Study on environmental monitoring classification system based on improved bayesian algorithm
में बचाया:
| में प्रकाशित: | Journal of Physics: Conference Series vol. 2813, no. 1 (Aug 2024), p. 012011 |
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| मुख्य लेखक: | |
| प्रकाशित: |
IOP Publishing
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| विषय: | |
| ऑनलाइन पहुंच: | Citation/Abstract Full Text - PDF |
| टैग: |
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3090935726 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1742-6588 | ||
| 022 | |a 1742-6596 | ||
| 024 | 7 | |a 10.1088/1742-6596/2813/1/012011 |2 doi | |
| 035 | |a 3090935726 | ||
| 045 | 2 | |b d20240801 |b d20240831 | |
| 100 | 1 | |a Guo, Xiaoyan | |
| 245 | 1 | |a Study on environmental monitoring classification system based on improved bayesian algorithm | |
| 260 | |b IOP Publishing |c Aug 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The commonly used methods for classifying water quality data are based on water quality parameters. The naive Bayesian classification method can be applied to substitute different evaluation criteria and selected water quality parameters for different water bodies. Compared to other water quality data classification methods, naive Bayesian classification methods have advantages such as simple calculation, high classification accuracy, and strong universality. However, this method overlooks the correlation between various water quality parameters and categories. To address the issues of poor universality, computational complexity, and low accuracy of traditional water quality data classification methods, a water quality data classification method based on weighted naive Bayes is proposed. This method comprehensively considers the impact of water quality attributes and their values on the classification results and replaces the original naive Bayes with weighted attribute conditional probabilities to make the classification results as close as possible to the actual category of the sample. The results indicate that this method exceeds 94% accuracy and can be directly utilized as a water quality classification module in water quality monitoring systems. | |
| 653 | |a Water quality | ||
| 653 | |a Quality management | ||
| 653 | |a Algorithms | ||
| 653 | |a Accuracy | ||
| 653 | |a Methods | ||
| 653 | |a Classification | ||
| 653 | |a Bayesian analysis | ||
| 653 | |a Parameters | ||
| 653 | |a Environmental monitoring | ||
| 773 | 0 | |t Journal of Physics: Conference Series |g vol. 2813, no. 1 (Aug 2024), p. 012011 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3090935726/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3090935726/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |