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With the increase of the photoelectric scale, data with high quality is a necessary prerequisite for accurate prediction. The least square fitting method is one of the typical methods of abnormal data screening, which has not been widely used in screening photovoltaic power. In this paper, Three methods for outfielders with the abnormal screening of single point, short-term continuous outliers, long-term...
In embedded Linux applications, the power failure may lead to the abnormity of the FAT file system. An effective repairing algorithm for the FAT file system was designed and implemented in this paper. The scanning files method based on tree structure was utilized as the core of repairing algorithm. FAT tables and cluster markers were adopted to improve the memory efficiency. Furthermore, the abnormities...
To improve the first word dictionary with hash structure and the reverse maximum matching segmentation algorithm, the last word dictionary based on Hash structure which records word length is designed. By utilizing the reverse maximum matching methods, it realizes the intended objective of improving the speed and reducing the ambiguities rate of word segmentation. This essay explains the design principle...
Whether distribution system can rebility operate is mostly decided by the network structure, a reasonable grid structure comes from power network planning. Power network planning is full of the randomness and uncertainty, we can't get accurate information of distribution transformer from planning grid, which causes some difficulties in distribution system reliability assessment. This paper makes some...
Particle swarm optimization algorithm has been widely used because of its advantages such as simple principle, easy to programming, suitable for parallel computing and others. Calculation example shows that particle swarm optimization can be well used to solve optimal allocation of water resources, availability and better than the dynamic programming algorithm accuracy.
Artificial immune algorithm is a new bionic algorithms, it becomes a hot spot. Artificial immune algorithm has self-adjustment ability and adaptive capacity of the environment and can deal with complex optimization problems in parallel. Immune algorithm takes concentration and affinity as standards. Thus low concentration, high-fit individuals have more breeding opportunities. As attention to the...
To reduce the heavy computation load of maximum likelihood parameter estimator for passive synthetic arrays(pasaML), a fast algorithm is proposed. This method combines Metropolis-Hasting Sampling with pasaML method, resulting in a frequency-azimuth joint estimation method(called MH-pasaML) to estimate the frequencies and directions of multiple sources at the same time. The method regards the power...
Manifold learning algorithms, such as ISOMAP, LLE, Laplacian Eigenmaps, LTSA and so on, are designed to map nonlinear high dimensional data into the low dimensional space. The key of their success is to select a suitable neighborhood parameter. However, it is difficult to determine a proper neighborhood size for most of manifold learning methods, in particular for non-uniform data sets. An adaptive...
During the product configuration design stage, it is important to find useful knowledge to reduce the dedicated efforts of engineers. To fulfill this task, the quality and interestingness of knowledge plays the decisive part. This paper utilizes Apriori algorithm to mine rules from historical data base. In addition the traditional criterions support and confidence, the criterion interestingness is...
The purpose of Web text mining is to find the potential knowledge from the immensity text information on the Internet. In this paper, a novel Web text mining method is proposed based on semantic polarity analysis. Firstly, the model for Web text mining is presented by using semantic polarity analysis, which includes three main parts: data acquisition, feature sentences analysis and semantic polarity...
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