Neural Network Residuals Kriging Surrogate and Sobol Method-Based Geometric Sensitivity Analysis for Wire Bonding in T/R Module-Reference-Cited by-同舟云学术

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Neural Network Residuals Kriging Surrogate and Sobol Method-Based Geometric Sensitivity Analysis for Wire Bonding in T/R Module

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:2021 CIE International Conference on Radar (Radar)
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Author:

Liu Shaoyi¹,Zhou Yijiang¹,Xue Song¹,Wang Wenjuan¹,Wang Congsi¹,Wang Zhihai²,Yu Kunpeng²,Liu Jing³

Affiliation:

1. Ministry of Education, Xidian University,Key Laboratory of Electronic Equipment Structure Design,Xi'an,China

2. China Electronics Technology Group Corporation No.38 Research Institute,Hefei,China

3. Xi'an Institute of Space Radio Technology,Xi'an,China

Funder

National Natural Science Foundation of China

National Key Basic Research and Development Program

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10027857/10027626/10028286.pdf?arnumber=10028286

Reference7 articles.

1. A Comparative Review of Sensitivity and Uncertainty Analysis of Large-Scale Systems—II: Statistical Methods

2. An Artificial Neural Network Residual Kriging Based Surrogate Model for Shape and Size Optimization of a Stiffened Panel

3. Model-Driven Design of Microwave Filters Based on Scalable Circuit Models

4. A Comparative Review of Sensitivity and Uncertainty Analysis of Large-Scale Systems—I: Deterministic Methods

5. A statistical approach to some basic mine valuation problems on the Witwatersrand;krige;J South African Inst Mining Metallurgy,1951

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