Review of studies on hydrological modelling in Malaysia
Hydrological models are vital component and essential tools for water resources and
environmental planning and management. In recent times, several studies have been …
environmental planning and management. In recent times, several studies have been …
Rainfall prediction using machine learning models: literature survey
Research on rainfall prediction contributes to different fields that have a huge impact on our
daily life. With the advancement of computer technology, machine learning has been …
daily life. With the advancement of computer technology, machine learning has been …
Monthly rainfall forecasting modelling based on advanced machine learning methods: Tropical region as case study
Existing forecasting methods employed for rainfall forecasting encounter many limitations,
because the difficulty of the underlying mathematical proceeding in dealing with the …
because the difficulty of the underlying mathematical proceeding in dealing with the …
A novel approach for precipitation forecast via improved K-nearest neighbor algorithm
M Huang, R Lin, S Huang, T Xing - Advanced Engineering Informatics, 2017 - Elsevier
The prediction method plays crucial roles in accurate precipitation forecasts. Recently,
machine learning has been widely used for forecasting precipitation, and the K-nearest …
machine learning has been widely used for forecasting precipitation, and the K-nearest …
A survey on rainfall forecasting using artificial neural network
Rainfall has a great impact on agriculture and people's daily travel, so accurate prediction of
precipitation is well worth studying for researchers. Traditional methods like numerical …
precipitation is well worth studying for researchers. Traditional methods like numerical …
MapReduce and optimized deep network for rainfall prediction in agriculture
A JP - The Computer Journal, 2020 - academic.oup.com
Rainfall prediction is the active area of research as it enables the farmers to move with the
effective decision-making regarding agriculture in both cultivation and irrigation. The existing …
effective decision-making regarding agriculture in both cultivation and irrigation. The existing …
An empirical-based rainfall-runoff modelling using optimization technique
This study proposes a new hybrid biogeography-based optimization (BBO) technique to
achieve a better balance between exploitation and exploration sides of BBO. The proposed …
achieve a better balance between exploitation and exploration sides of BBO. The proposed …
Rainfall modeling using two different neural networks improved by metaheuristic algorithms
Rainfall is crucial for the development and management of water resources. Six hybrid soft
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …
[HTML][HTML] PSPSO: A package for parameters selection using particle swarm optimization
This paper reports a high-level python package for selecting machine learning algorithms
and ensembles of machine learning algorithms parameters by using the particle swarm …
and ensembles of machine learning algorithms parameters by using the particle swarm …
Forecasting different types of droughts simultaneously using multivariate standardized precipitation index (MSPI), MLP neural network, and imperialistic competitive …
P Aghelpour, V Varshavian - Complexity, 2021 - Wiley Online Library
Precipitation deficit causes meteorological drought, and its continuation appears as other
different types of droughts including hydrological, agricultural, economic, and social …
different types of droughts including hydrological, agricultural, economic, and social …