Journal ArticleDOI
Artificial neural networks for automated year-round temperature prediction
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In this paper, the authors explore the application of artificial neural networks (ANNs) for the prediction of air temperature during the entire year based on near real-time data and develop Ward-style ANNs using detailed weather data collected by the Georgia Automated Environmental Monitoring Network (AEMN).About:
This article is published in Computers and Electronics in Agriculture.The article was published on 2009-08-01. It has received 114 citations till now.read more
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Journal ArticleDOI
Relationships between Obesity and Cardiovascular Diseases in Four Southern States and Colorado
Luma Akil,H. Anwar Ahmad +1 more
TL;DR: The results of this study showed a low association between obesity and myocardial infarction rates; a moderate association with stroke rates; and a strong association with HBP rates.
Journal ArticleDOI
Evaluating machine learning approaches for the interpolation of monthly air temperature at Mt. Kilimanjaro, Tanzania
TL;DR: A combined Cubist and residual kriging approach can be considered the best solution for predicting spatial temperature patterns based on a network of temperature observation plots across the southern slopes of Mt. Kilimanjaro.
Journal ArticleDOI
Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System
Imran Ali Lakhiar,Gao Jianmin,Tabinda Naz Syed,Farman Ali Chandio,Noman Ali Buttar,Waqar Ahmed Qureshi +5 more
TL;DR: Aeroponics using intelligent techniques (wireless sensors) provides a wide range of information which could be essential for plant researchers and provides a greater understanding of how the key parameters of aeroponics correlate with plant growth in the system.
Journal ArticleDOI
Forecasting agricultural output with an improved grey forecasting model based on the genetic algorithm
TL;DR: In this paper, both modified background value calculation and use of a genetic algorithm to find the optimal parameters were adopted simultaneously to construct an improved GM(1,1) model (GAIGM 1,1)).
Proceedings ArticleDOI
Rice crop yield prediction using artificial neural networks
TL;DR: In this article, a multilayer perceptron neural network was used to predict rice production yield and investigate the factors affecting the rice crop yield for various districts of Maharashtra state in India.
References
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Book
Neural Networks: A Comprehensive Foundation
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
Journal ArticleDOI
An ensemble of neural networks for weather forecasting
TL;DR: Empirical results indicate that HFM is relatively less accurate and RBFN is relatively more reliable for the weather forecasting problem, while the ensemble of neural networks produced the most accurate forecasts.
Journal ArticleDOI
A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area.
Junsub Yi,Victor R. Prybutok +1 more
TL;DR: A neural network model for forecasting daily maximum ozone levels is developed that is superior to the regression and Box-Jenkins ARIMA models the authors tested and compared the neural network's performance with those of two traditional statistical models.
Journal ArticleDOI
Prediction of building's temperature using neural networks models
TL;DR: The design of inside air temperature predictive neural network models, to be used for predictive control of air-conditioned systems, is discussed and the performance of these data-driven models is compared, favourably, with a multi-node physically based model.
Journal ArticleDOI
Development of a neural network model to predict daily solar radiation
TL;DR: In this article, a neural network model was developed to predict solar radiation as a function of readily available weather data and other environmental variables, such as minimum and maximum air temperature and precipitation, together with daily calculated values for daylength and clear sky radiation.