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Eutrophication has been considered as one of the most serious water quality problems of reservoirs in Taiwan. The back-propagation artificial neural network (ANN) was used to predict the water quality variation of the LungLuanTan Reservoir in southern Taiwan in current research. Three mathematical models were established and to predict the variation of parameters including total phosphorus (TP), secchi...
Identity authentication is the most important line in the network security. In order to improve authentication security and efficiency, this paper combined iris recognition technology and smart card and then analyzed the security of the scheme. As can be seen from the analysis, it can effectively protect the user information and resist replay and masquerade attack.
This paper focus on continuous K-nearest neighbor (CKNN for short) query and propose a query method based on R-Tree and Quad Tree (QR-Tree) to support continuous K-nearest neighbor query for moving objects, in which the main idea is to use a QR-Tree to divide the static spatial space for the moving objects. In the interested region, it uses the QR-Tree and hash tables as an index to store the moving...
Aiming at the problem of lower accuracy of vibration fault diagnosis system for turbo-generator set, a new diagnosis method based on self-organized fuzzy neural network is proposed and a self-organized fuzzy neural network system is structured for diagnosing faults of large-scale turbo-generator set in this paper by associating the fuzzy set theory with neural network technology. Especially, an effective...
In modern communication system, it??s important to use the channel efficiently and economically. So using low rate coding of high quality by extracting proper speech parameters has been a hotspot of relevant research. In this paper, we analyze the parameters of CELP codec based on LPA, do research on the redundancy of speech sources in different languages and genders. By studying the statistic features...
We present a chaos forecasting system for chaotic time series. After reconstructing the phase space of a chaotic time series, we partition the phase space into some clusters using the fuzzy c-means clustering algorithm. We learn the cluster to which future values will most likely belong. This allows us to make short-term forecasting of the future behavior of a time series by back-propagation network...
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