Manufacturing and technology industries produce large amounts of air pollutants. Ulsan Metropolitan City, South Korea, is well-known for its large industrial complexes; in particular, the concentration of SO2 here is the highest in the country. We assessed SO2 monitoring sites based on conditional and joint entropy, because this is a common method for determining an optimal air monitoring network. Monthly SO2 concentrations from 12 air monitoring sites were collected, and the distribution of spatial locations was determined by kriging. Mean absolute error, Root Mean Squared Error (RMSE), bias and correlation coefficients were employed to evaluate the considered algorithms. An optimal air monitoring network for Ulsan was suggested based on the improvement of RMSE.

Abstract
 1. 서 론
 2. 연구 방법
  2.1. 엔트로피
  2.2. 크리깅
  2.3. 최적관측소 선정방법
 3. 연구 자료
 4. 최적관측소 평가방법
  4.1. 엔트로피기반 최적관측소 선정결과
  4.2. 최적관측소 평가
  4.3. 최적관측소의 수 결정
 5. 결 론
 REFERENCES

• 임정현(대구대학교 통계학과) | Junghyun Lim (Department of Statistics, Daegu University)
• 윤상후(대구대학교 전산통계학과) | Sanghoo Yoon (Department of Computer Science and Statistics, Daegu University) Corresponding author