The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 25, 2016

Filed:

Dec. 05, 2013
Applicant:

Samsung Sdi Co., Ltd., Yongin-si, Gyeonggi-do, KR;

Inventors:

No-Kap Park, Yongin-si, KR;

Ho-Yul Baek, Yongin-si, KR;

Seung Bum Suh, Yongin-si, KR;

Jeong-Soon Shin, Yongin-si, KR;

Cheol-Ho Park, Yongin-si, KR;

Hee-Kwan Chai, Yongin-si, KR;

Young-Hwa Ko, Yongin-si, KR;

Kyeong-Beom Cheong, Yongin-si, KR;

Eun-Jung Lee, Yongin-si, KR;

Assignee:

Samsung SDI Co., Ltd., Gyeonggi-Do, KR;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01); G06N 99/00 (2010.01); G06K 9/62 (2006.01); G06N 5/02 (2006.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06N 99/005 (2013.01); G06K 9/6256 (2013.01); G06K 9/6269 (2013.01); G06N 5/025 (2013.01); G06N 7/005 (2013.01);
Abstract

A system for predicting the thickness of a battery is disclosed. In one aspect, the battery thickness predicting system includes a learning data input unit for receiving data on a previously manufactured battery. The thickness predicting system further includes an object data input unit for receiving data on a battery whose thickness is to be predicted. The system further comprises a mechanical learning unit connected to the learning data input unit to obtain a predicting function based on learning factors input to the learning data input unit and to provide weight values to the learning factors, respectively. The system further includes a thickness predicting unit connected to the object data input unit and the mechanical learning unit and using the weight values provided by the mechanical learning unit in order to predict the thickness of the battery whose thickness is to be predicted.


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