Search Results - (( rainfall optimization model algorithm ) OR ( parameter optimization based algorithm ))

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This research utilizes a genetic algorithm (GA) to optimize the multi-layer FFNN performance and structure in modelling three datasets: network traffic, rainfall, and tourist. …”
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Improved prediction of daily pan evaporation using Bayesian Model Averaging and optimized Kernel Extreme Machine models in different climates by Ehteram M., Graf R., Ahmed A.N., El-Shafie A.

Suspended sediment load prediction using artificial neural network and ant lion optimization algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Ebrahimi M., Fai C.M., Huang Y.F., El-Shafie A.

A hybrid model using genetic algorithm and neural network for predicting dengue outbreak by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaakob, Razali

“…Several model architectures are designed and the parameters are adjusted to achieve optimal prediction performance. …”
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Regionalization by fuzzy expert system based approach optimized by genetic algorithm. by Chavoshi, Sattar, Sulaiman, Wan Nor Azmin, Saghafian, Bahram, Sulaiman, Md. Nasir, Abd Manaf, Latifah

“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Predicting crop yields using a new robust Bayesian averaging model based on multiple hybrid ANFIS and MLP models: Predicting crop yields using a new robust Bayesian averaging model by Bazrafshan O., Ehteram M., Dashti Latif S., Feng Huang Y., Yenn Teo F., Najah Ahmed A., El-Shafie A.

Neural Network – A Black Box Model by Kuok, Kuok King, Chan, Chiu Po, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said, Chin Mei, Yun

“…A variety of metaheuristic algorithms have been used to train ANN, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Tabu Search (TS), and Harmony Search (HS). …”
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River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

“…In this research, Artificial Neural Network (ANN) is integrated with a nature-inspired optimizer, namely Cuckoo search algorithm (CS-ANN). …”

Modelling hourly runoff using ann for sg. Sarawak Kanan Basin by Chong, Kah Weng.

“…This model generated the highest R Testing of 0.896 when trained with the scaled conjugate gradient algorithm (TRAINSCG). …”
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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. …”

Comparison of future intensity duration frequency curve by considering the impact of climate change: case study for Kuching city by Kuok, Kelvin K.K, Mah, D.Y.S., Imteaz, M.A, Kueh, S.M

“…Therefore, there is an initiative in this study to derive future IDF curve by considering the future rainfall using ‘delta’ approach. The annual maximum precipitations for 2020s, 2050s and 2080s are generated using Statistical Downscaling Model (SDSM), neural network (NN) with scale conjugate gradient and Cuckoo search optimization algorithms. …”
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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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Rainfall prediction using multiple inclusive models and large climate indices by Mohamadi S., Sheikh Khozani Z., Ehteram M., Ahmed A.N., El-Shafie A.

Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar by Jaafar, Jurina

“…The development of the model strongly depends on the physical based parameters, examples of physical parameters that include roughness Manning’s n, hydraulic conductivity, soil depth, river geometry and the surface land cover. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). …”
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DEVELOPMENT OF MULTI-VERSE OPTIMIZER IN ARTIFICIAL NEURAL NETWORK FOR ENHANCING THE IMPUTATION ACCURACY OF DAILY RAINFALL OBSERVATIONS by Lai, Wai Yan, Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman

“…The comparison was conducted by reconstructing 20% of artificially missing daily rainfall data for Kuching Third Mile Station. Optimal hyperparameters for the ANN models were determined through trial-and-error combined with 5-fold cross-validation approaches. …”
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Rainfall-runoff model based on ANN with LM, BR and PSO as learning algorithms by Mohd Romlay, Muhammad Rabani, Rashid, Muhammad Mahbubur, Toha @ Tohara, Siti Fauziah, Mohd Ibrahim, Azhar

“…In this paper, the ANN rainfall-runoff models are trained by the Levenberg Marquardt (LM), Bayesian Regularization (BR) and Particle Swarm Optimization (PSO). …”
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Rainfall-rinoff model based on ANN with LM, BR and PSO as learning algorithms by Mohd Romlay, Muhammad Rabani, Rashid, Muhammad Mahbubur, Toha @ Tohara, Siti Fauziah, Mohd Ibrahim, Azhar

“…In this paper, the ANN rainfall-runoff models are trained by the Levenberg Marquardt (LM), Bayesian Regularization (BR) and Particle Swarm Optimization (PSO). …”
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