A Refined Approach for Forecasting Based on Neutrosophic Time Series
| Autor: | Victor Chang, Florentin Smarandache, Mai Mohamed, Mohamed Abdel-Basset |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
triangular neutrosophic number Physics and Astronomy (miscellaneous) Computer science Process (engineering) General Mathematics Intuitionistic fuzzy 02 engineering and technology Indeterminacy (literature) Fuzzy logic 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) Time series neutrosophic logical relationship groups Series (mathematics) Basis (linear algebra) business.industry lcsh:Mathematics lcsh:QA1-939 neutrosophic time series Chemistry (miscellaneous) Falsity neutrosophic logical relationship 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Symmetry, Vol 11, Iss 4, p 457 (2019) Symmetry; Volume 11; Issue 4; Pages: 457 |
| ISSN: | 2073-8994 |
| DOI: | 10.3390/sym11040457 |
| Popis: | This research introduces a neutrosophic forecasting approach based on neutrosophic time series (NTS). Historical data can be transformed into neutrosophic time series data to determine their truth, indeterminacy and falsity functions. The basis for the neutrosophication process is the score and accuracy functions of historical data. In addition, neutrosophic logical relationship groups (NLRGs) are determined and a deneutrosophication method for NTS is presented. The objective of this research is to suggest an idea of first-and high-order NTS. By comparing our approach with other approaches, we conclude that the suggested approach of forecasting gets better results compared to the other existing approaches of fuzzy, intuitionistic fuzzy, and neutrosophic time series. |
| Databáze: | OpenAIRE |
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