Mr. Yunpeng Cong Profile

Yunpeng Cong

at CATARC Automotive Test Ctr. Co., Ltd.

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 11 November 2022 Paper

Research and validation of intelligent control strategy for car seat comfort

Changjiang Du, Yunpeng Cong, Yu Qiao

Proceedings Volume 12301, 1230128 (2022) https://doi.org/10.1117/12.2644599

KEYWORDS: Data modeling, Mathematical modeling, Evolutionary algorithms, Data acquisition, Algorithm development, Performance modeling, Neural networks, Foam, Error analysis, Strategic intelligence

Read Abstract +

Based on Chinese human body characteristics and seat comfort evaluation model, this paper investigates the intelligent regulation model and validation method of car seat comfort applicable to Chinese human body. Consumers input the basic human characteristics parameters (height, weight, gender, age), and the seat position information (slide position, high adjustment position, angle position) can be calculated by using the regulation algorithm, so that the system can control the adjustment state of the seat. In the model building stage, the BP neural network algorithm, Gaussian regression algorithm and SVM prediction algorithm are studied in this paper, and the comparative analysis reveals that the prediction error and the stability of the prediction results can be optimized by using SVM algorithm for the prediction of the three position parameters, which can achieve the optimal prediction effect. In order to verify and optimize the model, a universal body platform is developed in this paper, which combines software and hardware together to verify the effectiveness of the regulation algorithm, and also feeds back and records the micro-secondary regulation data of consumers for subsequent optimization of the model.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years