzzy set and ... W Kurutach 被引量: 14发表: 1995年 A fuzzy mining appr...
An intelligent financial data mining system using a fuzzy clustering multimedia approachView further author informationMengsha PanView further author informationtzvcst.edu.cn xia_duan@outlook.comXiao DuanView further author informationMengsha PanView further author information...
To evaluate the performance of the proposed approach, we applied it to several well-known time series datasets. The experimental results showed that our approach is very promising. 展开 关键词: data mining fuzzy set theory time series adjusted residual analysis data mining technique fuzzy set ...
The classifier has achieved an accuracy of 93.55% for CHD data set with two class labels; 73.77% for CHD data set with five class labels; 94.44% for SHD data set and 92.54% for PID dataset.Previous article in issue Next article in issue Keywords Extreme learning machine Fuzzification Fuzzy ...
In the paper, we introduce a new kind of fuzzy formal concept derived from an adjoint pair of operations. Based on the discussed fuzzy formal concepts, a pair of rough fuzzy set approximations in fuzzy formal contexts is introduced. The properties of the
In educational data, many attributes are recorded as quantitative data. Therefore, we propose an Apriori-based mining approach, Fuzzy Apriori Rare Itemset Mining (FARIM), for mining fuzzy specific rare itemsets consisting of quantitative data. Fuzzy association rules are generated from these fuzzy ...