Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things
Massive events can be produced today because of the rapid development of the Internet of Things (IoT). Complex event processing, which can be used to extract high-level patterns from raw data, has become an essential part of the IoT middleware. Prediction analytics is an important technology in supp...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-12-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/723260 |
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| _version_ | 1850109668994580480 |
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| author | Xinghui Zhu Fang Kui Yongheng Wang |
| author_facet | Xinghui Zhu Fang Kui Yongheng Wang |
| author_sort | Xinghui Zhu |
| collection | DOAJ |
| description | Massive events can be produced today because of the rapid development of the Internet of Things (IoT). Complex event processing, which can be used to extract high-level patterns from raw data, has become an essential part of the IoT middleware. Prediction analytics is an important technology in supporting proactive complex event processing. In this paper, we propose the use of dynamic Bayesian model averaging to develop a high-accuracy prediction analytic method for large-scale IoT application. This method, which is based on a new multilayered adaptive dynamic Bayesian network model, uses Gaussian mixture models and expectation-maximization inference for basic Bayesian prediction. Bayesian model averaging is implemented by using Markov chain Monte Carlo approximation, and a novel dynamic Bayesian model averaging method is proposed based on event context clustering. Simulation experiments show that the proposed prediction analytic method has better accuracy compared to traditional methods. Moreover, the proposed method exhibits acceptable performance when implemented in large-scale IoT applications. |
| format | Article |
| id | doaj-art-48439f51ebd645148e00d7e4ffc7b717 |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2013-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-48439f51ebd645148e00d7e4ffc7b7172025-08-20T02:38:01ZengWileyInternational Journal of Distributed Sensor Networks1550-14772013-12-01910.1155/2013/723260723260Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of ThingsXinghui Zhu0Fang Kui1Yongheng Wang2 College of Information Science & Technology, Hunan Agricultural University, Changsha 410128, China College of Information Science & Technology, Hunan Agricultural University, Changsha 410128, China College of Information Science and Engineering, Hunan University, Changsha 410082, ChinaMassive events can be produced today because of the rapid development of the Internet of Things (IoT). Complex event processing, which can be used to extract high-level patterns from raw data, has become an essential part of the IoT middleware. Prediction analytics is an important technology in supporting proactive complex event processing. In this paper, we propose the use of dynamic Bayesian model averaging to develop a high-accuracy prediction analytic method for large-scale IoT application. This method, which is based on a new multilayered adaptive dynamic Bayesian network model, uses Gaussian mixture models and expectation-maximization inference for basic Bayesian prediction. Bayesian model averaging is implemented by using Markov chain Monte Carlo approximation, and a novel dynamic Bayesian model averaging method is proposed based on event context clustering. Simulation experiments show that the proposed prediction analytic method has better accuracy compared to traditional methods. Moreover, the proposed method exhibits acceptable performance when implemented in large-scale IoT applications.https://doi.org/10.1155/2013/723260 |
| spellingShingle | Xinghui Zhu Fang Kui Yongheng Wang Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things International Journal of Distributed Sensor Networks |
| title | Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things |
| title_full | Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things |
| title_fullStr | Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things |
| title_full_unstemmed | Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things |
| title_short | Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things |
| title_sort | predictive analytics by using bayesian model averaging for large scale internet of things |
| url | https://doi.org/10.1155/2013/723260 |
| work_keys_str_mv | AT xinghuizhu predictiveanalyticsbyusingbayesianmodelaveragingforlargescaleinternetofthings AT fangkui predictiveanalyticsbyusingbayesianmodelaveragingforlargescaleinternetofthings AT yonghengwang predictiveanalyticsbyusingbayesianmodelaveragingforlargescaleinternetofthings |