Evaluation of random forests and generalized regression neural networks for daily reference evapotranspiration modelling.
Sign Up to like & getrecommendations! Published in 2017 at "Agricultural Water Management"
DOI: 10.1016/j.agwat.2017.08.003
Abstract: Abstract Accurate estimation of reference evapotranspiration (ET 0 ) is of importance for regional water resource management. The present study proposed two artificial intelligence models, random forests (RF) and generalized regression neural networks (GRNN), for… read more here.
Keywords: regression neural; neural networks; random forests; generalized regression ... See more keywords
Short term load forecasting based on feature extraction and improved general regression neural network model
Sign Up to like & getrecommendations! Published in 2019 at "Energy"
DOI: 10.1016/j.energy.2018.10.119
Abstract: Along with the deregulation of electric power market as well as aggregation of renewable resources, short term load forecasting (STLF) has become more and more momentous. However, it is a hard task due to various… read more here.
Keywords: term load; load forecasting; load; short term ... See more keywords
Application of general regression neural network to model a novel integrated fluidized bed gasifier
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Hydrogen Energy"
DOI: 10.1016/j.ijhydene.2018.01.130
Abstract: Abstract In order to better understand gasification performance, a general regression neural network (GRNN) was developed to model a novel integrated fluidized bed (IFB) gasifier to research the correlative relationship between the input and output… read more here.
Keywords: model novel; regression neural; regression; model ... See more keywords
Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Chemical Theory and Computation"
DOI: 10.1021/acs.jctc.1c00813
Abstract: The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of… read more here.
Keywords: neural network; network approaches; regression; kernel regression ... See more keywords
Time Series Forecasting by Generalized Regression Neural Networks Trained With Multiple Series
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3140377
Abstract: Time series forecasting plays a key role in many fields such as business, energy or environment. Traditionally, statistical or machine learning models for time series forecasting are trained with the historical values of the series… read more here.
Keywords: generalized regression; time series; regression neural; series ... See more keywords
Yarn unevenness prediction using generalized regression neural network under various optimization algorithms
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Engineered Fibers and Fabrics"
DOI: 10.1177/15589250221093019
Abstract: Unevenness is one of the important parameters for evaluating yarn quality, but the current prediction accuracy of yarn unevenness is low. One of the important reasons is that there are few sample dataset for yarn… read more here.
Keywords: neural network; optimization; regression neural; generalized regression ... See more keywords
Power load forecasting of general regression neural network based on particle swarm optimization
Sign Up to like & getrecommendations! Published in 2018 at "Chemical engineering transactions"
DOI: 10.3303/cet1866223
Abstract: To study the power load forecasting optimization of general regression neural network using particle swarm optimization. Refer to the domestic and foreign literature, The paper refers to domestic and foreign literature, by comparing the GRNN… read more here.
Keywords: regression neural; load forecasting; optimization; power load ... See more keywords
A Generalized Regression Neural Network Model for Predicting the Curing Characteristics of Carbon Black-Filled Rubber Blends
Sign Up to like & getrecommendations! Published in 2022 at "Polymers"
DOI: 10.3390/polym14040653
Abstract: In this study, a new generalized regression neural network model for predicting the curing characteristics of rubber blends with different contents of carbon black filler cured at various temperatures is proposed for the first time… read more here.
Keywords: neural network; carbon black; regression neural; generalized regression ... See more keywords