Evaluation Model of Rural Ecological Environment Governance Quality Using Decision Tree Algorithm
In rural economic development and environmental protection, assessing the quality of rural ecological environment management is critical. This paper uses a decision tree algorithm to assess the quality of rural ecological environment governance based on an in-depth review of related literature. The...
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Veröffentlicht in: | Mobile information systems 2022-07, Vol.2022, p.1-10 |
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description | In rural economic development and environmental protection, assessing the quality of rural ecological environment management is critical. This paper uses a decision tree algorithm to assess the quality of rural ecological environment governance based on an in-depth review of related literature. The data are recursively processed from top to bottom in this paper, and a set of disordered and irregular examples is summed up into a set of classification rules represented by a tree structure, and an evaluation model is obtained, in which all pollution parameters are taken as environmental quality factors. It effectively overcomes the traditional environmental quality prediction model’s inflexibility and inaccurate boundary value. The simulation results show that the quality evaluation method in this paper has a classification accuracy of 96.82 percent and a recall rate of 96.63 percent, which is higher than the comparison algorithm. The experimental results support the effectiveness and applicability of the decision tree-based method for assessing the quality of rural environmental governance. This model can not only assist researchers in correctly analyzing and mastering the migration and change rules of pollutants in the air but also has promising social and economic implications. |
doi_str_mv | 10.1155/2022/5622757 |
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This paper uses a decision tree algorithm to assess the quality of rural ecological environment governance based on an in-depth review of related literature. The data are recursively processed from top to bottom in this paper, and a set of disordered and irregular examples is summed up into a set of classification rules represented by a tree structure, and an evaluation model is obtained, in which all pollution parameters are taken as environmental quality factors. It effectively overcomes the traditional environmental quality prediction model’s inflexibility and inaccurate boundary value. The simulation results show that the quality evaluation method in this paper has a classification accuracy of 96.82 percent and a recall rate of 96.63 percent, which is higher than the comparison algorithm. The experimental results support the effectiveness and applicability of the decision tree-based method for assessing the quality of rural environmental governance. This model can not only assist researchers in correctly analyzing and mastering the migration and change rules of pollutants in the air but also has promising social and economic implications.</description><identifier>ISSN: 1574-017X</identifier><identifier>EISSN: 1875-905X</identifier><identifier>DOI: 10.1155/2022/5622757</identifier><language>eng</language><publisher>Amsterdam: Hindawi</publisher><subject>Air pollution ; Algorithms ; Civilization ; Classification ; Decision trees ; Economic development ; Environmental impact ; Environmental management ; Environmental protection ; Environmental quality ; Literature reviews ; Methods ; Pollutants ; Prediction models ; Quality assessment ; Rural areas ; Rural environments ; Social change ; Society</subject><ispartof>Mobile information systems, 2022-07, Vol.2022, p.1-10</ispartof><rights>Copyright © 2022 Yan Yan and Xumeng Feng.</rights><rights>Copyright © 2022 Yan Yan and Xumeng Feng. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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This paper uses a decision tree algorithm to assess the quality of rural ecological environment governance based on an in-depth review of related literature. The data are recursively processed from top to bottom in this paper, and a set of disordered and irregular examples is summed up into a set of classification rules represented by a tree structure, and an evaluation model is obtained, in which all pollution parameters are taken as environmental quality factors. It effectively overcomes the traditional environmental quality prediction model’s inflexibility and inaccurate boundary value. The simulation results show that the quality evaluation method in this paper has a classification accuracy of 96.82 percent and a recall rate of 96.63 percent, which is higher than the comparison algorithm. The experimental results support the effectiveness and applicability of the decision tree-based method for assessing the quality of rural environmental governance. This model can not only assist researchers in correctly analyzing and mastering the migration and change rules of pollutants in the air but also has promising social and economic implications.