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This part of the paper introduces a comparison of VAR-IM algorithm with modern techniques used for missing data analysis. Quantitative methods are usually developed based on some fundamental understanding of the statistical analysis of the missing data. Various types of quantitative methods such as K nearest neighbour (KNN), (Multivariate Autoregressive state-Space) MARRS package and EM algorithm...
The classical mean shift algorithm is easy to pass into local maxima, which is caused by the lack of appropriate target model updating mechanism. In this paper, a SIFT-based mean shift algorithm is proposed, which can be used for continuous vehicle tracking in complex situations, such as the shape and the illumination of the vehicle object change. In our algorithm, the mean shift algorithm is utilized...
Facility location optimization is a common problem in the urben infrastructural constructions (such as hospital, school, park, and community service), this kind of problems was named as facility location allocation. The Location-Allocate(LA) Model is just developed due to handlding these problems. In this study, we review the algorithms that were applied to facility location model. Although there...
In view of that the two-dimensional chaotic sequence only holds a low limited-accuracy, as well as the linear complexity of linear feedback shift register generated-sequence is limited, also the generated-sequence is easily decoded. This paper proposes one kind of the two-dimensional mix chaos algorithm for image encryption based on uniting the ultra-chaos switch system and the linear feedback shift...
The traditional ideas and solutions focusing on network security problems are unsuitable for wireless sensor networks in which storage space and computing power are limited. In order to reduce cost in processor of sensor node, this paper proposes a new embedded encryption algorithm (AEEA) based on linear feedback shift register (LFSR). Because the algorithm is only composed by some basic operations...
With regards to the characteristics of work conditions on oil pipeline, such as complicated changes, lack of prior knowledge and difficult classification, simulated annealing K-means clustering algorithm are proposed. Samples, which include various work condition changes of oil pipeline, are selected from pressure data collected in field. In order to analyze data conveniently, each group of raw data...
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