A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …
with early applications including neural networks and expert systems. Since then, the field …
A review of machine learning methods for drought hazard monitoring and forecasting: Current research trends, challenges, and future research directions
Abstract Machine learning is a dynamic field with wide-ranging applications, including
drought modeling and forecasting. Drought is a complex, devastating natural disaster for …
drought modeling and forecasting. Drought is a complex, devastating natural disaster for …
Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas
Predicting water table depth over the long-term in agricultural areas presents great
challenges because these areas have complex and heterogeneous hydrogeological …
challenges because these areas have complex and heterogeneous hydrogeological …
Application of machine learning algorithms in plant breeding: predicting yield from hyperspectral reflectance in soybean
Recent substantial advances in high-throughput field phenotyping have provided plant
breeders with affordable and efficient tools for evaluating a large number of genotypes for …
breeders with affordable and efficient tools for evaluating a large number of genotypes for …
Seasonal drought prediction: Advances, challenges, and future prospects
Drought prediction is of critical importance to early warning for drought managements. This
review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid …
review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid …
Interpretable and explainable AI (XAI) model for spatial drought prediction
Accurate prediction of any type of natural hazard is a challenging task. Of all the various
hazards, drought prediction is challenging as it lacks a universal definition and is getting …
hazards, drought prediction is challenging as it lacks a universal definition and is getting …
Survey of computational intelligence as basis to big flood management: Challenges, research directions and future work
F Fotovatikhah, M Herrera… - Engineering …, 2018 - Taylor & Francis
Flooding produces debris and waste including liquids, dead animal bodies and hazardous
materials such as hospital waste. Debris causes serious threats to people's health and can …
materials such as hospital waste. Debris causes serious threats to people's health and can …
Artificial neural networks in drought prediction in the 21st century–A scientometric analysis
Droughts are the most spatially complex geohazard, which often lasts for years, thereby
severely impacting socio-economic sectors. One of the critical aspects of drought studies is …
severely impacting socio-economic sectors. One of the critical aspects of drought studies is …
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 …
Applications of hybrid wavelet–artificial intelligence models in hydrology: a review
Accurate and reliable water resources planning and management to ensure sustainable use
of watershed resources cannot be achieved without precise and reliable models …
of watershed resources cannot be achieved without precise and reliable models …