Intelligent time-space data clustering method

Abstract

The invention belongs to the field of multi-disciplinary and technology cross-combination. At the first step, data collection is performed; to be specific, a monitoring station uses a gas sensor to monitor the sulfur dioxide and nitrogen dioxide in air in real time and transmits the monitored nitrogen dioxide and sulfur dioxide concentrations through an application interface in a data collection system. At the second step, data analysis is performed. At the third step, interpolation calculation is performed. And at the fourth step, online data fusion is performed; to be specific, offline prediction simulation is performed on a time-space data model by using complete data after interpolation as sample data and online prediction of the nitrogen dioxide and sulfur dioxide concentration data is realized by using a forgetting factor recursive algorithm. The gas sensitive material of the gas sensor used by the monitoring station is a double-layer graphene / graphite-phase carbon nitride / tin oxide sensor and thus the response sensitivity is high and detection limit is low, so that the precision of data collection is improved substantially and thus the real-time online prediction of sulfur dioxide and nitrogen dioxide more accurate.

Description

technical field [0001] The invention belongs to the field of cross-combination of multiple disciplines and technologies, and in particular relates to an intelligent aggregation method of spatio-temporal data. Background technique [0002] Sulfur dioxide and nitrogen dioxide are the main pollutants in the atmosphere. With the rapid development of urbanization and the continuous expansion of the scale of transportation in my country, a large amount of sulfur dioxide and nitrogen dioxide that are harmful to the environment are discharged into the atmosphere, causing serious air pollution. Not only It has brought great harm to the earth environment on which we live, and even threatened the health of human beings. It is of great practical significance to predict sulfur dioxide and nitrogen dioxide. [0003] Although the existing methods for aggregating and predicting sulfur dioxide and nitrogen dioxide data can realize the prediction of nitrogen dioxide and sulfur dioxide to a cer...

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Problems solved by technology

[0003] Although the existing methods for aggregating and predicting sulfur dioxide and nitrogen dioxide data can realize the prediction of nitrogen dioxide and sulfur dioxide to a certain extent, due to the low response sensitivity of the sensor during the data collection process of sulfur dioxide and nitrogen dioxide, the detection The high lower limit concentration greatly affects the accuracy of data collection, which makes the prediction of sulfur dioxide and nitrogen dioxide inaccurate. In order to improve the sensor response sensitivity and reduce the lower limit of detection, people solve these problems by changing the gas-sensitive material, which is the core component of the gas sensor. problem, but existing sensors often prepare single-layer graphene as a gas-sensing material, but due to the lack of dangling bonds and zero bandgap width of single-layer graphene, the gas-sensing material prepared by graphene is not ideal, and the existing Another gas-sensing material made of metal oxide requires a higher temperature to respond to the detected gas, and both gas-sensing materials made of graphene and metal oxide have a high detection limit for sulfur dioxide and nitrogen dioxide. low response sensitivity

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