用图灵的量子模糊遗传算法求解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

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引用次数: 0

摘要

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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Quantum fuzzy genetic algorithm with Turing to solve DE

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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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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