An adaptive network based fuzzy inference system–auto regression–analysis of variance algorithm for improvement of oil consumption estimation and policy making: The cases of Canada, United Kingdom, and South Korea
- 28 February 2011
- journal article
- Published by Elsevier BV in Applied Mathematical Modelling
- Vol. 35 (2), 581-593
- https://doi.org/10.1016/j.apm.2010.06.001
Abstract
No abstract availableKeywords
This publication has 23 references indexed in Scilit:
- Forecasting stock market short-term trends using a neuro-fuzzy based methodologyExpert Systems with Applications, 2009
- A flexible fuzzy regression algorithm for forecasting oil consumption estimationEnergy Policy, 2009
- Neural networks and fuzzy inference systems for predicting water consumption time seriesStochastic Environmental Research and Risk Assessment, 2009
- An integrated GA-time series algorithm for forecasting oil production estimation: USA, Russia, India, and BrazilInternational Journal of Industrial and Systems Engineering, 2009
- Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, TurkeyJournal of Hydrology, 2008
- Discrete grey forecasting model and its optimizationApplied Mathematical Modelling, 2008
- A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoffJournal of Hydrology, 2007
- Chaotic time series prediction with a global model: Artificial neural networkJournal of Hydrology, 2005
- Artificial neural networks for non-stationary time seriesNeurocomputing, 2004
- A neuro-fuzzy computing technique for modeling hydrological time seriesJournal of Hydrology, 2004