论文标题
预测未来就像完成一幅画！
Predicting the Future is like Completing a Painting!
论文作者
论文摘要
本文是针对科学预测的更大研究框架的介绍性工作。这是科学与科学哲学之间的混合，因此我们可以谈论科学的实验哲学。作为第一个结果，我们引入了一种基于图像完成的新预测方法，命名为图像inpainting（FM2I）的预测方法。实际上，时间序列预测被转换为完全基于图像和信号的处理程序。将时间序列数据转换为相应的图像之后，数据预测的问题本质上成为图像填充问题的问题，即完成图像中丢失的数据。使用众所周知的M3竞争提出的大型数据集进行了广泛的实验评估。结果表明，FM2I代表了时间序列预测的有效且健壮的工具。它在准确性方面取得了突出的结果，并胜过最佳的M3预测方法。
This article is an introductory work towards a larger research framework relative to Scientific Prediction. It is a mixed between science and philosophy of science, therefore we can talk about Experimental Philosophy of Science. As a first result, we introduce a new forecasting method based on image completion, named Forecasting Method by Image Inpainting (FM2I). In fact, time series forecasting is transformed into fully images- and signal-based processing procedures. After transforming a time series data into its corresponding image, the problem of data forecasting becomes essentially a problem of image inpainting problem, i.e., completing missing data in the image. An extensive experimental evaluation is conducted using a large dataset proposed by the well-known M3-competition. Results show that FM2I represents an efficient and robust tool for time series forecasting. It has achieved prominent results in terms of accuracy and outperforms the best M3 forecasting methods.
