Can I read An Online Updating Method for Time-varying Preference Learning on EtoBox?

An Online Updating Method for Time-varying Preference Learning by Zhu, Xi; Feng, Jingshuo; Huang, Shuai; Chen, Cynthia is a Engineering article available to read on EtoBox.

What is An Online Updating Method for Time-varying Preference Learning about?

The rapid proliferation of smart, personal technologies has given birth to smart Transportation Demand Management (TDM) systems that can give personalized incentives to users. This personalization capacity builds on accurate modeling of user behaviors; however, in practice, a user's behavior data is often limited, and his preferences in the discrete choice-making process may change or evolve. In this paper, we propose a new online-updating model that can accurately and efficiently estimate an individual's preferences from his discrete choices. Our model is built on the concept of canonical structure, where a set of canonical models are identified as the common preference patterns shared by the whole population, and a membership vector is also identified for each individual to capture the degrees of the resemblance of his preferences to those common preference patterns. To allow preference to vary in the choice-making process, a time-varying model can be integrated with the canonical structure. In the current study, we use a simple cubic polynomial model with a single variant and show the detailed formulation of the integrated model. An online-updating strategy is also proposed, suc

Who reads An Online Updating Method for Time-varying Preference Learning?

Author

Zhu, Xi; Feng, Jingshuo; Huang, Shuai; Chen, Cynthia

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0968-090X)

Published

2020

Language

EN

Field

Engineering (Physical Sciences)