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Hydropower energy is one of most promising clean energy technologies, however this energy technologies has many challenges if compare other renewable energy for example Biomass, solar, wind energy, has high capital investment cost. In Mozambique, access to conversional energy in form of electricity has been limited to most of the rural population. This study investigates the effect of discrete wavelet transform data pre-processing method on neural network-based on monthly streamflow prediction models to produce energy from small Hydro power plant in along of Pungwe river basin in Mozambique.
The dataset used in this modelling experiment was a time series of average monthly river discharge see Figure.1 and during the period 1954 to 2004, which was collect from the Ara centro gauging hydrological station in the pungwe river basin Manica, and this study applied time series models for different matlab program like ANN,WANN, ANFIS, WANFIS at Pungwe basin station in Manica, Mozambique including the statistics tools ,RMSE, MAE, R2.
Miguel Meque Uamusse1, 3, Petro NdalilaM2, Alberto JúlioTsamba3, Frede de Oliveira Carvalho4, Kenneth Person1
1Department of Water Resource, Lund University, Lund, Sweden
2Department of Mechanical Engineering ,Mbeya University of Science and Technology, Mbea,Tanzania
3Faculdade de Engenharia, Universidade Eduardo Mondlane, Maputo, Mozambique
4Departamento de Engenharia Química , Universidade Federal de Alagoas, Brazil