Classification method for mixed detection signal in the distributed sensor network
Taking into account the limitations of the distributed sensor networks,a simple and efficient classification method was found.According to the main idea of naïve Bayes classification (NBC) algorithm,a new naïve Bayes classification based on attribute significance (NBCBAS) was proposed.The algorithm...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2012-09-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2012.z1.008/ |
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| _version_ | 1841539871649300480 |
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| author | Kan LI Hang XU Zhong-hua HUANG |
| author_facet | Kan LI Hang XU Zhong-hua HUANG |
| author_sort | Kan LI |
| collection | DOAJ |
| description | Taking into account the limitations of the distributed sensor networks,a simple and efficient classification method was found.According to the main idea of naïve Bayes classification (NBC) algorithm,a new naïve Bayes classification based on attribute significance (NBCBAS) was proposed.The algorithm inherited the characteristics of NBC algorithm that was simple and fast computation.At the same time,the algorithm made up for the defects of conditional independence assumption.It had high classification accuracy in practice.The characteristics of the NBCBAS met the classification requirements of the mixed detection signal.At last,the NBCBAS was tested on UCI datasets and mixed detection signal datasets.The results illustrate that our algorithm improves the classification performance. |
| format | Article |
| id | doaj-art-7e1bb4220dd64027b316ad6711218417 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2012-09-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-7e1bb4220dd64027b316ad67112184172025-01-14T06:33:44ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2012-09-0133535759667251Classification method for mixed detection signal in the distributed sensor networkKan LIHang XUZhong-hua HUANGTaking into account the limitations of the distributed sensor networks,a simple and efficient classification method was found.According to the main idea of naïve Bayes classification (NBC) algorithm,a new naïve Bayes classification based on attribute significance (NBCBAS) was proposed.The algorithm inherited the characteristics of NBC algorithm that was simple and fast computation.At the same time,the algorithm made up for the defects of conditional independence assumption.It had high classification accuracy in practice.The characteristics of the NBCBAS met the classification requirements of the mixed detection signal.At last,the NBCBAS was tested on UCI datasets and mixed detection signal datasets.The results illustrate that our algorithm improves the classification performance.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2012.z1.008/naïve Bayes classificationattribute significancedistributed sensor networksmixed detection signal |
| spellingShingle | Kan LI Hang XU Zhong-hua HUANG Classification method for mixed detection signal in the distributed sensor network Tongxin xuebao naïve Bayes classification attribute significance distributed sensor networks mixed detection signal |
| title | Classification method for mixed detection signal in the distributed sensor network |
| title_full | Classification method for mixed detection signal in the distributed sensor network |
| title_fullStr | Classification method for mixed detection signal in the distributed sensor network |
| title_full_unstemmed | Classification method for mixed detection signal in the distributed sensor network |
| title_short | Classification method for mixed detection signal in the distributed sensor network |
| title_sort | classification method for mixed detection signal in the distributed sensor network |
| topic | naïve Bayes classification attribute significance distributed sensor networks mixed detection signal |
| url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2012.z1.008/ |
| work_keys_str_mv | AT kanli classificationmethodformixeddetectionsignalinthedistributedsensornetwork AT hangxu classificationmethodformixeddetectionsignalinthedistributedsensornetwork AT zhonghuahuang classificationmethodformixeddetectionsignalinthedistributedsensornetwork |