Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest

• Main Authors: Sun, Y, Wendi, D, Kim, D.E, Liong, S.-Y
• Other Authors: TROPICAL MARINE SCIENCE INSTITUTE
• Format: Article
• Published: 2020
• Subjects: Forestry; Groundwater; Groundwater resources; Neural networks; Reservoirs (water); Wetlands; Accurate prediction; Computational costs; Efficient managements; Ground water table; Hydrological regime; Parameter uncertainty; Physical parameters; Physical systems; Forecasting; artificial neural network; forecasting method; groundwater; groundwater resource; hydrological regime; numerical model; performance assessment; reservoir; swamp forest; water table; Singapore [Southeast Asia]
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/176131
• Institution: National University of Singapore

10.5194/hess-20-1405-2016