Database System and Model for Predicting Risk Level of Flood That Damages Rice Farming in Thailand
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Susutti, W.; Dilokpatpongsa, P.; Kaemawichanurat, P.; Saleewong, T.; Dhakonlayodhin, B.; Supapakorn, T.; Watthayu, W.
ปีที่เผยแพร่ (ค.ศ.): 2025
วารสาร: Statistics, Optimization & Information Computing (2311-004X)
Volume number: 14
Issue number: 5
หน้าแรก: 2874
หน้าสุดท้าย: 2891
จำนวนหน้า: 18
นอก: 2311-004X
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
Rice is always an important economic crop of Thailand as it is not only the staple in every family of the entire country but it also earns an extremely large income among all the Thai crop exports. However, Thai farmers are considered to be economically vulnerable and still have to face many difficulties, in particular, the flood problem. The flood problem has destroyed rice farming areas over the past decade until now. Risk and severity assessments mainly contribute to the government promptly subsidizing the farmers. In any case, the updated and reliable database systems are the main ingredients for developing the model of these assessments. In this paper, we develop a database system from a survey with 5,000 samples across the whole country. All the raw data has been managed to cleaned and prepared in order to develop a model that is used to predict risk level. The model achieves 87.24 percent accuracy with a significance level of 0.05. In addition, the model is able to select variables that have a statistically significant effect on the risk level forecast, and these variables could be used to improve the quality and data structure for developing a Web Application (WebApp). The WebApp of our research group for individual risk assessment of the rice farmers has been developed by JavaScript for the front end, while the back end is run by Python. The WebApp was evaluated satisfactions by over 370 farmers from three public hearings. The average satisfaction scores are over 4 to a maximum of 5 in all categories. © © 2025 International Academic Press
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