基于深度学习的人工智能设计决策模型

Translated title of the contribution: Artificial intelligence design decision making model based on deep learning

Yahui Wang, Suihuai Yu, Dengkai Chen, Jianjie Chu, Zhuo Liu, Jinlei Wang, Ning Ma

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

To eliminate the influence of decision-maker's decision preferences on product development and further improve the design decision-making efficiency, a Residual Neural Network(ResNet)artificial intelligence design decision-making model was proposed. Based on artificial intelligence thinking, a design history scheme dataset based on product modeling semantics was built. After the semantic annotation of this design dataset, ResNet algorithm was applied to train the data set continuously to improve the accuracy of design decisions, which could transfer the general design decision problem into the image semantic recognition problem of the design schemes, so as to maximize the influence of decision-maker's decision preferences. The validity of ResNet artificial intelligence design decision model was verified by the example of crane design decision making experiment, which proved the feasibility and rationality of the model.

Translated title of the contributionArtificial intelligence design decision making model based on deep learning
Original languageChinese (Traditional)
Pages (from-to)2467-2475
Number of pages9
JournalJisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS
Volume25
Issue number10
DOIs
StatePublished - 1 Oct 2019

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