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With the development of distribution network, and the intelligentization of terminal devices in distribution automation system, it becomes key point that research the task allocation method and self-adaptive task allocation model from perspective of distributed system to improve the utilization of the devices in whole distribution network and optimize the system performance on intelligent terminal...
With the development of distribution networks, both the type of business and the amount of data transmitted in the network are gradually increasing. In order to guarantee the real-time and reliability transmission of the business data, it has drawn great concern about how to distribute the network resources reasonably in the distribution communication networks. In this paper, we propose a virtual...
Global uncertainty and sensitivity analysis(UA-SA) can be applied to quantify the influence of uncertain model inputs on the response variability of a power system model. Uncertainty and sensitivity analysis algorithms are becoming an efficient tool for the understanding, application and development of mathematical and computer models. In this paper, Morris and Extended Fourier Amplitude Sensitivity...
Micro-blogging is becoming increasingly prevalent in global world, which not only subverts the traditional means of communication, but also changes the entire media environment. Discovery of micro-blog community is of great value. However, the classical community discovery algorithms are generally based on links or interests only to recognize the traditional single community and limited to detect...
Recently, genome‐wide association studies (GWAS) have identified over 12 single‐nucleotide polymorphisms (SNPs) associated with bladder cancer risk in populations of European descent. However, effects of these SNPs in bladder cancer have not been systemically evaluated in the Chinese population. We conducted association studies of 12 SNPs in a Chinese population of 184 cases and 962 controls. These...
Stream data can often show abrupt changes over time. It is very critical to analyze and predict the trends autonomously on time in the continuous, high speed and variable stream data environment. In this paper, we discuss the Autonomous Real-time Clustering Evolution Tracking algorithm which integrate the fractal cluster technique, self-adaptive sampling technique with the restriction of computing...
Dimensionality reduction has long been an active research topic within statistics, pattern recognition, machine learning and data mining. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. In this paper, we transform the attribute selection problem into the optimization problem which...
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