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Computer software size continues to grow recently. But it is difficult to collect information to support software development and maintenances. Data mining technology can be used to automatically discover knowledge from software testing data. It is helpful to increase software developing process and improve software quality. At first, correlation analysis is adopted to study the relevance among the...
This study is to explore effect and significance of data mining technology (DMT) used in excavating prevention and treatment experience of infectious diseases from famous herbalist doctors (FHDs). DMT methods such as cluster analysis and association rules was applied to the study on FHDs literature on preventing and treating influenza, dysentery, tuberculosis, viral hepatitis and other infectious...
To address the problems of the rule redundancy and the long algorithm execution time in the process of mining one airborne radar intelligence database by the fuzzy association rules algorithm, this paper define a new QL-implicator based fuzzy support measure in order to enhance the recognition probability of the positive association rules and introduce the fuzzy conditional entropy measure (CE-measure)...
Notice of Violation of IEEE Publication Principles"An Efficient Mining Algorithm for Top K Strongly Correlated Item Pairs"by Qiang Li and Yongshi Zhangin the Proceedings of the 4th International Conference on Internet Computing for Science and Engineering, December 2009, pp. 152-155After careful and considered review of the content and authorship of this paper by a duly constituted expert...
Accurate operation data is the foundation of system identification and system analysis. Based on the characteristic of operation parameters in power plant, the method of data selection and data processing was discussed and the correlation analysis of operation parameters was introduced to operation optimization. The correlation coefficients were proposed to measure the related degree between operation...
The rational determination of operation optimization values is very important to economical analysis and operation optimization in power plant. Based on the correlation of operation data, the economical analysis and operation optimization based on data mining was proposed to guide the operation optimization. The basic structure of economical analysis and operation optimization based on data mining...
The determination of the optimal oxygen content is very important in power plant operation optimization. Due to the disadvantages of traditional ways, this paper proposed a new method to decide the optimal oxygen content based on incremental updating data mining. This method could determine the optimal oxygen content and related frequent items by fuzzy quantitative association rule mining algorithm...
As the development of electric industry, more and more real-time data is sent to databases by data acquisition system and large amounts of data are accumulated. Abundant knowledge exists in those historical data. It is meaning to analyze those historical data in electric industry and find useful knowledge and rules from the mass of data to provide better decision support and better adjustment guidance...
Coal-fired boiler combustion system in power plant is a complex multi-input and multi-output plant with strong nonlinear and large time-delay. The determination of the optimal excess air coefficient is very important for economical analysis and operation optimization and it is a difficulty and bottleneck for operation optimization in power plants. Based on the association characteristic in electric...
The equipments in power plant are closely related and interacted, and the relationships among the equipments are manifested by operation data. According to the actual operation data, the potential associations can be found and applied to guide the operation optimization in power plant. The characteristics of operation data and the methods of correlation analysis were discussed in detail to estimate...
Given a user-specified minimum correlation threshold and a relational table, the problem of mining all-strong correlated pairs is to find all attribute value pairs with Pearson's correlation coefficients above the minimum correlation threshold. However, algorithms developed for transaction database will generate invalid candidate pairs due to fundamental property of the itemsets in relational table...
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