[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 …
High-performance self-compacting concrete with recycled coarse aggregate: comprehensive systematic review on mix design parameters
A Alyaseen, A Poddar, H Alahmad… - Journal of structural …, 2023 - Taylor & Francis
The technological advancements and environmental concerns enlighten the importance of
incorporating more high-performance engineered materials in the construction sector. The …
incorporating more high-performance engineered materials in the construction sector. The …
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 …
High-performance self-compacting concrete with recycled coarse aggregate: Soft-computing analysis of compressive strength
The growth of cities and industrialization has led to an increase in demand for concrete,
resulting in resource depletion and environmental issues. Sustainable alternatives such as …
resulting in resource depletion and environmental issues. Sustainable alternatives such as …
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 …
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 …
[HTML][HTML] Forecasting vapor pressure deficit for agricultural water management using machine learning in semi-arid environments
Precise evapotranspiration (ET) estimation is critical for agricultural water management,
particularly in water-stressed developing countries. Vapor Pressure Deficit is one of the ET …
particularly in water-stressed developing countries. Vapor Pressure Deficit is one of the ET …
A novel hybrid algorithms for groundwater level prediction
Estimating groundwater levels (GWL) with accuracy and reliability, in order to maximize the
use of water resources, it is crucial to reduce water consumption. To predict GWL in the …
use of water resources, it is crucial to reduce water consumption. To predict GWL in the …
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 …