A statistical procedure for determining the best performing air quality simulation model |
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| Institution: | 1. Department of Civil Engineering & Centre for Environmental Science and Engineering, Indian Institute of Technology, Kanpur 208-016, India;2. Department of Chemical and Biological Engineering, Jeju National University, Jeju 690-756, Republic of Korea;1. Meteorological Institute, University of Hamburg, Germany;2. Department of Fluid Mechanics, Budapest University of Technology and Economics, Hungary;1. Department of Fiber and Composite Materials, Feng Chia University, Taichung, 40768, Taiwan;2. Department of Chemistry and Chemical Engineering, Minjiang University, Fuzhou, 350108, China;3. Innovation Platform of Intelligent and Energy-Saving Textiles, School of Textiles, Tianjin Polytechnic University, Tianjin, 300387, China;4. Graduate Institute of Biotechnology and Biomedical Engineering, Central Taiwan University of Science and Technology, Taichung, 40601, Taiwan;5. Laboratory of Fiber Application and Manufacturing, Department of Fiber and Composite Materials, Feng Chia University, Taichung, 40768, Taiwan;6. Department of Fashion Design, Asia University, Taichung, 41354, Taiwan;7. School of Chinese Medicine, China Medical University, Taichung, 40402, Taiwan;1. University of Calgary, Calgary, Alberta, Canada;2. Canadian Space Agency, Saint-Hubert, Quebec, Canada;3. MDA Corporation, Richmond, British Columbia, Canada;1. HPA Company, 2d Floor, No 4, Building 314, Valiasr Square, 1439914153, Tehran, Iran;2. Department of Environmental Science, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran |
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| Abstract: | Air quality simulation models have been the subject of extensive evaluations to determine their performance under a variety of environmental and meteorological conditions. While much information has been gathered, no clearly defined methodology exists for comparing the performance of two or more models. The purpose of this paper is to present a statistically oriented procedure to test if the performance of one model is superior to others using a composite performance index involving the bootstrap resampling technique. |
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