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Outlier detection is an important issue in data mining and knowledge discovery. The aim is to find the patterns that deviate too much from others. In this paper, a universal outlier detection method based on normalized residual is proposed. Different from previous methods, the residual of a pattern is calculated corresponding to its nearest normal patterns, so that the interaction between outliers...
With a growing amount of data, a viable solution is to use a cluster consisting of a large of computers for parallel processing, and Hadoop parallel computing platform is a typical representative. Clustering analysis for time series data is one of the main methods mining time series data, however, general clustering algorithms can't perform clustering for time series data directly since series data...
Based on data mining, the main impact factors of urban life water consumption are made gray relational analysis with the water consumption. The main driving factors of urban life water consumption are discussed. By the gray forecasting of the development trends of the main impact factors, a grey prediction of GM (0, N) model on urban life water is established. An instance proves to fit the data better...
The multi-cycle inventory problems have been studied under two main assumptions. Continuous review assumption where an order can made at any time depending on inventory position and periodic review assumption where an order can be initiated only at discrete time epochs. In this study, we analyze a multi period inventory problem that falls under neither of these two assumptions. In this case we consider...
In order to reduce the influence of the jitter of hard real-time task caused by scheduling to the stability and reliability of device-level operation system, a model with preemption segment threshold-RJPS is presented. According to the effect on jitter and latency brought by threshold and the analysis of the scheduling on this model, two minimum threshold assigned algorithms are designed. One of them...
Graphs are popularly used to model structural relationships between objects. In many application domains such as social networks, sensor networks and telecommunication, graphs evolve over time. In this paper, we study a new problem of discovering the subgraphs that exhibit significant changes in evolving graphs. This problem is challenging since it is hard to define changing regions that are closely...
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