</description><subject>Air pollution</subject><subject>Algorithms</subject><subject>Civilization</subject><subject>Classification</subject><subject>Decision trees</subject><subject>Economic development</subject><subject>Environmental impact</subject><subject>Environmental management</subject><subject>Environmental protection</subject><subject>Environmental quality</subject><subject>Literature reviews</subject><subject>Methods</subject><subject>Pollutants</subject><subject>Prediction models</subject><subject>Quality assessment</subject><subject>Rural areas</subject><subject>Rural environments</subject><subject>Social change</subject><subject>Society</subject><issn>1574-017X</issn><issn>1875-905X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><recordid>eNp9kF1LwzAYhYMoOKd3_oCAl1qXps3X5ZhzChNRNthdSZN0y-iSmbST_Xtbtmuv3sPLw-HwAHCfouc0JWSEEcYjQjFmhF2AQcoZSQQiq8suE5YnKGWra3AT4xYhijLCBkBOD7JuZWO9gx9emxr6Cn63QdZwqnzt11b10R1s8G5nXANn_mCCk04Z-NXK2jZHuIzWreGLUTb2PYtgDBzXax9ss9ndgqtK1tHcne8QLF-ni8lbMv-cvU_G80RhkTcJZ4qznCpRaZUzTnllmOZaiBxzrJERZdn9tRQ8l0aXuKSU6rRUFFVc8gpnQ_Bw6t0H_9Oa2BRb33ZD61hgKhDPSJqhjno6USr4GIOpin2wOxmORYqKXmLRSyzOEjv88YRvrNPy1_5P_wFcunJS</recordid><startdate>20220704</startdate><enddate>20220704</enddate><creator>Yan, Yan</creator><creator>Feng, Xumeng</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-9033-7907</orcidid></search><sort><creationdate>20220704</creationdate><title>Evaluation Model of Rural Ecological Environment Governance Quality Using Decision Tree Algorithm</title><author>Yan, Yan ; Feng, Xumeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c294t-87c8746c9fdc47868fe7d8d994282d0e9bbc47da984aedb2b666d1bc60f8a8f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Air pollution</topic><topic>Algorithms</topic><topic>Civilization</topic><topic>Classification</topic><topic>Decision trees</topic><topic>Economic development</topic><topic>Environmental impact</topic><topic>Environmental management</topic><topic>Environmental protection</topic><topic>Environmental quality</topic><topic>Literature reviews</topic><topic>Methods</topic><topic>Pollutants</topic><topic>Prediction models</topic><topic>Quality assessment</topic><topic>Rural areas</topic><topic>Rural environments</topic><topic>Social change</topic><topic>Society</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yan, Yan</creatorcontrib><creatorcontrib>Feng, Xumeng</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mobile information systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yan, Yan</au><au>Feng, Xumeng</au><au>Zhang, Liping</au><au>Liping Zhang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation Model of Rural Ecological Environment Governance Quality Using Decision Tree Algorithm</atitle><jtitle>Mobile information systems</jtitle><date>2022-07-04</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>10</epage><pages>1-10</pages><issn>1574-017X</issn><eissn>1875-905X</eissn><abstract>In rural economic development and environmental protection, assessing the quality of rural ecological environment management is critical. This paper uses a decision tree algorithm to assess the quality of rural ecological environment governance based on an in-depth review of related literature. The data are recursively processed from top to bottom in this paper, and a set of disordered and irregular examples is summed up into a set of classification rules represented by a tree structure, and an evaluation model is obtained, in which all pollution parameters are taken as environmental quality factors. It effectively overcomes the traditional environmental quality prediction model’s inflexibility and inaccurate boundary value. The simulation results show that the quality evaluation method in this paper has a classification accuracy of 96.82 percent and a recall rate of 96.63 percent, which is higher than the comparison algorithm. The experimental results support the effectiveness and applicability of the decision tree-based method for assessing the quality of rural environmental governance. This model can not only assist researchers in correctly analyzing and mastering the migration and change rules of pollutants in the air but also has promising social and economic implications.</abstract><cop>Amsterdam</cop><pub>Hindawi</pub><doi>10.1155/2022/5622757</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9033-7907</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Air pollution Algorithms Civilization Classification Decision trees Economic development Environmental impact Environmental management Environmental protection Environmental quality Literature reviews Methods Pollutants Prediction models Quality assessment Rural areas Rural environments Social change Society |
title | Evaluation Model of Rural Ecological Environment Governance Quality Using Decision Tree Algorithm |
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