Using Graph Complexity Connectivity Method to Predict Information from Design Representations: A Comparative Study

被引：1
|
作者：
Mohinder, C. V. Sri Ram [1 ]
Gill, Amaninder [1 ]
Summers, Joshua D. [1 ]
机构：
[1] Clemson Univ, Clemson, SC 29631 USA
来源：
DESIGN COMPUTING AND COGNITION '16 | 2017年
关键词：
ARTIFICIAL NEURAL-NETWORKS; ENGINEERING DESIGN; CENTRALITY; REGRESSION; SYSTEMS;
D O I：
10.1007/978-3-319-44989-0_36
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The objective of this research is to compare the value of information in a design representation used in product development. Two representations are explored in this study: assembly models and function structures. These representations are used to predict assembly time and market value for electromechanical products. This works builds on previous work on using complexity connectivity method to predict assembly time. The precision error is used as a metric to understand how valuable a representation is in answering a specific question. By measuring the value of a representation, designers can select between different representations and monitor the information accumulation in the design project.
引用
收藏
页码：667 / 683
页数：17
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