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Prediction of Evapotranspiration in a Mediterranean Region Using Basic Meteorological Variables
2017
Journal of hydrologic engineering
Evapotranspiration 24 Manuscript Click here to download Manuscript HEENG-3310_R1.docx gionalize the crop coefficients and calculate evapotranspiration from the values of refer-37 ence evapotranspiration ...
The results demonstrated the usefulness 40 and accuracy of the methodology to predict the water demands of crops and hence enable 41 farmers to plan their irrigation needs. 42 43 Keywords 44 45 Cluster ...
The most influential predictors were those related to temperature in general, with the exception of the colder months, wherein relative humidity and wind speed proved to be the greatest contributors for ...
doi:10.1061/(asce)he.1943-5584.0001485
fatcat:kcqttcrtkrb5feni5iiyog2kfa
Combining Thermal and RGB Imaging Indices with Multivariate and Data-Driven Modeling to Estimate the Growth, Water Status, and Yield of Potato under Different Drip Irrigation Regimes
2021
Remote Sensing
neuro-fuzzy inference system with a genetic algorithm (ANFIS-GA) for monitoring the biomass fresh weight (BFW), biomass dry weight (BDW), biomass water content (BWC), and total tuber yield (TTY) of two ...
potato varieties under 100%, 75%, and 50% of the estimated crop evapotranspiration (ETc). ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13091679
doaj:08a2ca28fed04abf82b73726e65bff03
fatcat:4me7q7fvg5enfff34jw7tsyfdq
Review of Artificial Intelligence Applied in Decision-Making Processes in Agricultural Public Policy
2020
Processes
The objective of this article is to review how Artificial Intelligence (AI) tools have helped the process of formulating agricultural public policies in the world. ...
The findings have shown that, first, the most commonly used AI tools are agent-based models, cellular automata, and genetic algorithms. ...
Acknowledgments: The authors express gratitude to the Universidad Distrital Francisco José de Caldas.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/pr8111374
fatcat:47qbjwmrmjfxhke2iv45mbijni
Evaluation of models for the dew point temperature determination
2017
Technical Sciences
The accuracy of the available from the literature models for the dew point temperature determination was compared. The proposal of the modelling using artificial neural networks was also given. ...
The accuracies of the models were measured using the mean bias error MBE, root mean square error RMSE, correlation coefficient R, and reduced chi-square χ2. ...
MOHAMMADI et al. (2016) applied adaptive neuro fuzzy inference system (ANFIS) to select the most influential parameters for prediction of daily dew point temperature. ...
doi:10.31648/ts.5425
fatcat:6n57pg3u5vhz7ls7okgziqk5ti
Flood Prediction Using Machine Learning Models: Literature Review
2018
Water
The research on the advancement of flood prediction models contributed to risk reduction, policy suggestion, minimization of the loss of human life, and reduction of the property damage associated with ...
on the various ML algorithms used in the field. ...
Adaptive neuro-FIS, or so-called ANFIS, is a more advanced form of neuro-fuzzy based on the T-S FIS, first coined [67, 77] . ...
doi:10.3390/w10111536
fatcat:5ewkgi4oibbkhn7nievusbyrim
Artificial Neural Network–Based Drought Forecasting Using a Nonlinear Aggregated Drought Index
2012
Journal of hydrologic engineering
The Artificial Neural Network (ANN) technique, which has proved to be one of the most successful drought forecasting modeling techniques, was then used to develop and test several drought forecasting models ...
Based on the findings of the evaluation study, a new Nonlinear Aggregated Drought Index (NADI) was developed and evaluated for the Yarra River catchment. ...
The Adaptive Neuro-Fuzzy Inference System (ANFIS), consisting of the combination of ANN and FIS, has been used by many researchers to organize the network structure itself and to adapt the parameters of ...
doi:10.1061/(asce)he.1943-5584.0000574
fatcat:3om2fy6uibe23bvekumaiimwwq
Hydrological Modeling in an Ungauged Basin of Central Vietnam Using SWAT Model
2016
Hydrology and Earth System Sciences Discussions
The model was calibrated in three time scales: daily, monthly and yearly by river discharge, actual evapotranspiration (ETa) and crop yield, respectively. ...
The monthly average of actual evapotranspiration was the highest in May and lowest in December. ...
,and Bonakdari, H.:
Determination of the Most Influential Weather Parameters on Reference Evapotranspiration by Adaptive Neuro-
25 Fuzzy Methodology. ...
doi:10.5194/hess-2016-44
fatcat:orv6v7il7fduzk63yphw5etcni
Machine Learning in Agriculture: A Comprehensive Updated Review
2021
Sensors
The present study aims at shedding light on machine learning in agriculture by thoroughly reviewing the recent scholarly literature based on keywords' combinations of "machine learning" along with "crop ...
