Search Results - rainfall optimization method algorithm

SINE COSINE ALGORITHM BASED NEURAL NETWORK FOR RAINFALL DATA IMPUTATION by Chiu, Po Chan, Ali, Selamat, Kuok, King Kuok

“…This chapter presents the ability of the sine cosine algorithm-based neural network (SCANN) to predict and optimize missing rainfall at different percentages of missing rates. …”
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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.

Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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Weather Prediction for Strawberry Cultivation Using Double Exponential Smoothing and Golden Section Optimization Methods by Herlinah, Asrul, Billy Eden William, Hafsah, Faisal, Muhammad, Lee Lee, Swa, Gani, Hamdan, Feng, Zhipeng

“…The system was developed by implementing the PHP programming language on the interface design as well as MySQL as a database processing. The algorithm used to predict the air temperature feature, wind speed feature, and rainfall feature was Double Exponential Smoothing, followed by the optimization of the Golden Section method to select the right smoothing value. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…A coati optimization algorithm is introduced to select input scenarios. …”

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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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network by Chiu, Po Chan, Ali, Selamat, Ondrej, Krejcar, Kuok, King Kuok, Enrique, Herrera-Viedma, Giuseppe, Fenza

“…Second, a sine cosine algorithm is presented to optimize neural network for infilling the missing rainfall data. …”
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Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

“…In conclusion, this finding contributes toward the development of models using evolution algorithm and statistical methods for sustainable water resources planning and management in the context of future climate change…”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…The application of FES optimized by GA on regionalization creates opportunities for further researches which utilizes different types of optimization like Ant Colony Optimization (ACO), ANN’s, Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA).…”
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Comparative study: Using machine learning techniques about rainfall prediction by Hasan R.A., Alomari M.F., Jamaluddin J.B.

“…Rainfall forecasting is a major problem because of the unreliability of existing methods for predicting rainfall. …”

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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Rainfall time series modeling for a mountainous region in West Iran by Mekanik, Fatemeh

“…One of the major problems of water resources management is rainfall forecasting. Different linear and non-linear methods have been used in order to have an accurate forecast. …”
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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill by Abunama, Taher, Othman, Faridah, Ansari, Mozafar, El-Shafie, Ahmed

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Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction by Ehteram M., Ahmed A.N., Latif S.D., Huang Y.F., Alizamir M., Kisi O., Mert C., El-Shafie A.

Bat algorithm and neural network for monthly streamflow prediction by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

“…BA is an optimization technique, which is to optimize BPNN in deciding optimum parameters and then improve the prediction accuracy. …”

An equijoin-optimization technique for Malaysian Hydrological Information System (MHIS) data by Kurmin, Norazrin, Selamat, Harihodin, Wahid, Mohd. Taib, Mohd. Rahim, Mohd. Shafry

“…Thus, this paper proposed an Equijoin Optimization Technique to solve that problem. This technique was introduced based on modification of an equijoin method where an entity will be joined based on equijoin algorithm. …”
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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.

Artificial neural networks for water level prediction based on Z-score technique in Kelantan river / Khairah Jaafar ...[et al.] by Jaafar, Khairah, Ismail, Nurlaila, Tajjudin, Mazidah, Adnan, Ramli, Rahiman, Mohd Hezri Fazalul

“…The ANN model was formulated to simulate water level using feedforward algorithm. Readings from 6 stations from rainfall stations showed that S1, S2, S3 and S6 code station while S1 and S2 for water level station were significant value based on ZScore processing method. …”
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