An Intelligent Modeling of Oil Consumption-Reference-Cited by-同舟云学术

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An Intelligent Modeling of Oil Consumption

Published:2015 Issue: Volume: Page:557-568
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Chiroma Haruna,Abdulkareem Sameem,Muaz Sanah Abdullahi,Abubakar Adamu I.,Sutoyo Edi,Mungad Mungad,Saadi Younes,Sari Eka Novita,Herawan Tutut

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-11218-3_50

Reference19 articles.

1. Energy Information Administration of the US Department of Energy (2013), http://www.eia.gov/

2. Assareh, E., Behrang, M.A., Assari, M.R., Ghanbarzadeh, A.: Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran. Energy 35(12), 5223–5229 (2010)

3. Toksarı, M.D.: Ant colony optimization approach to estimate energy demand of Turkey. Energy Policy 35(8), 3984–3990 (2007)

4. Chiroma, H., Abdulkareem, S., Abubakar, A., Zeki, A., Gital, A.Y., Usman, M.J.: Co – Active Neuro-Fuzzy Inference Systems Model for Predicting Crude Oil Price based on OECD Inventories. In: 3rd International Conference on Research and Innovation in Information Systems (ICRIIS 2013), Malaysia, pp. 232–235. IEEE (2013)

5. Lecture Notes in Computer Science;H. Chiroma,2014

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2. Prediction of Malaysian–Indonesian Oil Production and Consumption Using Fuzzy Time Series Model;Advances in Data Science and Adaptive Analysis;2017-01

3. Forecasting of Malaysian Oil Production and Oil Consumption Using Fuzzy Time Series;Advances in Intelligent Systems and Computing;2016-12-29

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