Dingsheng Wan

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Traditional data mining algorithm had limited capacity at short-term hydrological forecasting with low accuracy, and made little use of the error between the data set and the results to correct the results. Considering of the traditional hydrology predictive algorithm combined only with the external associated factors, but had not fully excavated the(More)
Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similarity of the MTS is obtained by synthesizing each of the(More)
Pre-computation of data cube can greatly improve the performance of OLAP (online analytical processing). There are a lot of effective pre-computation methods of data cube. But in practice, appropriate pre-computation method for the characteristics of data set plays a crucial role in improving the efficiency of data cube pre-computation. In view of the(More)
Current algorithms that utilize water index to extract water information from high resolution remote sensing image are inadequate in that it is difficult to determine the optimal thresholds, the result of water boundary is not satisfactory and prone to error. We propose a new algorithm which combines image segmentation algorithm based on MRF model with(More)
Large amount of hydrological data set is a kind of big data, which has much hidden and potentially useful knowledge. Hydrological prediction is important for the state flood control and drought relief. How to forecast accurately and timely with hydrological big data becomes a big challenge. There are some forecasting techniques used widely. However, they(More)
—In this paper, we evaluate some techniques for the time series similarity searching. Many distance measures have been proposed as alternatives to the Euclidean distance in the similarity searching. To verify the assumption that the combination of various similarity measures may produce more accurate similarity searching results, we propose an multi-measure(More)