A systematic literature review on machine learning applications for sustainable agriculture supply chain performance
Agriculture plays an important role in sustaining all human activities. Major challenges such
as overpopulation, competition for resources poses a threat to the food security of the planet …
as overpopulation, competition for resources poses a threat to the food security of the planet …
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
Predicting standardized streamflow index for hydrological drought using machine learning models
S Shamshirband, S Hashemi, H Salimi… - Engineering …, 2020 - Taylor & Francis
Hydrological droughts are characterized based on their duration, severity, and magnitude.
Among the most critical factors, precipitation, evapotranspiration, and runoff are essential in …
Among the most critical factors, precipitation, evapotranspiration, and runoff are essential in …
Estimation of SPEI meteorological drought using machine learning algorithms
Accurate estimation of drought events is vital for the mitigation of their adverse
consequences on water resources, agriculture and ecosystems. Machine learning …
consequences on water resources, agriculture and ecosystems. Machine learning …
Development of advanced artificial intelligence models for daily rainfall prediction
In this study, the main objective is to develop and compare several advanced Artificial
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …
Prediction of droughts over Pakistan using machine learning algorithms
Climate change has increased frequency, severity and areal extent of droughts across the
world in the last few decades magnifying their adverse impacts. Prediction of droughts is …
world in the last few decades magnifying their adverse impacts. Prediction of droughts is …
Forecasting of SPI and meteorological drought based on the artificial neural network and M5P model tree
Climate change has caused droughts to increase in frequency and severity worldwide,
which has attracted scientists to create drought prediction models to mitigate the impacts of …
which has attracted scientists to create drought prediction models to mitigate the impacts of …
Meteorological drought forecasting based on a statistical model with machine learning techniques in Shaanxi province, China
R Zhang, ZY Chen, LJ Xu, CQ Ou - Science of the Total Environment, 2019 - Elsevier
Background Drought is a major natural disaster that causes severe social and economic
losses. The prediction of regional droughts may provide important information for drought …
losses. The prediction of regional droughts may provide important information for drought …
Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh
A noticeable increase in drought frequency and severity has been observed across the
globe due to climate change, which attracted scientists in development of drought prediction …
globe due to climate change, which attracted scientists in development of drought prediction …