Results 251 to 260 of about 1,072,947 (315)

A NOTE ON TREE DIAGRAMS, SET THEORY AND SYMBOLIC LOGIC

The Professional Geographer, 1966
Louis Hamill
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Power transformer failure analysis using interval type-2 fuzzy set theory based fault tree analysis

2016 IEEE 7th Power India International Conference (PIICON), 2016
Reliable power supply depends on proper equipment functioning. Power transformer keeps up voltage and power level of the system. Power transformer failure is caused by insulation failure, low voltage bushing, frequent tap change, tank leakage etc. These causes are analysed with the help of probability of occurrence of each event.
Rituparna Mitra, Galiveeti Hemakumar Reddy, Arup Kumar Goswami, Nalin B. Dev Choudhury   +3 more
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Axiomatic fuzzy set theory-based fuzzy oblique decision tree with dynamic mining fuzzy rules

Neural Computing and Applications, 2019
This paper proposes a novel classification technology—fuzzy rule-based oblique decision tree (FRODT). The neighborhood rough sets-based FAST feature selection (NRS_FS_FAST) is first introduced to reduce attributes. In the axiomatic fuzzy set theory framework, the fuzzy rule extraction algorithm is then proposed to dynamically extract fuzzy rules.
Yuliang Cai, Huaguang Zhang, Shaoxin Sun, Xianchang Wang, Qiang He   +4 more
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Construction of Decision Tree Based on Rough Sets Theory

Advanced Materials Research, 2012
In the process of constructing decision trees, the selecting criteria of classification attributes will directly affect the classification results. Here we presented the classification contribution function (CCF), a new concept based on rough sets theory, which is regarded as the criteria for choosing attributes in the core of attributes.
Zhi Jun Lei, Lin Li Wu
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Induction of Decision Trees Based on the Rough Set Theory

1998
This paper aimed at two following objectives. One was the introduction of a new measure (R-measure) of dependency between groups of attributes in a data set, inspired by the notion of dependency of attribute in the rough set theory. The second was the application of this measure to the problem of attribute selection in decision tree induction, and an ...
Tu Bao Ho, Trong Dung Nguyen, Masayuki Kimura   +2 more
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Decision Tree Construction from Knowledge Discovered by Rough Sets Theory

Proceedings of the … International Conference on Operational Research, 2008
Decision Tree Construction from Knowledge Discovered by Rough Sets ...
Vrbka, Jasna, Dalbelo Bašić, Bojana
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An Integration of Cloud Transform and Rough Set Theory to Induction of Decision Trees

Fundamenta Informaticae, 2009
Decision trees are one of the most popular data-mining techniques for knowledge discovery. Many approaches for induction of decision trees often deal with the continuous data and missing values in information systems. However, they do not perform well in real situations.
Song, Jing, Li, Tianrui, Ruan, Da
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NB Tree Based Intrusion Detection Technique Using Rough Set Theory Model

2019
Security is an important need for any organization to establish trust and consequently prevents misuse. Intrusion detection system (IDS) is a defense mechanism that strives to differentiate between legitimate and malicious activities with intent to secure the resource and henceforth establish trust. Due to this importance significant amount of research
Neha Gupta, Ritu Prasad, Praneet Saurabh, Bhupendra Verma   +3 more
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An Optimized Parallel Decision Tree Model Based on Rough Set Theory

2008
This paper presents an optimized parallel decision tree model based on rough set theory, first the model divides global database into subsets, then using the intuitive classification ability of decision tree to learn the rules in each subset, at last merge each subset's rule set to obtain the global rule set.
Xiaowang Ye, Zhijing Liu
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Notice of Retraction: Algorithm of constructing decision tree based on rough set theory

2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, 2010
Problem of classification is the main research target of many algorithms in machine learning and data mining. Of all the algorithms, decision tree is more preferred by researchers due to its clarity and readability. Attribute of little value domain is the important feature of training dataset of decision trees.
null Baowei Song, null Chunxue Wei
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