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Journal of the Air & Waste Management Association Volume 50, 2000 - Issue 4
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Technical Paper

Neural Network Model for Predicting Peak Photochemical Pollutant Levels

Dimitrios Melas Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
,
Ioannis Kioutsioukis Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
&
Ioannis C. Ziomas Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
Pages 495-501 | Published online: 27 Dec 2011

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KostasP. Moustris, IoannisX. Tsiros, IoannisC. Ziomas & AthanasiosG. Paliatsos. (2010) Artificial neural network models as a useful tool to forecast human thermal comfort using microclimatic and bioclimatic data in the great Athens area (Greece). Journal of Environmental Science and Health, Part A 45:4, pages 447-453.
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IoannisX. Tsiros, IoannisF. Dimopoulos, KostasI. Chronopoulos & Georgios Chronopoulos. (2009) Estimating airborne pollutant concentrations in vegetated urban sites using statistical models with microclimate and urban geometry parameters as predictor variables: A case study in the city of Athens Greece. Journal of Environmental Science and Health, Part A 44:14, pages 1496-1502.
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Kostas I. Chronopoulos, IoannisX. Tsiros, IoannisF. Dimopoulos & Nikolaos Alvertos. (2008) An application of artificial neural network models to estimate air temperature data in areas with sparse network of meteorological stations. Journal of Environmental Science and Health, Part A 43:14, pages 1752-1757.
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S. Dehhaghi & Y. Rashidi. (2022) Evaluation of air quality standard compliance by means of statistical distribution modeling: a study in Tehran. International Journal of Environmental Science and Technology 19:12, pages 12235-12248.
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Tuan-Dung Hoang, Nguyen Minh Ky, Nguyen Thi Ngoc Thuong, Hoang Quy Nhan & Nguyen Vo Chau Ngan. 2022. Artificial Intelligence and Environmental Sustainability. Artificial Intelligence and Environmental Sustainability 23 43 .
Debendra Dalai, Sanjay Sharma, Varinder Kanwar & Jyotsna Kaushal. 2022. Proceedings of International Conference on Innovative Technologies for Clean and Sustainable Development (ICITCSD – 2021). Proceedings of International Conference on Innovative Technologies for Clean and Sustainable Development (ICITCSD – 2021) 791 800 .
Khandaker M. A. Hossain. (2014) Predictive Ability of Improved Neural Network Models to Simulate Pollutant Dispersion. International Journal of Atmospheric Sciences 2014, pages 1-12.
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P.T. Nastos, K.P. Moustris, I.K. Larissi & A.G. Paliatsos. (2013) Rain intensity forecast using Artificial Neural Networks in Athens, Greece. Atmospheric Research 119, pages 153-160.
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Kostas P. Moustris, Ioanna K. Larissi, Panagiotis T. Nastos & Athanasios G. Paliatsos. (2011) Precipitation Forecast Using Artificial Neural Networks in Specific Regions of Greece. Water Resources Management 25:8, pages 1979-1993.
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Konstantinos P. Moustris, Ioannis C. Ziomas & Athanasios G. Paliatsos. (2009) 3-Day-Ahead Forecasting of Regional Pollution Index for the Pollutants NO2, CO, SO2, and O3 Using Artificial Neural Networks in Athens, Greece. Water, Air, & Soil Pollution 209:1-4, pages 29-43.
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Dimitris K. Papanastasiou & Dimitris Melas. (2009) Application of PM10′s Statistical Distribution to Air Quality Management—A Case Study in Central Greece. Water, Air, and Soil Pollution 207:1-4, pages 115-122.
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A. K. Paschalidou, P. A. Kassomenos & A. Bartzokas. (2008) A comparative study on various statistical techniques predicting ozone concentrations: implications to environmental management. Environmental Monitoring and Assessment 148:1-4, pages 277-289.
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Lazaros S. Iliadis & A. Papaleonidas. 2009. Engineering Applications of Neural Networks. Engineering Applications of Neural Networks 1 16 .
Jeng-Chung Chen & Ni-Bin Chang. (2007) Mining the fuzzy control rules of aeration in a Submerged Biofilm Wastewater Treatment Process. Engineering Applications of Artificial Intelligence 20:7, pages 959-969.
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D. K. Papanastasiou, D. Melas & I. Kioutsioukis. (2007) Development and Assessment of Neural Network and Multiple Regression Models in Order to Predict PM10 Levels in a Medium-sized Mediterranean City. Water, Air, and Soil Pollution 182:1-4, pages 325-334.
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S. V. Barai, A. K. Dikshit & Sameer Sharma. 2007. Soft Computing in Industrial Applications. Soft Computing in Industrial Applications 290 305 .
G. Nunnari. (2005) An improved back propagation algorithm topredict episodes of poor air quality. Soft Computing 10:2, pages 132-139.
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Christine W. Chan & Guo H. Huang. (2003) Artificial intelligence for management and control of pollution minimization and mitigation processes. Engineering Applications of Artificial Intelligence 16:2, pages 75-90.
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Héctor Jorquera, Wilfredo Palma & José Tapia. (2002) A ground‐level ozone forecasting model for Santiago, Chile. Journal of Forecasting 21:6, pages 451-472.
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Christine Chan & Ranh Nguyen. 2002. Intelligent Systems. Intelligent Systems.

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