Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series
MHDM Ribeiro, L dos Santos Coelho - Applied soft computing, 2020 - Elsevier
The investigation of the accuracy of methods employed to forecast agricultural commodities
prices is an important area of study. In this context, the development of effective models is …
prices is an important area of study. In this context, the development of effective models is …
A review on recent advancements in forex currency prediction
In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny
from researchers all over the world. Due to its vulnerable characteristics, different types of …
from researchers all over the world. Due to its vulnerable characteristics, different types of …
Decision-making for financial trading: A fusion approach of machine learning and portfolio selection
FD Paiva, RTN Cardoso, GP Hanaoka… - Expert Systems with …, 2019 - Elsevier
Forecasting stock returns is an exacting prospect in the context of financial time series. This
study proposes a unique decision-making model for day trading investments on the stock …
study proposes a unique decision-making model for day trading investments on the stock …
A hybrid deep learning approach by integrating LSTM-ANN networks with GARCH model for copper price volatility prediction
Y Hu, J Ni, L Wen - Physica A: Statistical Mechanics and its Applications, 2020 - Elsevier
Forecasting the copper price volatility is an important yet challenging task. Given the
nonlinear and time-varying characteristics of numerous factors affecting the copper price, we …
nonlinear and time-varying characteristics of numerous factors affecting the copper price, we …
[HTML][HTML] Foreign exchange currency rate prediction using a GRU-LSTM hybrid network
The foreign exchange (FOREX) market is one of the biggest financial markets in the world.
More than 5.1 trillion dollars are traded each day in the FOREX market by banks, retail …
More than 5.1 trillion dollars are traded each day in the FOREX market by banks, retail …
Global stock market investment strategies based on financial network indicators using machine learning techniques
This study presents financial network indicators that can be applied to global stock market
investment strategies. We propose to design both undirected and directed volatility networks …
investment strategies. We propose to design both undirected and directed volatility networks …
Evaluating the performance of machine learning algorithms in financial market forecasting: A comprehensive survey
With increasing competition and pace in the financial markets, robust forecasting methods
are becoming more and more valuable to investors. While machine learning algorithms offer …
are becoming more and more valuable to investors. While machine learning algorithms offer …
Deep Neural Network Based Ensemble learning Algorithms for the healthcare system (diagnosis of chronic diseases)
J Abdollahi, B Nouri-Moghaddam… - arXiv preprint arXiv …, 2021 - arxiv.org
learning algorithms. In this paper, we review the classification algorithms used in the health
care system (chronic diseases) and present the neural network-based Ensemble learning …
care system (chronic diseases) and present the neural network-based Ensemble learning …
Prediction of NOx emissions for coal-fired power plants with stacked-generalization ensemble method
Z Yuan, L Meng, X Gu, Y Bai, H Cui, C Jiang - Fuel, 2021 - Elsevier
Measuring the nitrogen oxides (NOx) concentration accurately at the inlet of the denitration
reactor plays an important role in controlling the NOx emissions for coal-fired power plants …
reactor plays an important role in controlling the NOx emissions for coal-fired power plants …
[HTML][HTML] A framework combined stacking ensemble algorithm to classify crop in complex agricultural landscape of high altitude regions with Gaofen-6 imagery and …
Z Ma, W Li, TA Warner, C He, X Wang, Y Zhang… - International Journal of …, 2023 - Elsevier
Mapping crop distribution using satellite technology is an effective approach for gaining
information about food production over broad, regional scales. However, crop classification …
information about food production over broad, regional scales. However, crop classification …