Name
Abstract | ||
|---|---|---|
Nowadays, the success of a company is dependent to the novelty of the company in developing new items. Product design and engineering are a basic phase in developing new commodities which examines the product economically and technologically. In the proposed study, “Trust” is identified as an effective factor on the life cycle of the new designed product. This study addresses a simulation structure to generate all the possible trust modes between two agents over time and implements four prediction methods to forecast the trust value of the new item. The time horizon is considered to be short term and middle term, and 27 and 108 scenarios are designed, respectively, based on three categories involving high, medium and short trust. Here, three prediction techniques: conventional time series, artificial neural networks and adaptive neuro-fuzzy inference system, are recommended and compared. By comparing MAPEs of all prediction methods, the best technique is identified. |
Year | DOI | Venue |
|---|---|---|
2017 | https://doi.org/10.1007/s40815-017-0314-1 | International Journal of Fuzzy Systems |
Keywords | Field | DocType |
Product engineering,Trust prediction,Conventional time series analysis,Artificial neural networks,Adaptive neuro-fuzzy inference system | Time horizon,Middle term,Artificial intelligence,Adaptive neuro fuzzy inference system,Product design,Artificial neural network,Product engineering,Mathematical optimization,Industrial engineering,Fuzzy logic,Novelty,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
19 | 4 | 1562-2479 |
Citations | PageRank | References |
1 | 0.34 | 9 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Azadeh | 1 | 172 | 23.32 |
| Sh. Sadri | 2 | 1 | 0.34 |
| Morteza Saberi | 3 | 207 | 28.66 |
| Jin Hee Yoon | 4 | 77 | 10.77 |
| Elizabeth Chang | 5 | 102 | 14.51 |
| Omar Khadeer Hussain | 6 | 406 | 56.97 |
| N. Pourmohammad Zia | 7 | 1 | 0.34 |