Estimation of suspended sediment yield flowing into Inanda Dam using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8612

@MastersThesis{Jaiyeola:masters,

• author = "Adesoji Tunbosun Jaiyeola",
• title = "Estimation of suspended sediment yield flowing into {Inanda Dam} using genetic programming",
• school = "Durban University of Technology",
• year = "2016",
• type = "Master of Engineering",
• address = "Durban, South Africa",
• month = dec,
• keywords = "genetic algorithms, genetic programming",
• URL = "http://hdl.handle.net/10321/1495",
• URL = "http://ir.dut.ac.za/bitstream/handle/10321/1495/JAIYEOLA_2016.pdf",
• size = "175 pages",
• abstract = "Reservoirs are designed to specific volume called the dead storage to be able to withstand the quantity of particles in the rivers flowing into it during its design period called its economic life. Therefore, accurate calculation of the quantities of sediment being transported is of great significance in environment engineering, hydroelectric equipment longevity, river aesthetics, pollution and channel navigability. In this study different input combination of monthly upstream suspended sediment concentration and upstream flow dataset for Inanda Dam for 15 years was used to develop a model for each month of the year. The predictive abilities of each of the developed model to predict the quantity of suspended sediment flowing into Inanda Dam were also compared with those of the corresponding developed Sediment Rating Curves using two evaluation criteria - Determination of Coefficient (R 2 ) and Root-Mean-Square Error (RMSE). The results from this study show that a genetic programming approach can be used to accurately predict the relationship between the streamflow and the suspended sediment load flowing into Inanda Dam. The twelve developed monthly genetic programming (GP)...",
• notes = "KwaZulu-Natal advisor Josiah Adeyemo",

}

Genetic Programming entries for Adesoji Tunbosun Jaiyeola

Citations