Using ML to Model and Optimize Chip Geometry for Improved Lithography – Junaid AHMAD
Junaid AHMAD
Master's thesis
Using ML to Model and Optimize Chip Geometry for Improved Lithography
Abstract:
This thesis delves into the creation and application of a predictive model aimed at optimizing chip production on a wafer, while maintaining the on-resistance (Ron) of a MOSFET within acceptable limits. Through a systematic approach, various regression models were developed, including linear regression, Random Forest, XGBoost, and a Deep Neural Network (DNN), to predict chip quantities considering …moreAbstract:
This thesis delves into the creation and application of a predictive model aimed at optimizing chip production on a wafer, while maintaining the on-resistance (Ron) of a MOSFET within acceptable limits. Through a systematic approach, various regression models were developed, including linear regression, Random Forest, XGBoost, and a Deep Neural Network (DNN), to predict chip quantities considering …more
Language used: Czech
Date on which the thesis was submitted / produced: 31. 8. 2023
Thesis defence
- Supervisor: prof. Dr. Cezar Ionescu
Citation record
ISO 690-compliant citation record:
AHMAD, Junaid. \textit{Using ML to Model and Optimize Chip Geometry for Improved Lithography}. Online. Master's thesis. České Budějovice: University of South Bohemia in České Budějovice, Faculty of Science. 2023. Available from: https://theses.cz/id/ou03k0/.
The right form of listing the thesis as a source quoted
AHMAD, Junaid. Using ML to Model and Optimize Chip Geometry for Improved Lithography. České Budějovice, 2023. diplomová práce (Mgr.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH, Přírodovědecká fakultaUNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE
Faculty of ScienceMaster programme / field:
Artificial Intelligence and Data Science / Artificial Intelligence and Data Science
Theses on a related topic
-
Evolutionary Synthesis of the Turing Machine´s Rules
Lukáš KOUŘIL -
Simulation-based Evaluation of Test Power in Regression Analysis
Nicol Tinková -
Regression analysis of the relationship between COVID-19 pandemic and the change in unemployment in EU27 countries
Vahid Mammadzada -
Logistic regression in R
Alicem Karaca -
Regression analysis on tests results for diabetes diagnosis using R
Gayrat Dadamirzaev -
Predictive regression analysis of housing price in Iowa
Zhida Guo -
Regression analysis of the relationship between economic growth and foreign aid in Africa
Jean Gabin Ngango -
Credit score model via GAS model and logistic regression
Nela Hendrichová
Name
Posted by
Uploaded/Created
Rights