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Application of the rough set theory and BP neural network model in disease diagnosis is discussed in this paper. BP neural network model was established, and trained by the real diagnosis data of nephritis, utilizing the neural network toolbox in Matlab software. In this way we were able to provide a good solution to the problem of diagnose for new patients based on their chemical test data. By data...
Early-warning system of China's real estate is still in the development of a sound stage, and there are following two main aspects. Firstly, the selection of indicators is to be improved. Secondly, predictive capability of the turning point about the real estate business cycle is to be improved. Based on the above-mentioned problems, the Rough-GA-BP model proposed is applied to the real estate early-warning...
Application of constructon supply chain can increase construction enterprises' profits and enhance the core competitiveness. Under the condition of construction supply chain, the correct evaluation and selection of partners are the key to success. This paper establishes a partner evaluation system and proposes a kind of artificial intelligence method for the partners evaluation, combining with the...
An intelligent method on short-term prediction on water bloom of BP neural network based on rough set and wavelet analysis is proposed in this paper. This method analyzes factors of effecting the outbreak of water bloom, and these many factors which were processed by reduction method based on rough set were used as input information of the prediction model; after analyzing the main input information...
Based on rough set and basic theory of data fusion, the data fusion algorithm combining rough set theory and BP neural network is studied. Since rough set theory can effectively simplify information, cut down the tagged dimension . This paper will be rough set theory and neural networks combined, using channel capacity of knowledge relative reduction algorithms to simplify the input information. Rough...
For implementing supply chain management effectively, it is very important to select suppliers. So a supplier selection model which could evaluate the performance of suppliers was proposed based on rough sets and BP neural network from the perspective of knowledge discovery and data mining at first. Then, the calculation and analysis process of the model was given and discussed. The performance decision...
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