Open AccessSingle‐valued neutrosophic relations and their application to factors affecting oil prices
Author(s) -
Chaw Yenling,
Abdullah Lazim,
Othman Mahmod
Publication year - 2020
Publication title -
caai transactions on intelligence technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.613
H-Index - 15
ISSN - 2468-2322
DOI - 10.1049/trit.2020.0004
Subject(s) - boom , oil price , affect (linguistics) , oil boom , econometrics , factor (programming language) , economics , algebraic number , computation , computer science , mathematics , engineering , macroeconomics , monetary economics , algorithm , mathematical analysis , linguistics , philosophy , environmental engineering , programming language
The recent boom of economic activities has escalated the demand for oil that eventually will affect its prices. However, oil prices are difficult to predict because most of the factors affecting oil prices are vague and intangible. The challenges in predicting oil prices urgently require a novel approach where issues related to multiple‐factors, uncertainty, and periodicity can be addressed. The authors propose the single‐valued neutrosophic relations based decision‐making method inspired by the three memberships of neutrosophic sets, and amplitude and periodicity of complex numbers. The proposed method is applied to the case of oil prices where six factors affecting oil prices and six benchmarks measuring oil prices are employed. This new method combines with complex neutrosophic numbers and algebraic relations, and can suggest the most influential factor that affects oil prices. Considering the periodicity of 24 months, computation results verify the ‘global economic rate’ as the most influential factor that affects the prices of oil. The main contribution of this study is the development of a neutrosophic relations‐based decision‐making method to suggest the most influential factor that affects oil prices. The result provides evidence on the feasibility of the proposed method in suggesting the influential factors that affect oil prices.