Model Fourier Untuk Prediksi Harga Saham Astrazeneca Menggunakan Algoritma Levenberg-Marquardt

Hafizh Al Kautsar
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Abstract

The soaring cases of covid-19 prompted some countries to find solutions to save their people. One of the steps that is currently being taken is with vaccines. Several leading companies in the world that produce drugs are known to have produced vaccines for covid-19, one of which is AstraZeneca. AstraZeneca vaccine is known as the most widely used vaccine in all countries in the world. Interesting thing to research is how the development of the company's stock engaged in the medical field, especially companies that produce vaccines for covid-19. This study used Fourier's approach to modeling its curve fittings. As for the prediction process using levenberg-marquardt algorithm which is known to be reliable to perform the prediction process. Levenberg-Marquardt's algorithm has the advantage of a fast training process and reliable accuracy due to its work that combines Gauss-Newton and Steepest Descent. The result is root mean square error value from the test result that was lower than the Root Mean Square Error value in the training process. This indicates that the prediction went well.
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covid-19病例飙升促使一些国家寻找拯救本国人民的解决方案。目前正在采取的步骤之一是疫苗。据悉,包括阿斯利康(AstraZeneca)在内,世界上几家领先的制药公司都生产了针对新冠病毒的疫苗。阿斯利康疫苗是世界各国使用最广泛的疫苗。值得研究的是,该公司股票的发展如何涉足医疗领域,特别是生产新冠病毒疫苗的公司。本研究使用傅立叶方法对其曲线拟合进行建模。对于预测过程,采用已知可靠的levenberg-marquardt算法进行预测。Levenberg-Marquardt算法结合了高斯-牛顿法和最陡下降法,具有训练过程快、精度可靠的优点。结果为测试结果的均方根误差值,低于训练过程中的均方根误差值。这表明预测进行得很顺利。
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