การนำเสนอผลงานในที่ประชุมวิชาการนานาชาติ
• Chaipimonplin, T. and Mukdanasit, S. (2024). CM Water Forecast Mobile Application Verstion 1.0. 3rd Trilateral Symposium on Sustainability: Strategies for climate action and mitigation of climate change impacts, August 2024. Chiang Mai University, Thailand, p. 60.
• Chaipimonplin, T. and Mukdanasit, S. (2023). Drought Management with Web Application for Chiang Mai Province, Thailand. 2nd Trilateral Symposium on SDGs: New Strategies Approaches Toward SDGs Beyond the COVID-19 Pandemic, August 2023. Kagawa University, Japan, p. 103.
• Chaipimonplin, T. and Sin-ampol, P. (2019). Future Flood Prediction with Artificial Neural Network Model from Rainfall Grid Data at Bangrakam District, Thailand. International Conference on Capacity Building for Research and Innovation in Disaster Resilience 2019, 14-18 January 2019.
• Sim-ampol, P., Chaipimonplin, T. and Songka, S. (2019). Local Community Engagement for Adaptation to Future Challenges in Pilot Flood Detention Area of Thailand. International Conference on Capacity Building for Research and Innovation in Disaster Resilience 2019, 14-18 January 2019
• Chaipimonplin, T., Aumthong, S. and Chotamonsak, C. (2018). Prediction of total organic carbon storage with artificial neural network model in 9 Northern Province, Thailand. 7th Chiang Mai University-Kagawa University Joint Symposium 2018, August 2018. Chiang Mai, Thailand, pp. 48-51.
• Chaipimonplin, T. (2017) Comparison learning algorithms of artificial neural network model for flood forecasting, Chiang Mai, Thailand. In Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (eds) MODSIM 2017, 22nd International Congress on Modelling and Simulation Society of Australia and New Zealand, December 2017, pp. 473-479. ISBN: 978-2-9872143-7-9. www.mssanz.org.au/modsim2017/C6/chaipimonplin.pdf.
• Chaipimonplin, T. (2016) “The efficiency of using different of learning algorithms in artificial neural network model for flood forecasting at Upper River Ping Catchment, Thailand”. 85th International Conference on Civil and Environmental Engineering (I2C2E 2016), 16-17 November 2016, Oxford, UK, 1-5.
• Chaipimonplin, T. (2016) “Global navigation satellite system in Thailand” The 2nd International Conference of Indonesian Society for Remote Sensing (ICOIRS 2016), 17-19 October 2016, Yogyakarta, Indonesia, 86-89.
• Aumtong, S., Chaipimonplin, T. and Pongwongkhum, P. (2016) “Artificial neural network development for forecasting soil carbon sequestration of paddy soils in Thailand”. Workshop SOMmic- Microbial Contribution and Impact on Soil Organic Matter, 9-11 November 2016, Leipzig, Germany.
• Chaipimonplin, T. and Vangpaisal, T. (2015) “The efficiency of input determination techniques in ANN for flood forecasting Mun Basin, Thailand”. The 2015 International Conference on Water Resource and Environment (WRE 2015), 25-28 July 2015, Beijing, China.
• Chaipimonplin, T. (2013). The effective of different learning algorithms of Artificial Neural Network for flood forecasting at Upper Ping River, Thailand. BIT’s 1st Annual International Conference of Emerging Industry (ICEI 2013), 6-7 November, Shenzhen, China. (Invited speaker).
• Chaipimonplin, T. and Vangpaisal, T. (2013). Comparison of the efficiency of input determination techniques with LM and BR algorithms in ANN for flood forecasting, Mun Basin, Thailand. The 2013 6th International Conference on Advanced Computer Theory and Engineering (ICACTE 2013), 17-18 August, Male, Maldives.
• Chaipimonplin, T., See, L.M. and Kneale, P.E. (2011). Improving Neural Network for Flood Forecasting Using Radar Data on the Upper Ping River. In Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM 2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2011, pp.1070-1076. ISBN: 978-0-9872143-1-7. www.mssanz.org.au/modsim2011/C1/chaipimonplin.pdf)
• Chaipimonplin, T., See, L.M. and Kneale, P.E. (2011). Comparison of Neural Network Learning Algorithms; BR and LM, for Flood Forecasting, Upper Ping Catchment. 10th International Symposium on New Technologies for Urban Safety of Mega Cities in ASIA (USMCA 2011) 12-14 October 2011, Chiang Mai, Thailand.
• Chaipimonplin, T., See, L.M. and Kneale, P.E. (2008). Use of neural network to predict flooding in Chiang Mai, Thailand: comparison of input determination techniques. AOGS 2008, The Asian Oceania Geosciences Society, Pusan, South Korea, 17-19 June 2008.
• Chaipimonplin, T., See, L.M. and Kneale, P.E. (2008). Neural network prediction of flooding in Chiang Mai, Thailand: comparison of input determination techniques. EGU, Vienna, Austria, 13-18 Apr 2008.