Semi-supervised and semi-learned atmospheric pollutant system

An air pollutant, semi-supervised technology, applied in the field of air pollutants, can solve the problems of inaccurate assessment and different air pollution levels, and achieve the effect of improving the accuracy of control

CN111896681AInactive Publication Date: 2020-11-06NANCHANG INST OF TECH
9 Cites 1 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2020-11-06
Estimated Expiration
Not applicable · inactive patent

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a semi-supervised and semi-learned atmospheric pollutant system and relates to the technical field of atmospheric pollutants, and the system comprises a data processing module,a data preprocessing module, a learning classification module, a comprehensive analysis module, an auxiliary arrangement module and a computer terminal module. The output end of the data processing module is electrically connected with the input end of a data preprocessing module; the output end of the data preprocessing module is electrically connected with the input end of a learning classification module; data can be acquired and collected through the data acquisition module. Dimensionality reduction processing of the data is realized through the data preprocessing module; the acquired data parameters can be transmitted to the data classification module; data classification is achieved through the learning classification module, then data analysis processing is achieved through the comprehensive analysis module, the analyzed data is sorted through the auxiliary sorting module, and then watching monitoring of the sorted data can be achieved through the computer terminal module.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the technical field of air pollutants, in particular to a semi-supervised and half-learning air pollutant system. Background technique

[0002] Atmospheric environment refers to the physical, chemical and biological characteristics of the air on which organisms live. Harmful gases such as ammonia, sulfur dioxide, carbon monoxide, nitrogen compounds and fluorides discharged from human life or industrial and agricultural production can change the composition of the original air, and Cause pollution, cause global climate change, destroy ecological balance;

[0003] Semi-supervised learning (Semi-Supervised Learning, SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method that combines supervised learning and unsupervised learning. Semi-supervised learning uses a large amount of unlabeled data, and Use labeled data to carry out pattern recognition work. When semi-supervised learning is...

Examples

Embodiment Construction

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention.

[0021] refer to Figure 1-3 , a semi-supervised and semi-learning air pollutant system, including a data processing module 1, a data preprocessing module 2, a learning classification module 3, a comprehensive analysis module 4, an auxiliary sorting module module 5, a computer terminal module 6, and a data processing module 1 The output end of the data preprocessing module 2 is electrically connected to the input end of the data processing module 1. The data processing module 1 includes an air pollutant concentration acquisition device. The air pollutant concentration detection device includes a base 7. The side wall of the base 7 is provided with threaded holes. The b...