Causality of geopolitical risk on food prices: Considering the Russo–Ukrainian conflict
Abstract As the Russo–Ukrainian conflict obstructs the vast wheat production of Ukraine, we
investigate the relationship over crises between geopolitical risk and prices of essential food …
investigate the relationship over crises between geopolitical risk and prices of essential food …
PM2. 5 concentration forecasting at surface monitoring sites using GRU neural network based on empirical mode decomposition
G Huang, X Li, B Zhang, J Ren - Science of the Total Environment, 2021 - Elsevier
The main component of haze is the particulate matter (PM) 2.5. How to explore the laws of
PM2. 5 concentration changes is the main content of air quality prediction. Combining the …
PM2. 5 concentration changes is the main content of air quality prediction. Combining the …
Analysis and forecasting of financial time series using CNN and LSTM-based deep learning models
S Mehtab, J Sen - Advances in Distributed Computing and Machine …, 2022 - Springer
Designing predictive models for forecasting future stock price has always been a very
popular area of research. On the one hand, the proponents of the famous efficient market …
popular area of research. On the one hand, the proponents of the famous efficient market …
Robust analysis of stock price time series using CNN and LSTM-based deep learning models
S Mehtab, J Sen, S Dasgupta - 2020 4th International …, 2020 - ieeexplore.ieee.org
Prediction of stock price and stock price movement patterns has always been a crucial task
for researchers. While the well-known efficient market hypothesis rules out any possibility of …
for researchers. While the well-known efficient market hypothesis rules out any possibility of …
Deep learning methods for multi-channel EEG-based emotion recognition
Currently, Fourier-based, wavelet-based, and Hilbert-based time–frequency techniques
have generated considerable interest in classification studies for emotion recognition in …
have generated considerable interest in classification studies for emotion recognition in …
The role of political risk, uncertainty, and crude oil in predicting stock markets: Evidence from the UAE economy
This study examines how the determinants of the political risk factor affect the forecasting
performance of the United Arab Emirates' stock market during the COVID-19 pandemic. The …
performance of the United Arab Emirates' stock market during the COVID-19 pandemic. The …
Self-adaptive particle swarm optimization-based echo state network for time series prediction
Echo state networks (ESNs), belonging to the family of recurrent neural networks (RNNs),
are suitable for addressing complex nonlinear tasks due to their rich dynamic characteristics …
are suitable for addressing complex nonlinear tasks due to their rich dynamic characteristics …
Machine learning in structural engineering
JP Amezquita-Sancheza… - Scientia …, 2020 - scientiairanica.sharif.edu
This article presents a review of selected articles about structural engineering applications of
machine learning (ML) in the past few years. It is divided into the following areas: structural …
machine learning (ML) in the past few years. It is divided into the following areas: structural …
[HTML][HTML] The impact of oil and global markets on Saudi stock market predictability: A machine learning approach
This study investigates the predictability power of oil prices and six international stock
markets namely, China, France, UK, Germany, Japan, and the USA, on the Saudi stock …
markets namely, China, France, UK, Germany, Japan, and the USA, on the Saudi stock …
Revisiting Islamic banking efficiency using multivariate adaptive regression splines
F Saâdaoui, M Khalfi - Annals of Operations Research, 2024 - Springer
Islamic banking is among rapidly-growing components in the world's financial system. Within
its institutions, continuous criteria of efficiency facilitate the evaluation of the impact of the …
its institutions, continuous criteria of efficiency facilitate the evaluation of the impact of the …