Advanced air pollution by Farhad Nejadkoorki

By Farhad Nejadkoorki

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2050-2059. Taheri S. M. (1999). ), Ferdowsi University of Mashhad Jihad publications, 212 pages. A. and Towhidi N. (2009). 51, pp. 111-122. Zadeh L. A. (1965). Fuzzy sets, Information and Control, Vol. 8, Issue 3, pp. 338-353. , L. Centomo, C. Greenen, N. Piret, G. Richards and R. Stephens. 2010. , MetSoc, COM2010, 1287 pages. org 3 Indoor Nitrogen Oxides Silvia Vilčeková Technical University of Košice Slovakia 1. Introduction Nitrogen monoxide (NO) and nitrogen dioxide (NO2) are gases produced by hightemperature combustion through reactions between nitrogen and oxygen.

E. process i located in area j, is partially biocompatible or safe in producing pollutant k. The worst conditions are considered in this research; therefore, the minimum fuzzy logic rule is used. The most dangerous process i in producing pollutant k in area j is the process that has the least biocompatibility or safety in producing pollutant k in area j. As a result, is obtained from the fuzzy minimum rule like equation 8. C,, , C,, , = Min C , , (8) Perhaps, it seems that monitoring of pollutants only through the set of processes is confusing.

In this chapter, it shows that, it used for monitoring of industrial pollutions as a case study of air pollution monitoring in iron and steel making industry and aluminum making industry. Fuzzy logic has a real concept of natural actuation which everybody meets everyday. This logic seems to be natural phenomena in a real form. Fuzzy logic is used in uncertainty environments so that expert's experiments can be converted into mathematical languages. On the bases of fuzzy logic it is possible to maximize the utilization of decision making.

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