Data extracting and predicting model establishing method for environment monitoring

Abstract

The invention discloses a data extracting and predicting model establishing method for environment monitoring. The method comprises the environment monitoring data extracting step and the environment predicting model establishing step. Data extracting logic and dispatching schedule can be customized, and user operation is facilitated. The standard and uniform regulation of environment data is established, and the environment data is unified. Scientific data effectiveness verification is adopted in the extracting process, and the data effectiveness of an environment data center is improved. The data are fully utilized through the data mining process of the environment monitoring data. An environment model is established through the extracted data, and support can be provided for an environment-friendly strategy.

Description

technical field [0001] The present invention relates to multi-source heterogeneous data extraction and model building methods, specifically, to a multi-source heterogeneous data extraction method applied to environmental monitoring, and an environmental prediction model established on the basis of data extraction, so as to provide environmental protection decision-making Technology that provides data support. Background technique [0002] With the development of computer information technology and the establishment of information systems in various industries, human society has entered the information age, and information systems generate a large amount of data every moment. Especially with the rapid development of Internet of Things technology and the continuous generation of a large amount of real-time data, how to effectively manage and utilize massive data has become an important research topic of current informatization. The Internet of Things has been widely used in e...

AI Technical Summary

Problems solved by technology

[0003] 1. Data extraction logic and scheduling plan are fixed, not easy to maintain, and difficult to understand and operate for non-IT professionals

2. There is a lack of standard and unified information management of environmental data, and data inconsistency often occurs

3. The lack of scientific data validity verification in the extraction process has resulted in a large amount of data being invalid, seriously affecting the reliability of the data

4. The environmental monitoring data only stays in the collection and display stage, lack of data mining process, resulting in the data not being fully utilized

5. For the extracted data, there is a lack of steps to establish an environmental model, which cannot provide support for environmental protection decisions

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