Search Results - (( developing forecasting bat algorithm ) OR ( java visualization mining algorithm ))

A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

“…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
Get full text
Get full text

Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

“…Both standalone and hybrid models were developed to identify the most optimum parameter to be used for river SF forecasting. …”

Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

Support vector machine and neural network based model for monthly stream flow forecasting by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

“…Accurate forecasting of streamflow is desired in many water resources planning and management, flood prevention and design development. …”

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
Get full text
Get full text
Get full text

Rainfall modeling using two different neural networks improved by metaheuristic algorithms by Sammen S.S., Kisi O., Ehteram M., El-Shafie A., Al-Ansari N., Ghorbani M.A., Bhat S.A., Ahmed A.N., Shahid S.

“…Rainfall is crucial for the development and management of water resources. Six hybrid soft computing models, including�multilayer perceptron (MLP)�Henry gas solubility optimization (HGSO), MLP�bat algorithm (MLP�BA), MLP�particle swarm optimization (MLP�PSO), radial basis neural network function (RBFNN)�HGSO, RBFNN�PSO, and RBFGNN�BA, were used in this study to forecast monthly rainfall at two stations in Malaysia (Sara and Banding). …”