Short term forecasting based on hybrid least squares support vector machines

• Main Authors: Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor
• Format: Article
• Language: English
• Published: American Scientific Publisher 2018
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/19448/1/29.%20Short%20Term%20Forecasting%20based%20on%20Hybrid%20Least%20Squares%20Support%20Vector%20Machines1.pdf; http://umpir.ump.edu.my/id/eprint/19448/; https://doi.org/10.1166/asl.2018.12958

Flood is one of the common natural disasters that have caused universal damage throughout the world. Due to that matter, reliable flood forecasting is crucial for the purpose of preventing loss of life and minimizing property damage. In this study, hybrid Least Squares Support Vector Machines (LSSVM...