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River temperature prediction is an important project in the environmental impact assessments. Based on river temperature data of Yichang hydrological station in the middle reach of the Yangtze River, BP neural network model based on particle swarm optimization (PSO) was applied to predict river temperature of the Yangtze River. PSO was used to optimize the initial weights of nodes in BP neural network...
This paper uses neural network to process acquired digital signals on line, realizing automotive recognition to and thickness analysis of three kinds of gas. This method can automatically measure and show working temperature of air-sense organ, and according to a given temperature adjust the temperature, which decreases effect of intercross sensitivity and improves accuracy of measurement results.
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