Prediction of flow discharge in Mahanadi River Basin, India, based on novel hybrid SVM approaches
S Samantaray, A Sahoo - Environment, Development and Sustainability, 2024 - Springer
Accurate monthly flow discharge prediction can yield significant evidence for sustainable
management of water resources systems, optimal water allocation and use, mitigating flood …
management of water resources systems, optimal water allocation and use, mitigating flood …
Prediction of soil temperature using regression and artificial neural network models
M Bilgili - Meteorology and atmospheric physics, 2010 - Springer
In this study, monthly soil temperature was modeled by linear regression (LR), nonlinear
regression (NLR) and artificial neural network (ANN) methods. The soil temperature and …
regression (NLR) and artificial neural network (ANN) methods. The soil temperature and …
Metaheuristic optimization algorithms hybridized with artificial intelligence model for soil temperature prediction: Novel model
An enhanced hybrid artificial intelligence model was developed for soil temperature (ST)
prediction. Among several soil characteristics, soil temperature is one of the essential …
prediction. Among several soil characteristics, soil temperature is one of the essential …
[HTML][HTML] Forecasting soil temperature at multiple-depth with a hybrid artificial neural network model coupled-hybrid firefly optimizer algorithm
S Samadianfard, MA Ghorbani… - Information Processing in …, 2018 - Elsevier
Forecasting soil temperature at multiple depths is considered to be a core decision-making
task for examining future changes in surface and sub-surface meteorological processes …
task for examining future changes in surface and sub-surface meteorological processes …
[PDF][PDF] Integrating granger causality and vector auto-regression for traffic prediction of large-scale WLANs
Flexible large-scale WLANs are now widely deployed in crowded and highly mobile places
such as campus, airport, shopping mall and company etc. But network management is hard …
such as campus, airport, shopping mall and company etc. But network management is hard …
Chaos-based multigene genetic programming: A new hybrid strategy for river flow forecasting
Chaos theory is integrated with Multi-Gene Genetic Programming (MGGP) engine as a new
hybrid model for river flow forecasting. This is to be referred to as Chaos-MGGP and its …
hybrid model for river flow forecasting. This is to be referred to as Chaos-MGGP and its …
SVR-based prediction of evaporation combined with chaotic approach
Ö Baydaroğlu, K Koçak - Journal of Hydrology, 2014 - Elsevier
Evaporation, temperature, wind speed, solar radiation and relative humidity time series are
used to predict water losses. Prediction of evaporation amounts is performed using Support …
used to predict water losses. Prediction of evaporation amounts is performed using Support …
Enhancement of neural networks model's predictions of currencies exchange rates by phase space reconstruction and Harris Hawks' optimization
Predictions of variations in exchange rates of other currencies to a vehicle currency such as
the Dollar (USD) are vital in order to reduce the risks for international transactions. In this …
the Dollar (USD) are vital in order to reduce the risks for international transactions. In this …
Artificial neural network model for estimating the soil temperature
Ozturk, M., Salman, O. and Koc, M. 2011. Artificial neural network model for estimating the
soil temperature. Can. J. Soil Sci. 91: 551–562. Although soil temperature is a critically …
soil temperature. Can. J. Soil Sci. 91: 551–562. Although soil temperature is a critically …
Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques
M Flach, F Gans, A Brenning, J Denzler… - Earth System …, 2017 - esd.copernicus.org
Today, many processes at the Earth's surface are constantly monitored by multiple data
streams. These observations have become central to advancing our understanding of …
streams. These observations have become central to advancing our understanding of …