Wei Wang
Hebei University of Engineering

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Distributed Control System in Electrical Heaters of the Public Buildings Jianhua Ren; Wei Wang; Tingchao Yang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 6: June 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Being with many advantages such as environmental protection, controllable, facilitate measurement etc, electric heating has been promoted actively in some places .For public buildings with huge energy consumption, electric heating intelligent controlling may be the key to achieve energy conservation. In this paper, visual distributed control system (DCS) was presented in electric heating of the public buildings. In this control system, a PC was used as the host, and RS232/485 interface converter was used as serial interface of mutual conversion .Through industrial standard RS485 bus with high reliability and low cost which was the link between the host and many sets of thermostat, a one-to-many communication network was formed. The MCU of the thermostats was ATMega8 microcontroller. Meanwhile, DS18B20 integrated temperature probe was used in temperature sensor .Through the DCS test online,it met the need of each individual heating unit. Therefore, unnecessary heat waste was reduced, heating costs were saved. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2660
Traffic Prediction Based on Correlation of Road Sections Xiaodan Huang; Wei Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 10: October 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Road section data packet is very necessary for the estimation and prediction in short-time traffic condition. However, previous researches on this problem are lack of quantitative analysis. A section correlation analyzing method with traffic flow microwave data is proposed for this problem. It is based on the metric multidimensional scaling theory. With a dissimilarity matrix, scalar product matrix can be calculated. Subsequently, a reconstructing matrix of section traffic flow could be got with principal components factor analysis, which could display section groups in low dimension. It is verified that the new method is reliable and effective. After that, Auto Regressive Moving Average (A RMA) model is used for forecasting traffic flow and lane occupancy. Finally, a simulated example has shown that the technique is effective and exact. The theoretical analysis indicates that the forecasting model and algorithms have a broad prospect for practical application. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3335