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自动化工业论文 求翻译 谢谢啦
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An integrated cloud can be used to express the conversion from quantitative to qualitative data as the fuzziness and randomness mapping from the quantitative to the qualitative are effectively integrated by the cloud modeling theory. The space fusion structure based on cloud modeling is shown in Fig. 4 In Fig. 4, n represents the number of spaces that all the sensors are included in the space fusion structure. The data level consists of Drop(x1i), . . . , Drop(xni ) (i = 2, 3, . . . ,m),where m is the number of sensors in each space. The sampling values are simultaneously obtained from the multiple sensors in different spaces. In the feature level, the cloud droplets far away from the center value are eliminated while the others are regarded as the input to be transformed into the final cloud digital features (E p x , E p n , H pe ), (p = 1, 2, . . . , n) by thebackward cloud generator. In the decision level, the fusion rule can be implemented in a practical algorithm based on vectorization using the weighted average method [24] D. Space–Time Fusion Structure Based on Cloud Modeling Space fusion based on cloud modeling is mainly used to fuse the data from the sensors located in different spaces simultaneously. However, the simple space fusion without considering the time-domain characteristics of the target is insufficient for the description of its feature. From the perspective of time–space fusion, not only the space informationof the sensors is fused, but also the time-domain information is considered to achieve more comprehensive identification and decision making of the target, so that the loss of information is reduced and the recognition rate of the data fusion system improved [25]. The space–time fusion structure based on cloud modeling is shown in Fig. 5. III. OXYGEN CONTENT MEASUREMENT USING DATA FUSION METHOD BASED ON CLOUD MODELING |
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