Improved support vector machine using optimization techniques for an aerobic granular sludge

• Main Authors: Yasmin, Nur Sakinah Ahmad, Abdul Wahab, Norhaliza, Nor Anuar, Aznah
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2020
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/91716/1/NurSakinahAhmad2020_ImprovedSupportVectorMachine.pdf; http://eprints.utm.my/id/eprint/91716/; http://dx.doi.org/10.11591/eei.v9i5.2264
• Institution: Universiti Teknologi Malaysia

Aerobic granular sludge (AGS) is one of the treatment methods often used in wastewater systems. The dynamic behavior of AGS is complex and hard to predict especially when it comes to a limited data set. Theoretically, support vector machine (SVM) is a good prediction tool in handling limited data se...