Forecasting of drought can be very useful in preparing to reduce its impacts, especially in
the agricultural sector. Three machine learning models of MLP neural network, GRNN …

The accuracy of four evolutionary neuro fuzzy methods, adaptive neuro-fuzzy inference
system with particle swarm optimization (ANFIS-PSO), ANFIS with genetic algorithm (ANFIS …

This review chapter discusses drought index predictions with data intelligent methods. Due
to massive climate change owing to temperature increments, water resources have faced a …

The modelling of drought is of utmost importance for the efficient management of water
resources. This article used the adaptive neuro-fuzzy interface system (ANFIS), multilayer …

Drought modeling is vital for designing and managing water resource systems due to its
significant effects on agriculture and other components of the environment. This study …

The present study aimed to model reconnaissance drought index (RDI) time series at three
various time scales (ie, RDI-6, RDI-9, RDI-12). Two weather stations located at Iran, namely …

Quantification and prediction of drought events are important for planning and management
of water resources in coping with climate change scenarios at global and local scales. In this …

Drought is among the most important natural disasters influencing different aspects of
human life. In recent decades, intelligent techniques have shown to be highly capable of …

A new version of the fuzzy logic model, called the co-active neuro fuzzy inference system
(CANFIS), is introduced for predicting standardized precipitation index (SPI). Multiple scales …

Climate change has increased drought frequency globally, which harms the environment,
agriculture, and water resources. This study explores the capacity of a hybrid model based …