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Community detection is an important research issue in complex network mining. In this paper, firstly, we define central nodes, called Extended Local Max-Degree (ELMD) nodes in a complex network. All the central nodes are used for the community expanding. We also prove that ELMD method is more precise and dispersed than local max-degree method in the real datasets. Secondly, we propose an improved...
Since fault diagnosis of blast furnace is very important in manufacturing, in this paper, a new strategy based on NN-DPSO-SVM is proposed to solve it. Using the nearest neighbor principle deletes the useless samples so that the training set is pruned. A modified discrete particle swarm optimization is applied to optimize the feature selection and the SVM parameters so that the algorithm can improve...
Three-dimensional spatial overlap analysis (3DSOA) has become a bottleneck in the development of three-dimensional Geographic Information System (3DGIS). Three-dimensional spatial overlay analysis method for vector polyhedrons is the key problem of three-dimensional spatial overlap analysis which still lacks complete solutions. This paper proposes a method for three dimensional spatial vector polyhedrons...
Community detection in complex networks is a topic of considerable recent interest within the scientific community. For dealing with the problem that genetic algorithm are hardly applied to community detection, we propose a genetic algorithm with ensemble learning (GAEL) for detecting community structure in complex networks. GAEL replaces its traditional crossover operator with a multi-individual...
This paper extracts automotive marketing information, constructs data warehouse, adopts an improved ID3 decision tree model and an association rule model to do data mining, and then obtains prediction information of automotive customers' behavior. Experimental and comparative results verify the validity and accuracy of the prediction results.
Data missing in data pretreatment has a serious effect on the accuracy of subsequent analysis results in data mining. In this paper, the cause of data missing and the corresponding effect on data mining were discussed. Then the missing pattern and the application limitation of traditional missing value estimation were analyzed as well. Finally, the estimation algorithm of missing value in MAR (missing...
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