Skylight Opening Degree Prediction Method Based on Parallel Clustering

Authors

Deng Li, 1. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;;2. Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200072, China;
Yu Yue, 1. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;;2. Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200072, China;
Honglin Pang, 1. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;;2. Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200072, China;
Minrui Fei, 1. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;;2. Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200072, China;

Abstract

Abstract: To process the massive distributed data and control the agricultural facilities intelligently, a parallel Dirichlet Process Mixture Model (DPMM) clustering method was proposed based on Spark. With this method, the prediction model of greenhouse skylight opening degree was obtained by training the agricultural environmental and facilities data. The model was used to predict the greenhouse skylight opening degree. Through several comparison experiments, both the feasibility and the efficiency of the proposed parallel clustering were verified, the prediction accuracy was calculated. The experimental results show that the proposed approach has higher efficiency and accuracy.

Recommended Citation

Li, Deng; Yue, Yu; Pang, Honglin; and Fei, Minrui (2020) "Skylight Opening Degree Prediction Method Based on Parallel Clustering," Journal of System Simulation: Vol. 29: Iss. 10, Article 29.
DOI: 10.16182/j.issn1004731x.joss.201710029
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss10/29

First Page

2459

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201710029

Last Page

2467

CLC

TP338.8

Recommended Citation

Deng Li, Yu Yue, Pang Honglin, Fei Minrui. Skylight Opening Degree Prediction Method Based on Parallel Clustering[J]. Journal of System Simulation, 2017, 29(10): 2459-2467.

DOI

10.16182/j.issn1004731x.joss.201710029