Kriging-Based Land-Use Regression Models That Use Machine Learning Algorithms to Estimate the Monthly BTEX Concentration
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- Raeesa Moolla & Christopher J. Curtis & Jasper Knight, 2015. "Occupational Exposure of Diesel Station Workers to BTEX Compounds at a Bus Depot," IJERPH, MDPI, vol. 12(4), pages 1-15, April.
- Daniel P. McMillen, 2004. "Geographically Weighted Regression: The Analysis of Spatially Varying Relationships," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 554-556.
- Chin-Yu Hsu & Jhao-Yi Wu & Yu-Cheng Chen & Nai-Tzu Chen & Mu-Jean Chen & Wen-Chi Pan & Shih-Chun Candice Lung & Yue Leon Guo & Chih-Da Wu, 2019. "Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration," IJERPH, MDPI, vol. 16(7), pages 1-12, April.
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- Liadira Kusuma Widya & Chin-Yu Hsu & Hsiao-Yun Lee & Lalu Muhamad Jaelani & Shih-Chun Candice Lung & Huey-Jen Su & Chih-Da Wu, 2020. "Comparison of Spatial Modelling Approaches on PM 10 and NO 2 Concentration Variations: A Case Study in Surabaya City, Indonesia," IJERPH, MDPI, vol. 17(23), pages 1-15, November.
- Corina Popitanu & Gabriela Cioca & Lucian Copolovici & Dennis Iosif & Florentina-Daniela Munteanu & Dana Copolovici, 2021. "The Seasonality Impact of the BTEX Pollution on the Atmosphere of Arad City, Romania," IJERPH, MDPI, vol. 18(9), pages 1-11, May.
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Keywords
nitrogen dioxide (NO 2 ); hybrid Kriging-LUR model; culture-specific sources; spatiotemporal variations;All these keywords.
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