Quantum fuzzy genetic algorithm with Turing to solve DE

Q1 Engineering

Periodicals of Engineering and Natural Sciences Pub Date : 2023-02-07 DOI:10.21533/pen.v11i1.3417

A. Hamid, Elias Igor Klebanov, S. Albermany

引用次数: 0

Abstract

In this study, we create the quantum fuzzy Turing machine (QFTM) approach for solving fuzzy differential equations under Seikkala differentiability by combining it with a differential equation and a genetic algorithm. A theoretical model of computation called a quantum fuzzy Turing machine (QFTM) incorporates aspects of fuzzy logic and quantum physics

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用图灵的量子模糊遗传算法求解DE

在本研究中，我们将量子模糊图灵机（QFTM）方法与微分方程和遗传算法相结合，创建了求解Seikkala可微性下模糊微分方程的量子模糊图灵机方法。一种称为量子模糊图灵机（QFTM）的理论计算模型融合了模糊逻辑和量子物理学的各个方面

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Periodicals of Engineering and Natural Sciences Engineering-Architecture

CiteScore

1.90

自引率

0.00%

发文量

140

审稿时长

7 weeks

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