Research on water quality data classification based on weighted Naive Bayes
In order to better implement the water environmental management policies, water quality evaluation is the basic step, that is to reasonably divide it into specific water quality category according to multiple water quality parameters in a certain water area.Aimed at this problem, an improved Naive B...
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China InfoCom Media Group
2022-03-01
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| Series: | 物联网学报 |
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| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00255/ |
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| _version_ | 1841533776497213440 |
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| author | Zhihao FANG Zhengquan LI Mingwei ZHANG |
| author_facet | Zhihao FANG Zhengquan LI Mingwei ZHANG |
| author_sort | Zhihao FANG |
| collection | DOAJ |
| description | In order to better implement the water environmental management policies, water quality evaluation is the basic step, that is to reasonably divide it into specific water quality category according to multiple water quality parameters in a certain water area.Aimed at this problem, an improved Naive Bayes classification method was proposed, which endowed different attributes with different weights, weakened the assumption of Naive Bayes conditional independence, and made the classification result closer to the actual category.Firstly, referred to the data released by the national surface water quality automatic monitoring station, 500 water quality data were selected as samples, and an evaluation system with four indicators was established, including dissolved oxygen, permanganate index, ammonia nitrogen and total phosphorus.And then, the improved Naive Bayes classification method was used to learn and evaluate the samples, and its classification performance by the five fold cross validation method was verified.The results show that the accuracy, precision, recall and F1 value of the improved Naive Bayes classification method reach 96.0%, 95.9%, 93.8% and 94.8% respectively, with higher performance index of water quality data classification compared with other Naive Bayes classification method, which can provide some reference for the problem of water quality data classification encountered in actual engineering. |
| format | Article |
| id | doaj-art-003529551b29453c954f60197770e4c3 |
| institution | Kabale University |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2022-03-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-003529551b29453c954f60197770e4c32025-01-15T02:53:34ZzhoChina InfoCom Media Group物联网学报2096-37502022-03-01611312259649026Research on water quality data classification based on weighted Naive BayesZhihao FANGZhengquan LIMingwei ZHANGIn order to better implement the water environmental management policies, water quality evaluation is the basic step, that is to reasonably divide it into specific water quality category according to multiple water quality parameters in a certain water area.Aimed at this problem, an improved Naive Bayes classification method was proposed, which endowed different attributes with different weights, weakened the assumption of Naive Bayes conditional independence, and made the classification result closer to the actual category.Firstly, referred to the data released by the national surface water quality automatic monitoring station, 500 water quality data were selected as samples, and an evaluation system with four indicators was established, including dissolved oxygen, permanganate index, ammonia nitrogen and total phosphorus.And then, the improved Naive Bayes classification method was used to learn and evaluate the samples, and its classification performance by the five fold cross validation method was verified.The results show that the accuracy, precision, recall and F1 value of the improved Naive Bayes classification method reach 96.0%, 95.9%, 93.8% and 94.8% respectively, with higher performance index of water quality data classification compared with other Naive Bayes classification method, which can provide some reference for the problem of water quality data classification encountered in actual engineering.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00255/water quality evaluationNaive Bayesive fold cross validationperformance index |
| spellingShingle | Zhihao FANG Zhengquan LI Mingwei ZHANG Research on water quality data classification based on weighted Naive Bayes 物联网学报 water quality evaluation Naive Bayes ive fold cross validation performance index |
| title | Research on water quality data classification based on weighted Naive Bayes |
| title_full | Research on water quality data classification based on weighted Naive Bayes |
| title_fullStr | Research on water quality data classification based on weighted Naive Bayes |
| title_full_unstemmed | Research on water quality data classification based on weighted Naive Bayes |
| title_short | Research on water quality data classification based on weighted Naive Bayes |
| title_sort | research on water quality data classification based on weighted naive bayes |
| topic | water quality evaluation Naive Bayes ive fold cross validation performance index |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00255/ |
| work_keys_str_mv | AT zhihaofang researchonwaterqualitydataclassificationbasedonweightednaivebayes AT zhengquanli researchonwaterqualitydataclassificationbasedonweightednaivebayes AT mingweizhang researchonwaterqualitydataclassificationbasedonweightednaivebayes |