Oil Price Prediction Using Ensemble Machine Learning

被引：0

作者：

Gabralla, Lubna A. ^{[1
]}

Jammazi, Rania

Abraham, Ajith ^{[2
,3
]}

机构：

[1] Sudan Univ Sci Technol, Fac Comp Sci & Informat Technol, Khartoum, Sudan

[2] Sousse Univ, Fac Management & Econ Sci Sousse, El Riadh, Tunisia

[3] MIR Labs Sci Network Innovat & Res Excellence, Auburn, WA USA

来源：

2013 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRICAL AND ELECTRONICS ENGINEERING (ICCEEE) | 2013年

关键词：

crude oil price prediction; hybrid models; influential features; ALGORITHM; NETWORKS; MARKET;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Crude oil price forecasting is a challenging task due to its complex nonlinear and chaotic behavior. During the last couple of decades, both academicians and practitioners devoted proactive knowledge to address this issue. A strand of them has focused on some key factors that may influence the crude oil price prediction accuracy. This paper extends this particular branch of recent works by considering a number of influential features as inputs to test the forecasting performance of daily WTI crude oil price covering the period 4th January 1999 through 10th October 2012. Empirical results indicate that the proposed methods are efficient and warrant further research in this field.

引用

页码：674 / 679

页数：6

共 50 条

[31] Oil and gold price prediction using optimized fuzzy inference system based extreme learning machine
Das, Sudeepa
Sahu, Tirath Prasad
Janghel, Rekh Ram
[J]. RESOURCES POLICY, 2022, 79
[32] Cryptocurrency Price Prediction Using Supervised Machine Learning Algorithms
Chaudhary, Divya
Saroj, Sushil Kumar
[J]. ADCAIJ-ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2023, 12 (01):
[33] Stock Closing Price Prediction using Machine Learning Techniques
Vijh, Mehar
Chandola, Deeksha
Tikkiwal, Vinay Anand
Kumar, Arun
[J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE, 2020, 167 : 599 - 606
[34] Price Prediction Using LSTM Based Machine Learning Models
Rahman, Md. Hafizur
Nahid, Sayeda Islam
Al Fahad, Ibna Huda
Nahid, Faysal Mahmud
Khan, Mohammad Monirujjaman
[J]. 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021, 2021, : 453 - 459
[35] House Price Prediction Using Machine Learning And Neural Networks
Varma, Ayush
Sarma, Abhijit
Doshi, Sagar
Nair, Rohini
[J]. PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), 2018, : 1936 - 1939
[36] Airbnb Price Prediction Using Machine Learning and Sentiment Analysis
Kalehbasti, Pouya Rezazadeh
Nikolenko, Liubov
Rezaei, Hoormazd
[J]. MACHINE LEARNING AND KNOWLEDGE EXTRACTION (CD-MAKE 2021), 2021, 12844 : 173 - 184
[37] Airbnb Rental Price Prediction Using Machine Learning Models
Lektorov, Alexander
Abdelfattah, Eman
Joshi, Shreehar
[J]. 2023 IEEE 13TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE, CCWC, 2023, : 339 - 344
[38] Crude oil price prediction using deep reinforcement learning
Liang, Xuedong
Luo, Peng
Li, Xiaoyan
Wang, Xia
Shu, Lingli
[J]. RESOURCES POLICY, 2023, 81
[39] A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting
Yu, Lean
Dai, Wei
Tang, Ling
[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2016, 47 : 110 - 121
[40] An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price Prediction
Shrivastav, Lokesh Kumar
Kumar, Ravinder
[J]. JOURNAL OF INFORMATION TECHNOLOGY RESEARCH, 2022, 15 (01)

← 1 2 3 4 5 →