Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm
The main difference between rough set theory and some methods of uncertainty theory, such as probabilistic data mining, fuzzy set theory, and evidence-based data mining, is that they do not require any prior knowledge beyond the data set being processed. This is also its advantage. At present, rough...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/9286252 |
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| _version_ | 1850235066390675456 |
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| author | Xiaoli Liu |
| author_facet | Xiaoli Liu |
| author_sort | Xiaoli Liu |
| collection | DOAJ |
| description | The main difference between rough set theory and some methods of uncertainty theory, such as probabilistic data mining, fuzzy set theory, and evidence-based data mining, is that they do not require any prior knowledge beyond the data set being processed. This is also its advantage. At present, rough set theory has been well applied in artificial intelligence, knowledge discovery, pattern recognition, fault detection, and so on. According to the discovery model of classification knowledge, the attribute reduction of decision table, classification rule reduction, and classification algorithm under the condition of missing attribute are discussed. It tests the effectiveness of the knowledge recognition algorithm. The effectiveness of the algorithm proposed in this article reaches 87.6%, 84.4%, 94.97%, and 96.34%. |
| format | Article |
| id | doaj-art-0e7fb45cf8d142b98b135fa7bafffcb0 |
| institution | OA Journals |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-0e7fb45cf8d142b98b135fa7bafffcb02025-08-20T02:02:25ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/9286252Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition AlgorithmXiaoli Liu0School of Humanities and ManagementThe main difference between rough set theory and some methods of uncertainty theory, such as probabilistic data mining, fuzzy set theory, and evidence-based data mining, is that they do not require any prior knowledge beyond the data set being processed. This is also its advantage. At present, rough set theory has been well applied in artificial intelligence, knowledge discovery, pattern recognition, fault detection, and so on. According to the discovery model of classification knowledge, the attribute reduction of decision table, classification rule reduction, and classification algorithm under the condition of missing attribute are discussed. It tests the effectiveness of the knowledge recognition algorithm. The effectiveness of the algorithm proposed in this article reaches 87.6%, 84.4%, 94.97%, and 96.34%.http://dx.doi.org/10.1155/2022/9286252 |
| spellingShingle | Xiaoli Liu Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm Discrete Dynamics in Nature and Society |
| title | Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm |
| title_full | Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm |
| title_fullStr | Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm |
| title_full_unstemmed | Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm |
| title_short | Accounting and Financial Management Cost Accounting Integrating Rough Set Knowledge Recognition Algorithm |
| title_sort | accounting and financial management cost accounting integrating rough set knowledge recognition algorithm |
| url | http://dx.doi.org/10.1155/2022/9286252 |
| work_keys_str_mv | AT xiaoliliu accountingandfinancialmanagementcostaccountingintegratingroughsetknowledgerecognitionalgorithm |