Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM

Carbon Price Forecasting Based on Improved CEEMDAN and Extreme Learning Machine Optimized by Sparrow Search Algorithm

(2021) Jianguo Zhou et al.   Sustainability

A decomposition-ensemble model with regrouping method and attention-based gated recurrent unit network for energy price prediction

(2021) Hongli Niu et al.   ENERGY

Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm

(2021) Pei Du et al.   RESOURCES POLICY

Using SARIMA–CNN–LSTM approach to forecast daily tourism demand

(2021) Kaijian He et al.   Journal of Hospitality and Tourism Management

Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts

(2020) Mumtaz Ali et al.   JOURNAL OF HYDROLOGY

A CNN–LSTM model for gold price time-series forecasting

(2020) Ioannis E. Livieris et al.   NEURAL COMPUTING & APPLICATIONS

A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network

(2020) Hongli Niu et al.   APPLIED INTELLIGENCE

A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting

(2020) Pei Du et al.   APPLIED SOFT COMPUTING

CNNpred: CNN-based stock market prediction using a diverse set of variables

(2019) Ehsan Hoseinzade et al.   EXPERT SYSTEMS WITH APPLICATIONS

Stock price forecasting model based on modified convolution neural network and financial time series analysis

(2019) Jiasheng Cao et al.   INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS

A novel hybrid model on the prediction of time series and its application for the gold price analysis and forecasting

(2019) Jianwei E et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

A novel framework for daily forecasting of ozone mass concentrations based on cycle reservoir with regular jumps neural networks

(2019) Yuqin Mo et al.   ATMOSPHERIC ENVIRONMENT

Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach

(2018) Omer Berat Sezer et al.   APPLIED SOFT COMPUTING

A least squares-based parallel hybridization of statistical and intelligent models for time series forecasting

(2018) Zahra Haji Rahimi et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Deep belief network based k-means cluster approach for short-term wind power forecasting

(2018) Kejun Wang et al.   ENERGY

Improving forecasting accuracy of daily enterprise electricity consumption using a random forest based on ensemble empirical mode decomposition

(2018) Chuan Li et al.   ENERGY

Volatility of main metals forecasted by a hybrid ANN-GARCH model with regressors

(2017) Werner Kristjanpoller R et al.   EXPERT SYSTEMS WITH APPLICATIONS

Multi-Scale Volatility Feature Analysis and Prediction of Gold Price

(2017) Fenghua Wen et al.   INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING

Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method

(2016) Shouxiang Wang et al.   RENEWABLE ENERGY

Gold price volatility: A forecasting approach using the Artificial Neural Network–GARCH model

(2015) Werner Kristjanpoller et al.   EXPERT SYSTEMS WITH APPLICATIONS

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Improved complete ensemble EMD: A suitable tool for biomedical signal processing

(2014) Marcelo A. Colominas et al.   Biomedical Signal Processing and Control

A real time clustering and SVM based price-volatility prediction for optimal trading strategy

(2013) Subhabrata Choudhury et al.   NEUROCOMPUTING

The Model Confidence Set

(2011)   ECONOMETRICA

A dynamic meta-learning rate-based model for gold market forecasting

(2011) Shifei Zhou et al.   EXPERT SYSTEMS WITH APPLICATIONS

Exchange rate forecasting using a combined parametric and nonparametric self-organising modelling approach

(2009) Leonidas Anastasakis et al.   EXPERT SYSTEMS WITH APPLICATIONS

Evolutionary artificial neural networks for hydrological systems forecasting

(2009) Yung-hsiang Chen et al.   JOURNAL OF HYDROLOGY