基于 python- 的模糊逻辑算法的 NTMC 警察交通犯罪评估系统

Dimas Raihan, Naufal, Muhamad Malik Mutoffar
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引用次数: 0

摘要

本研究旨在利用基于 Python 语言的模糊逻辑算法建立一个交通违规系统。利用输入组件接收交通违规数据,利用输出组件生成交通理解水平值。该方法用于处理基于交通违规的数据,系统测试结果显示了系统的准确性。确认系统在交通违章方面的能力,为准确理解警察法的水平提供了一个基准评估。该系统的意义表明,它有可能成为一种有效的检测工具,从个人理解的不同层面来衡量现有的违法行为,尤其是在法律领域。考虑到这项研究,可为在未来各种理解能力评估环境中开发类似系统奠定坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SISTEM EVALUASI PELANGGARAN LALU LINTAS NTMC POLRI DENGAN ALGORITMA FUZZY LOGIC BERBASIS PYTHON
This research aims to build a traffic violation system using a fuzzy logic algorithm based on the Python language. By utilizing input components to receive traffic violation data and output components to produce traffic understanding level values. This method is used to process data based on traffic violations, system test results show the system's accuracy. To confirm the system's capabilities in traffic violations provides a baseline assessment of the level of accurate understanding of police law. The implications of this system show its potential as an effective detection tool for measuring existing legal violations from various levels of a person's understanding, especially in the legal field. Taking this research into account could provide a strong foundation for the development of similar systems in a variety of future comprehension evaluation contexts
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