[HTML][HTML] Deep learning based computer vision approaches for smart agricultural applications
The agriculture industry is undergoing a rapid digital transformation and is growing powerful
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …
An integrated statistical-machine learning approach for runoff prediction
Nowadays, great attention has been attributed to the study of runoff and its fluctuation over
space and time. There is a crucial need for a good soil and water management system to …
space and time. There is a crucial need for a good soil and water management system to …
Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India
Agricultural droughts are a prime concern for economies worldwide as they negatively
impact the productivity of rain-fed crops, employment, and income per capita. In this study …
impact the productivity of rain-fed crops, employment, and income per capita. In this study …
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 …
Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR …
Agriculture, meteorological, and hydrological drought is a natural hazard which affects
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
Modelling daily reference evapotranspiration based on stacking hybridization of ANN with meta-heuristic algorithms under diverse agro-climatic conditions
Precise estimation of reference evapotranspiration (ET0) is crucial for efficient agricultural
water management, crop modelling, and irrigation scheduling. In recent years, the data …
water management, crop modelling, and irrigation scheduling. In recent years, the data …
Pre-and post-dam river water temperature alteration prediction using advanced machine learning models
Dams significantly impact river hydrology by changing the timing, size, and frequency of low
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
Application of innovative machine learning techniques for long-term rainfall prediction
Rainfall forecasting is critical because it is the componen t that has the strongest link to
natural disasters such as landslides, floods, mass movements, and avalanches. The present …
natural disasters such as landslides, floods, mass movements, and avalanches. The present …
Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration
For develo** countries, scarcity of climatic data is the biggest challenge, and model
development with limited meteorological input is of critical importance. In this study, five data …
development with limited meteorological input is of critical importance. In this study, five data …
Prediction of streamflow drought index for short-term hydrological drought in the semi-arid Yesilirmak Basin using Wavelet transform and artificial intelligence …
OM Katipoğlu - Sustainability, 2023 - mdpi.com
The prediction of hydrological droughts is vital for surface and ground waters, reservoir
levels, hydroelectric power generation, agricultural production, forest fires, climate change …
levels, hydroelectric power generation, agricultural production, forest fires, climate change …