Data Classification with Qubit Superposition Approach in Quantum Perceptron

Amirullah, Desi; Gultom, Lipantri Mashur

doi:10.1109/icae47758.2019.9221662

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“…An information file with many types must be organized efficiently and effectively to make ready-to-use details available. There are several algorithms in guided research, one of which is an artificial neural network [1].…”

Section: Introductionmentioning

confidence: 99%

Development of Quantum Circuit Architecture on Quantum Perceptron Algorithm for Classification of Marketing Bank Data

Wahyudi

Solikhun

2023

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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The creation of quantum circuit architecture based on the quantum perceptron algorithm to classify marketing bank data is proposed in this work. A quantum circuit is a quantum gate made up of two quantum gates. Quantum bits are used in this study's computation. The primary proposed learning method was not ideal, which is the context of this study. The percentage of qubits measurement value is still 90.7 percent. It is essential to raise the value of the qubit rate. Using the IBM Quantum Experience quantum computer, researchers measured, trained, and tested the quantum circuit architecture. Bank marketing data from the UCI Machine Learning Repository was used. A quantum circuit architecture model results from this research the quantum circuit measurement results.

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Section: Introductionmentioning

confidence: 99%