An Integrated Fuzzy Trust Prediction Approach in Product Design and Engineering

An Integrated Fuzzy Trust Prediction Approach in Product Design and Engineering 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Fuzzy Systems Springer Journals

An Integrated Fuzzy Trust Prediction Approach in Product Design and Engineering

Loading next page...
 
/lp/springer_journal/an-integrated-fuzzy-trust-prediction-approach-in-product-design-and-5zrCgFTKs7
Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Operations Research, Management Science
ISSN
1562-2479
eISSN
2199-3211
D.O.I.
10.1007/s40815-017-0314-1
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Fuzzy SystemsSpringer Journals

Published: May 11, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from Google Scholar, PubMed
Create lists to organize your research
Export lists, citations
Access to DeepDyve database
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off