AIMC Topic: Agricultural Irrigation
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Appraising water resources for irrigation and spatial analysis based on fuzzy logic model in the tribal-prone areas of Bangladesh.
Environmental monitoring and assessment
Jun 21, 2024
The lack of quality water resources for irrigation is one of the main threats for sustainable farming. This pioneering study focused on finding the best area for farming by looking at irrigation water quality and analyzing its location using a fuzzy ...
Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data.
Water research
May 31, 2024
The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. Th...
Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model.
Environmental science and pollution research international
May 29, 2024
An in-depth understanding of nitrate-contaminated surface water and groundwater quality and associated risks is important for groundwater management. Hydrochemical characteristics and driving forces of groundwater quality and non-carcinogenic risks o...
Prediction of monthly evapotranspiration by artificial neural network model development with Levenberg-Marquardt method in Elazig, Turkey.
Environmental science and pollution research international
Feb 21, 2024
The phenomenon of evapotranspiration (ET) is closely linked to the issue of water scarcity, as it involves water loss through both evaporation and plant transpiration. Accurate prediction of evapotranspiration is of utmost importance in the strategic...
Daily reference evapotranspiration prediction for irrigation scheduling decisions based on the hybrid PSO-LSTM model.
PloS one
Apr 18, 2023
The shortage of available water resources and climate change are major factors affecting agricultural irrigation. In order to improve the irrigation water use efficiency, it is necessary to predict the water requirements for crops in advance. Referen...
Efficacy of GIS-based AHP and data-driven intelligent machine learning algorithms for irrigation water quality prediction in an agricultural-mine district within the Lower Benue Trough, Nigeria.
Environmental science and pollution research international
Feb 1, 2023
Agricultural productivity can be impaired by poor irrigation water quality. Therefore, adequate vulnerability assessment and identification of the most influential water quality parameters for accurate prediction becomes crucial for enhanced water re...
Evaluation and prediction of irrigation water quality of an agricultural district, SE Nigeria: an integrated heuristic GIS-based and machine learning approach.
Environmental science and pollution research international
Jan 9, 2023
Poor irrigation water quality can mar agricultural productivity. Traditional assessment of irrigation water quality usually requires the computation of various conventional quality parameters, which is often time-consuming and associated with errors ...
Comparison of neuron-based, kernel-based, tree-based and curve-based machine learning models for predicting daily reference evapotranspiration.
PloS one
May 31, 2019
Accurately predicting reference evapotranspiration (ET0) with limited climatic data is crucial for irrigation scheduling design and agricultural water management. This study evaluated eight machine learning models in four categories, i.e. neuron-base...
Remote Control of Greenhouse Vegetable Production with Artificial Intelligence-Greenhouse Climate, Irrigation, and Crop Production.
Sensors (Basel, Switzerland)
Apr 16, 2019
The global population is increasing rapidly, together with the demand for healthy fresh food. The greenhouse industry can play an important role, but encounters difficulties finding skilled staff to manage crop production. Artificial intelligence (AI...
Research on soil moisture prediction model based on deep learning.
PloS one
Apr 3, 2019
Soil moisture is one of the main factors in agricultural production and hydrological cycles, and its precise prediction is important for the rational use and management of water resources. However, soil moisture involves complex structural characteri...
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