In addition, maize and wheat as well as cattle and sheep were the most investigated crops and animals, respectively. ...
Boosting
ADT
DT
Alternating Decision Trees
ANFIS
ANN
Adaptive-Neuro Fuzzy Inference Systems
ARD
BM
Automatic Relevance Determination
Bayesian-ANN
ANN
Bayesian Artificial Neural Network
BAG ...
doi:10.3390/s21113758
pmid:34071553
fatcat:moehdvs6efdpxpklidutmw2ary
Smart Indoor Farms: Leveraging Technological Advancements to Power a Sustainable Agricultural Revolution
2021
AgriEngineering
Smart indoor farms offer the potential to remedy the shortfalls of conventional farms by providing a controlled, intelligent, and smart environment. ...
However, with the evolution of technology (and when they become widely available in the near future), a more favourable farming scenario may emerge. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/agriengineering3040047
fatcat:aiiydc3dovecrc6u43kupid3ti
A review of regression models employed for predicting diffuse solar radiation in North-Western Africa
2017
Trends in Renewable Energy
The regression models so far utilized were classified into six main categories and presented based on the input parameters applied. ...
The knowledge of diffuse solar radiation (Hd) is of almost importance for determining the gross primary productivity, net ecosystem, exchange of carbon dioxide, light use efficiency and changing colour ...
Acknowledgements Our thanks go to all the authors cited in this paper for their research works that have made this research possible. ...
doi:10.17737/tre.2017.3.2.0042
fatcat:d6j7jjq4z5ce3lw6hqf3xn3imi
Large-scale climate change vulnerability assessment of stream health
2016
Ecological Indicators
The goal of this study was to determine the extent of climate change impacts on stream ecosystems as represented by four commonly used stream health indicators (Ephemeroptera, Plecoptera, and Trichoptera ...
Important variables for each thermal class were selected using a Bayesian variable selection method and used as inputs to adaptive neuro-fuzzy inference systems models of EPT, FIBI, HBI, and IBI. ...
Adaptive neuro fuzzy inference system (ANFIS) (Jang, 1993) , a fusion of artificial neural networks (ANNs) and fuzzy logic, was used to develop the stream health models for each combination of stream ...
doi:10.1016/j.ecolind.2016.04.002
fatcat:pvxt7jopufdp5myggruujk4keq
Support vector machine applications in the field of hydrology: A review
2014
Applied Soft Computing
Furthermore, this review provides a brief synopsis of the techniques of SVMs and other emerging ones (hybrid models), which have proven useful in the analysis of the various hydrological parameters. ...
SVMs introduced by Vapnik and others in the early 1990s are machine learning systems that utilize a hypothesis space of linear functions in a high dimensional feature space, trained with optimization algorithms ...
Negative sediment estimates, which were encountered in the soft computing calculations using Fuzzy logic, ANN and Neuro-fuzzy, were not produced by SVM prediction. ...
doi:10.1016/j.asoc.2014.02.002
fatcat:gkcq34t4mnhibcotphbrnbusba
ITIKI: bridge between African indigenous knowledge and modern science of drought prediction
2011
Knowledge Management for Development Journal
Wherever contributions of other people are involved, every effort has been made to indicate this clearly, with due reference to the literature and acknowledgement. ...
Further, this work was done under the guidance of Dr ...
This is addressed in MATLAB via the Adaptive Neuro-Fuzzy Inference System (ANFIS). ...
doi:10.1080/19474199.2012.683444
fatcat:zkhefk7kgjdadasijz26yag3m4
Estimation of SPEI Meteorological Drought using Machine Learning Algorithms
2021
IEEE Access
Accurate estimation of drought events is vital for the mitigation of their adverse consequences on water resources, agriculture and ecosystems. ...
In this study, a combination of machine learning with the Standardized Precipitation Evapotranspiration Index (SPEI) is proposed for analysis of drought within a representative case study in the Tibetan ...
The investigation of [14] applied the Wavelet-ARIMA-ANN (WAANN) and the Wavelet-Adaptive Neuro-Fuzzy Inference System (WANFIS) models to predict the SPEI at the Langat River Basin in Malaysia for 1-month ...
doi:10.1109/access.2021.3074305
fatcat:7rj5zr3gmzgx3bk7brgksptkti
Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints
2006
Water resources management
Groundwater is one of the most valuable natural resources, which supports human health, economic development and ecological diversity. ...
The main intent of the present paper is to highlight RS and GIS technologies and to present a comprehensive review on their applications to groundwater hydrology. ...
Acknowledgements The present work was financially supported by the Alexander von Humboldt (AvH) Foundation, Bonn, Germany in terms of research fellowship to the first author. ...
doi:10.1007/s11269-006-9024-4
fatcat:hh5oscwawjfi3jjubrbmjcd6wi
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