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Balanced Stochastic Realization Algorithm For Development Of Rainfall Model by Azhari, Fahimy

“…In this research, Balanced Stochastic Realization (BSR) subspace algorithm is used to develop a rainfall model for Malaysia. …”
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Rainfall-funoff modelling in batang layar and oya sub-catchments using pre-developed ann model for tinjar catchment by Awangku Faizal Sallehin, Awangku Brahim

“…Artificial Neural Network (ANN) has been widely used to forecast Rainfall-Runoff relationships. Many ANN has been developed by experts in order to forecast RainfallRunoff relationships in certain catchment. …”
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Rainfall forecasting model using machine learning methods: Case study Terengganu, Malaysia by Ridwan W.M., Sapitang M., Aziz A., Kushiar K.F., Ahmed A.N., El-Shafie A.

Satellite based quantitative rainfall estimation for flash flood forecasting / Wardah Tahir by Tahir, Wardah

“…In this study, a rainfall estimation algorithm using the information from the geostationary meteorological satellite infrared (IR) images is developed for potential input to a flood forecasting system. …”
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Daily Rainfall Forecasting Using Meteorology Data with Long Short-Term Memory (LSTM) Network by Soo See, Chai, Goh, Kok Luong

“…Rainfall is a natural climatic phenomenon and prediction of its value is crucial for weather forecasting. …”
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Investigation of Multimodel Ensemble Performance Using Machine Learning Method for Operational Dam Safety by Basri H., Marufuzzaman M., Mohd Sidek L., Ismail N.

“…Hence, consideration of the development of more flexible inflow forecasting systems is needed. …”

Development of trees management system using radial basis function neural network for rain forecast by Auzani, Hasnul, Hashim, Khairusy Syakirin Has-Yun, Mohd Nazri, Farah Aniza

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Daily rainfall prediction using clonal selection algorithm by Noor Rodi, Nur Syazwani, Ismail , Amelia Ritahani, Abdul Malik, Marlinda

“…This paper utilizes Artificial Immune System (AIS) algorithm for daily rainfall prediction where rainfall is used as input nodes. …”
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Rainfall time series modeling for a mountainous region in West Iran by Mekanik, Fatemeh

“…A feedforward Artificial Neural Network (ANN) rainfall model and a Seasonal Autoregressive Integrated Moving Average (SARIMA) rainfall model were developed to investigate their potentials in forecasting rainfall. …”
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Neural network application in the change of reservoir water level stage forecasting by Ashaary, Nur Athirah, Wan Ishak, Wan Hussain, Ku-Mahamud, Ku Ruhana

“…Artificial Neural Network is one of the computational algorithms that can be applied in developing a forecasting model for the change of reservoir water level stage.Forecasting of the change of reservoir water level stage is vital as the change of the reservoir water level can affect the reservoir operator’s decision.The decision of water release is very critical in both flood and drought seasons where the reservoir should maintain high volume of water during less rainfall and enough space for incoming heavy rainfall. …”
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Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

“…To forecast unexpected flood occurrences, faster flood prediction necessitates computational prediction models such as Machine Learning (ML) algorithms, which are extensively utilized around the world. …”

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

“…In this study, the ANNs were developed specifically to forecast the hourly rainfall-runoff for Buan Bidi Station. …”
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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. …”

Implementation of machine learning algorithms for streamflow prediction of Dokan dam by Sarmad Dashti Latif, Mr.

“…Daily inflow and rainfall time-series data have been collected as two hydrological parameters to forecast reservoir inflow using the developed deep learning long-short term memory (LSTM) model and conventional machine learning models, namely support vector machine (SVM), random forest (RF), and boosted regression tree (BRT). …”

Artificial neural networks (ANNS) for daily rainfall runoff modelling by Kuok, King Kuok, Nabil, Bessaih

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Forecasting model for the change in stage of reservoir water level by Nur Athirah, Ashaary

“…This study is aimed to develop a forecasting model for the change in stage of reservoir water level. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

“…This study concluded that Relevance Vector Machine (RVM) models are suitable for forecasting future rainfall since they can support large rainfall extremes and generate reliable daily rainfall estimates based on rainfall extremes. …”
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Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data by Jajarmizadeh M., Sidek L.M., Mirzai M., Alaghmand S., Harun S., Majid M.R.

Extreme gradient boosting (Xgboost) model to predict the groundwater levels in Selangor Malaysia by Ibrahem Ahmed Osman A., Najah Ahmed A., Chow M.F., Feng Huang Y., El-Shafie A.

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. …”