LogiThis study presents a novel forecasting framework that integrates Genetic Algorithms (GA) with Long Short-Term Memory (LSTM) networks to enhance the prediction accuracy of passenger volumes in Thailand's public transportation systems.
Khumla Pornsiri, Sarawan Kamthorn
doaj +1 more source
Applied Informatics, 2021 Cryptocurrency is a new sort of asset that has emerged as a result of the advancement of financial technology and it has created a big opportunity for researches. Cryptocurrency price forecasting is difficult due to price volatility and dynamism.
Mohammad J. Hamayel, A. Y. Owda
semanticscholar +1 more source
Comparison of multiple linear regression (MLR), support vector machine (SVM), Gaussian process regression (GPR) and artificial neural network (ANN) models in predicting total gastrointestinal quality of life index (GIQLI) score, physical component summary (PCS) score and mental component summary (MCS) score. [PDF]
, 2012 MSE = mean square error, MAPE = mean absolute percentage error.
King-Teh Lee (105939) +6 more
core +1 more source
A new hybrid model SARIMA-ETS-SVR for seasonal influenza incidence prediction in mainland China
Journal of Infection in Developing Countries, 2023 Introduction: Seasonal influenza is a serious public health issue in China. This study aimed to develop a new hybrid model for seasonal influenza incidence prediction and provide reference information for early warning management before outbreaks ...
Daren Zhao, Ruihua Zhang
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Summary statistics for the fall risk models using data from the Markov chains. [PDF]
, 2023 R2 gives the adjusted R2 value for the fitted model (Eq 12). The root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), relative average absolute error (RAAE), and maximum absolute error (Max Abs Err) are over ...
Anne E. Martin (10838318) +1 more
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DiagnosticsBackground: Myocardial perfusion scintigraphy (MPS) is an important tool for evaluating ischemia in diabetic populations. However, applications of advanced predictive models like multivariate adaptive regression splines (MARS) to estimate summed stress ...
Chien-Han Yuan +5 more
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ToxicsSurface air pollution affects ecosystems and people’s health. However, traditional models have low prediction accuracy. Therefore, a hybrid model for accurately predicting daily surface PM2.5 concentrations was integrated with wavelet (W), convolutional ...
Zhenfang He +3 more
semanticscholar +1 more source
Sistem Produksi Dan Analisis Peramalan Penjualan Produk Gula Dengan Menggunakan Metode Time Series Pada PT. Pabrik Gula Candi Baru [PDF]
, 2023 Hasil peramalan dengan menggunakan dua metode lainnya yakni metode Weighted Moving Average dan Single Exponential Smoothing tidak dipilih karena hasil dari uji kesalahan atau forecast error yang masih besar.
Gusti, Mohamad Lukman Hakim
core
Transforming oil market analysis: A novel GAN + LSTM predictive framework
Next EnergyA novel method of predicting the crude oil WTI futures prices based on a data set covering April 12, 2009 through January 7, 2024. To capture complex market dynamics more precisely, it incorporates key market factors such as open, high, and low price ...
Prity Kumari +2 more
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Forecasting PM2.5 in Malaysia Using a Hybrid Model
Aerosol and Air Quality Research, 2023 Predicting future PM2.5 concentrations based on knowledge obtained from past observational data is very useful for predicting air pollution. This paper aims to develop a hybrid forecasting model using an Artificial Neural Network (ANN) and Triple ...
Ezahtulsyahreen Ab. Rahman +3 more
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