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Bayesian optimization has been demonstrated as an effective methodology for the global optimization. However, it suffers from a computational bottleneck that the inference time grows cubically with the number of observations. In this paper, a Bayesian optimization based on the data-parallel approach is proposed to alleviate this problem. Firstly, an improved geometry motivated clustering algorithm...
Greenhouse climate is difficult to model as a complex nonlinear system. The solution to the problem of describing the relation between inputs and outputs is using T-S fuzzy modeling which could transform a nonlinear system into several linear systems. During the transition, c-means clustering is used to cluster the variable of inputs and outputs. The result of clustering determines the compose of...
The biological signals collected by the multi-electrode array are contaminated by heavy noise signals. How to quickly classify the original action potential from the measured noisy signals accurately is the basis of researches in the field of neuroscience. In this paper, we analyze the characteristics and shortcomings of Wave-clus sorting algorithm, and present a novel sorting algorithm to solve the...
The Big data analytics gives new chances to the enterprises to enhance their management and manufacturing levels. A solution with case study is proposed to accomplish deep-level quality management based on big data analytics. First, the implementation of big data analytics based on industrial process data is illustrated with case study illustration. Through the analysis and feature extraction of off-line...
Image segmentation has always been an important research direction in the field of images processing, however, due to the long cycle of algorithm, the image segmentation techniques have never been widely applied. According to the problem above, a image segmentation algorithm of Gaussian Mixture Model (GMM) based on Map/Reduce is proposed to improve the real-time performance. Firstly, the architecture...
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