A Review on Artificial Intelligence Methodologies for the Forecasting of Crude Oil Price
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Review on Artificial Intelligence Methodologies for the Forecasting of Crude Oil Price
Authors
Keywords
-
Journal
INTELLIGENT AUTOMATION AND SOFT COMPUTING
Volume 22, Issue 3, Pages 449-462
Publisher
TSI Press
Online
2016-01-11
DOI
10.1080/10798587.2015.1092338
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An Application of SVM-Based Classification in Landslide Stability
- (2015) Tingyao Jiang et al. INTELLIGENT AUTOMATION AND SOFT COMPUTING
- Stock Market Prediction Using a Combination of Stepwise Regression Analysis, Differential Evolution-based Fuzzy Clustering, and a Fuzzy Inference Neural Network
- (2013) David Enke et al. INTELLIGENT AUTOMATION AND SOFT COMPUTING
- Modified Radial Basis Function Neural Network Integrated with Multiple Regression Analysis and its Application in the Chemical Industry Processes
- (2013) Yang Wang et al. INTELLIGENT AUTOMATION AND SOFT COMPUTING
- Crude oil price analysis and forecasting using wavelet decomposed ensemble model
- (2012) Kaijian He et al. ENERGY
- Forecasting Crude Oil Price and Stock Price by Jump Stochastic Time Effective Neural Network Model
- (2012) Jun Wang et al. Journal of Applied Mathematics
- Three new fuzzy neural networks learning algorithms based on clustering, training error and genetic algorithm
- (2011) Hamed Malek et al. APPLIED INTELLIGENCE
- A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting
- (2011) Ali Azadeh et al. COMPUTERS & INDUSTRIAL ENGINEERING
- Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network
- (2011) Kamyar Movagharnejad et al. ENERGY
- A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems
- (2010) Arash Bahrammirzaee NEURAL COMPUTING & APPLICATIONS
- Hybrid credit ranking intelligent system using expert system and artificial neural networks
- (2009) Arash Bahrammirzaee et al. APPLIED INTELLIGENCE
- A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns
- (2009) Xiang Li et al. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- Hybrid learning machines
- (2009) Ajith Abraham et al. NEUROCOMPUTING
- Estimating VaR in crude oil market: A novel multi-scale non-linear ensemble approach incorporating wavelet analysis and neural network
- (2009) Kaijian He et al. NEUROCOMPUTING
- Hybrid and ensemble-based soft computing techniques in bankruptcy prediction: a survey
- (2009) Antanas Verikas et al. SOFT COMPUTING
- Daily prediction of short-term trends of crude oil prices using neural networks exploiting multimarket dynamics
- (2009) Heping Pan et al. Frontiers of Computer Science in China
- Reliability analysis of structures using artificial neural network based genetic algorithms
- (2008) Jin Cheng et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- Piles shaft capacity from CPT and CPTu data by polynomial neural networks and genetic algorithms
- (2008) H. Ardalan et al. COMPUTERS AND GEOTECHNICS
- Evaluating the process of a genetic algorithm to improve the back-propagation network: A Monte Carlo study
- (2008) Chien-Yu Huang et al. EXPERT SYSTEMS WITH APPLICATIONS
- Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks
- (2007) R.E. Abdel-Aal COMPUTERS & INDUSTRIAL ENGINEERING
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started