Results 11 to 20 of about 75,093 (310)
Graph Neural Networks With Convolutional ARMA Filters [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Popular graph neural networks implement convolution operations on graphs based on polynomial spectral filters. In this paper, we propose a novel graph convolutional layer inspired by the auto-regressive moving average (ARMA) filter that, compared to ...
F. Bianchi +3 more
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AQI Prediction Based on CEEMDAN-ARMA-LSTM
Sustainability, 2022 In the context of carbon neutrality and air pollution prevention, it is of great research significance to achieve high-accuracy prediction of the air quality index. In this paper, Beijing is used as the study area; data from January 2014 to December 2019
Yong Sun, Jiwei Liu
semanticscholar +1 more source
Scientific Reports, 2021 In order to correct the monitoring data of the miniature air quality detector, an air quality prediction model fusing Principal Component Regression (PCR), Support Vector Regression (SVR) machine, and Autoregressive Moving Average (ARMA) model was ...
Bing Liu, Yueqiang Jin, Chaoyang Li
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Endoscopy International Open, 2021 Background and study aims Antireflux mucosectomy (ARMS) and antireflux mucosal ablation (ARMA) are new endoscopic procedures for patients with gastroesophageal reflux disease (GERD). We conducted a meta-analysis to systematically assess the feasibility,
E. Rodríguez de Santiago +11 more
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Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX
Energies, 2021 The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. The interest in solar radiation prediction is increasing nowadays so efficient prediction can greatly improve
I. Sansa, Zina Boussaada, N. Bellaaj
semanticscholar +1 more source
Minimum Message Length in Hybrid ARMA and LSTM Model Forecasting
Entropy, 2021 Modeling and analysis of time series are important in applications including economics, engineering, environmental science and social science. Selecting the best time series model with accurate parameters in forecasting is a challenging objective for ...
Zheng Fang +3 more
semanticscholar +1 more source
Clustered Hybrid Wind Power Prediction Model Based on ARMA, PSO-SVM, and Clustering Methods
IEEE Access, 2020 Wind power prediction is the key technology to the safe dispatch and stable operation of power system with large-scale integration of wind power. In this work, based on the historical data of wind power, wind speed and temperature, the autoregressive ...
Yurong Wang, Dongchuan Wang, Yi Tang
semanticscholar +1 more source
Forest@, 2022 Tree defoliation and mortality are triggered in Europe by extreme climatic events that are recurring since the beginning of XXI century. Data from the ICP Forests monitoring networks reveal a general worsening of tree conditions in the last ten years, as
Bussotti F +8 more
doaj +1 more source
Acta Periodica Duellatorum, 2013 The paper aims at reinterpreting the so called ‘Teutonic estoc’ (inventory number: MNK XIV-49) from the Czartoryski Princes Collection, Cracow, Poland.
Talaga Maciej
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Investigation of the performance and accuracy of multivariate timeseries models in predicting EC and TDS values of the rivers of Urmia Lake Basin [PDF]
Journal of Advances in Environmental Health Research, 2017 Considering the complexity of hydrological processes, it seems that multivariate methods may enhance the accuracy of time series models and the results obtained from them by taking more influential factors into account.
Mohammad Soleimani +2 more
doaj +1 more source