The Comparison of Grey System and the Verhulst Model for Rainfall and Water in Dam Prediction

บทความในวารสาร


ผู้เขียน/บรรณาธิการ


กลุ่มสาขาการวิจัยเชิงกลยุทธ์

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รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่งPuripat C., Sarikavanij S.

ผู้เผยแพร่Hindawi Limited

ปีที่เผยแพร่ (ค.ศ.)2018

Volume number2018

นอก1687-9309

eISSN1687-9309

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85053712764&doi=10.1155%2f2018%2f7169130&partnerID=40&md5=fd9df4fa7b8d53f72766d1dc41830fb8

ภาษาEnglish-Great Britain (EN-GB)


ดูในเว็บของวิทยาศาสตร์ | ดูบนเว็บไซต์ของสำนักพิมพ์ | บทความในเว็บของวิทยาศาสตร์


บทคัดย่อ

A time series of data of rainfall in Thailand between the years 2005 and 2015 was employed to predict possible future rainfall based on Julong Deng's grey systems theory and the grey Verhulst model to see which model can predict more accurately with uncertain and limited data. Firstly, the rainfall data were arranged to display the overall patterns of rainfall volume along with its frequency as well as the temperature during Thailand's rainy seasons. This makes it possible to see the cycle of rainfall, which is too long for people to intuitively understand the nature of precipitation. One puzzling phenomenon that has made rainfall forecast elusive is the unpredictability of the haphazard nature of rainfall in Thailand. A more precise prediction would certainly result in a better control of water volume in rivers and dams for fruitful agricultural business and adequate human consumption. This can also prevent the flooding that can devastate the economy and transportation of the whole country and also tremendously improve the future water management policy in many ways. This effective prediction could also be employed elsewhere around the globe for similar benefits. Hence, the grey systems theory and the grey Verhulst model are juxtaposed to determine a better prediction possible. ฉ 2018 Chalermchai Puripat and Sukuman Sarikavanij.


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อัพเดทล่าสุด 2023-29-09 ถึง 10:29