Exploring Quantum Machine Learning (QML) for Earthquake Prediction

Saloni Dhotre, Karan Doshi, Sneha Satish, Kalpita Wagaskar
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引用次数: 4

Abstract

Quantum computing functions on qubits, different from the classical bits. These qubits follow the properties of quantum physics such as superposition, interference and entanglement. Our aim is to use this quantum technology in the prediction of earthquakes, a natural disaster resulting in a large number of deaths and destruction every year. Earthquakes are one of the most catastrophic natural hazards, and they frequently turn into disasters that cause utter devastation and loss of life. We first implement the prediction on a classical machine learning algorithm and then compare the results with quantum machine learning. Since the processing power of quantum computers is significantly higher than classical computers, it is expected to predict earthquakes accurately and give an early warning to alert the locals residing in that area.
探索量子机器学习(QML)用于地震预测
量子计算在量子比特上起作用,不同于经典比特。这些量子比特遵循量子物理的特性,如叠加、干涉和纠缠。我们的目标是利用这种量子技术来预测地震,这是一种每年造成大量死亡和破坏的自然灾害。地震是最具灾难性的自然灾害之一,它们经常演变成造成彻底破坏和生命损失的灾难。我们首先在经典机器学习算法上实现预测,然后将结果与量子机器学习进行比较。由于量子计算机的处理能力明显高于传统计算机,因此有望准确预测地震,并向居住在该地区的当地人发出预警。
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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