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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 328341, 9 pages
Research Article

Region-Dot Conversion Fusion Algorithm and Application

1College of Electric and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
2Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan

Received 26 February 2014; Revised 26 April 2014; Accepted 26 April 2014; Published 28 May 2014

Academic Editor: Her-Terng Yau

Copyright © 2014 Zhouxing Fu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The interior decoration materials and the new furniture using formaldehyde, ammonia, and other poisonous substances are known as the main sources of indoor air pollutions. However, it is still a big challenge to estimate accurately the overall air quality by using the current measuring tools. Accordingly, the region-dot fusion (RDF) algorithm is proposed to evaluate the air quality in this paper. For the conversion from a region to a dot, the region-dot function is firstly defined as the summation of the belief function and the weighted width of the belief interval. In the RDF algorithm, the belief intervals of the two sensors with the basic probability functions are calculated based on the measurements of formaldehyde sensor and ammonia sensor. Then, the belief intervals are converted to the specific values. After the computation of collision degree and combination, the pollution level represented by a belief interval with the maximum probability is selected as the outcome of fusion decision. Compared with the weighted fusion algorithm and D-S evidence reasoning method, it is experimentally proved that the RDF algorithm can improve the separability of the belief intervals of the belief functions. Also, the evidence collision degree is decreased dramatically.