Advancements in daily precipitation forecasting: A deep dive into daily precipitation forecasting hybrid methods in the Tropical Climate of Thailand.

Climate change and increasing water demands underscore the importance of water resource management. Precise precipitation forecasting is critical to effective management. This study introduced a Daily Precipitation Forecasting Hybrid (DPFH) technique for central Thailand, which uses three different input-based models to improve prediction accuracy.

Imputation of missing daily rainfall data; A comparison between artificial intelligence and statistical techniques.

Handling missing values is a critical component of the data processing in hydrological modeling. The key objective of this research is to assess statistical techniques (STs) and artificial intelligence-based techniques (AITs) for imputing missing daily rainfall values and recommend a methodology applicable to the mountainous terrain of northern Thailand. In this study, 30 years of daily rainfall data was collected from 20 rainfall stations in northern Thailand and randomly 25-35 % of data was deleted from four target stations based on Spearman correlation coefficient between the target and neighboring stations.

Translation and psychometric testing of the Thai version of cancer survivors' unmet needs measure among cancer survivors.

Objective: To evaluate the psychometric properties of the Thai version of the Cancer Survivors' Unmet needs (CaSUN-TH) scale among Thai cancer survivors after completion of primary treatment.

Methods: Standardized translation procedures developed the Cancer Survivors' Unmet Needs into a Thai version (CaSUN-TH). Face validity was evaluated by a group of experts, and a pilot test on 10 cancer patients was conducted to evaluate its readability.