Thursday 28th of March 2024
 

Traffic Demand Forecasting for EGCS with Grey Theory Based Multi-Model Method


Zhenshan Yang and Yunli Zhang

Elevator traffic demand forecasting is the essential prerequisite for effectively implementing elevator group control system (EGCS). Considering that there exists lots of abnomal information in elevator traffic caused by subjectivity and occasionality in human behaviour and that observing traffic information continuously is costly and difficult, an improved grey forecasting based method using multi-model to forecast future elevator traffic demand of EGCS is proposed, the abnomal information which refers to outliers is processed, based on which a smoothing technique on original traffic data is conducted to transform the raw data into an increasing sequence, to further reduce the randomness of the observed traffic data and to make full use of regularity information. The proposed method not only avoid the theorrtical error of grey model per se, but also improved the forecasting accuracy, which is suitable for short period forecasting for elevator traffic demand. Simulation experiments show the validity of the proposed method.

Keywords: Elevator Traffic Demand Forecasting, Elevator Group Control System (EGCS), Grey Model (GM), Abnormal Information, Multi-Model Forecasting, Smoothing Processing.

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ABOUT THE AUTHORS

Zhenshan Yang
Zhenshan Yang received the B.S. degree in industrial electrical automation from Shenyang Jianzhu University, in 1987. He received the Ph.D. degree in control theory & control engineering from Dalian University of Technology, in 2008. He is a committee member of China Electrotechnology Society (CES), the Deputy Secretary-General of the Affiliated Society of CES of Liaoning Province and the editorial board member of the International Journal of Urban Planning and Design Research (UPDR). Currently, he is a professor at Bohai University. His research interests include intelligent building, elevator traffic analysis, design, and intelligent Control.

Yunli Zhang
Yunli Zhang received the B.S. degree in applied mathematics from Northeastern University, in 1987, and the master\'s degree in computer technology and application from Dalian University of Technology. Currently, she is a Professor at Liaoning Medical University, Jinzhou, China. His interests are in data mining and its application in intelligent control systems.


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