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Application of deep learning in single top quark production at LHC

By:

Muhammad Waqas (489)

Material type: Text

TextPublication details: Islamabad (unpublished) 2021Description: vii, 67 p. : ill., Col., ; 30 cm. +CDSubject(s):

Physics -- Large hadron collider -- Artificial neural network -- Multilayer perceptron -- Deep Learning -- Machine learning -- Artificial Intelligence -- TMVA -- LHC -- BDT -- MLP -- ML -- DBS -- FEAS

DDC classification:

530 WAQ

Dissertation note: Thesis (M.Phil)--Riphah International University, 2021

List(s) this item appears in: FEAS & DBS Thesis I-14 Campus

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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Thesis	Main Campus	530 WAQ (Browse shelf(Opens below))	1	NOT for LOAN		68387

Submitted in fulfillment of the requirements for the degree of Master of Philosophy in Physics to the Department of Basic Sciences, Faculty of Engineering and Applied Sciences.

Includes bibliographical references.

Thesis supervisor: Dr. Ijaz Ahmed

Thesis (M.Phil)--Riphah International University, 2021

English

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