Identification of greenhouse temperature system using time series based on the NARX model
Author:
Affiliation:
1. Moulay Ismail University,Computer Engineering and Intelligent Eletrical Systems Laboratory, High School of Technology,Meknes,Morocco
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9982722/9982807/09982952.pdf?arnumber=9982952
Reference19 articles.
1. A two-step combined algorithm based on NARX neural network and the subsequent prediction of the residues improves prediction accuracy of the greenhouse gases concentrations
2. Prediction of Tomato Yield in Chinese-Style Solar Greenhouses Based on Wavelet Neural Networks and Genetic Algorithms
3. Carbon dioxide reforming of methane over Ni-based catalysts: Modeling the effect of process parameters on greenhouse gasses conversion using supervised machine learning algorithms
4. Estimation of in-situ biogas upgrading in microbial electrolysis cells via direct electron transfer: Two-stage machine learning modeling based on a NARX-BP hybrid neural network
5. Application of Nonlinear Time Series and Machine Learning Algorithms for Forecasting Groundwater Flooding in a Lowland Karst Area
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