Search Results - (( model relation bat algorithm ) OR ( whale identification system algorithm ))

Metaheuristic Algorithms and Neural Networks in Hydrology

“…It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.…”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

“…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”

Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

“…Thus, Bat Algorithm (BA) was used to enhance the efficiency of ANN in forecasting upstream river SF, as BA is capable of switching from the “explore to exploit” function which could increase the rate of convergence at the initial stage and deliver a quick result for a majority of a classification problem. …”

Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…In addition, Chaotic Local Search Whale Optimization Algorithm-based Feature Selection (CLSWOA-FS) technique is employed to choose the optimal feature subsets. …”
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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.

“…In this study, the accuracy of two hybrid model, support vector machine - particle swarm optimization (SVM-PSO) and bat algorithm - backpropagation neural network (BA-BPNN) for monthly streamflow forecasting at Kuantan River located in Peninsular Malaysia are investigated and compared to regular SVM and BPNN model. …”

A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems by Yaseen, Zaher, Ehteram, Mohammad, Hossain, Md., Fai, Chow, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, Lai, Sai Hin, Zaini, Nuratiah, Ahmed, Ali, El-Shafie, Ahmed

“…The current research is devoted to the implementation of hybrid novel meta-heuristic algorithms (e.g., the bat algorithm (BA) and particle swarm optimization (PSO) algorithm) to formulate multi-purpose systems for power production and irrigation supply. …”
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A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: Application to multi-purpose reservoir systems by Yaseen Z.M., Ehteram M., Hossain M.S., Fai C.M., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., Hin L.S., Zaini N., Ahmed A.N., El-Shafie A.