Abstract. Fuzzy C-Means (FCM) algorithm is a kind of widely used clustering algorithm, which is widely used in pattern recognition, image processing, medical research and other fields. But FCM doesn't have better performance suppressing noise. A parallel clustering algorithm based on MapReduce is proposed in this paper, which combines Clonal Selection Algorithm and the algorithm uses intelligent optimization method to optimize the initial clustering center, and makes use of the global search ability of CSA to make the algorithm more robust. The algorithm process is designed to conform to the MapReduce programming model and it has the ability of dealing with large-scale dataset. The experiments prove that parallel Clonal Selection Algorithm-Fuzzy C-Means (CSA-FCM) can improves the searching performance and the noise immunity and has high speed up and scalability.
Abstract-Nonlinear model simplification is an important part of many applications, such as flow control, optimization and statistical analysis. In this article, we summarize the POD-DEIM method to solve the nonlinear system of the truss frame .And use an example of a clamped beam to illustrate the DEIM specific simplification process with images which can intuitively observe the image of the specific selection process. The application of the method to the truss frame to verify the correctness of the study. The results show that POD-DEIM is able to approximate fully nonlinear behavior of geometrically nonlinear finite element models with good accuracy.
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