Problem: multi-horizon probabilistic forecasting tasks; Propose an end-to-end framework for multi-horizon time series forecasting, with temporal attention mechanisms to capture latent patterns. Introduction: forecasting ----- understanding demands. t…

Problem: high-dimensional time series forecasting ?? what is "high-dimensional" time series forecasting? one dimension for each individual time-series. n个time series为n维. A need for exploiting global pattern and coupling them with local calibrati…

Problem: time series forecasting Challenge: forecasting for non-stationary signals and multiple future steps prediction ?? how to deal with non-stationary datasets?? Introduction one-step prediction problem VS multi-step prediction; multi-step foreca…

An overview of time series forecasting models 2019-10-04 09:47:05 This blog is from: https://towardsdatascience.com/an-overview-of-time-series-forecasting-models-a2fa7a358fcb What is this article about? This article provides an overview of the main m…

1. Air Pollution Forecasting In this tutorial, we are going to use the Air Quality dataset. This is a dataset that reports on the weather and the level of pollution each hour for five years at the US embassy in Beijing, China. The data includes the d…

Problem define a fuzzy visibility graph (undirected weighted graph), then give a new similarity measure of time series. Problem: 1. some significant information of the time series, such as trend information is lost by using visibility graph. 2. the o…

最小二次方时序差分学习 原文地址: https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=9&cad=rja&uact=8&ved=2ahUKEwjD6qn5x8zhAhVSuZ4KHfJTCyUQFjAIegQIBBAC&url=https%3A%2F%2Fiu.instructure.com%2Ffiles%2F69696547%2Fdownload%3Fdow…

From: Yoshua Bengio Problem: time series forecasting. Supplementary knowledge: 1. what is meta-learning: https://www.zhihu.com/question/264595128 2. what is zero-shot learning: ZSL就是希望我们的模型能够对其从没见过的类别进行分类,让机器具有推理能力,实现真正的智能.其中零次(Zero-shot)是指对于要分类的类别对象…

Problem: time series prediction The nonlinear autoregressive exogenous model: The Nonlinear autoregressive exogenous (NARX) model, which predicts the current value of a time series based upon its previous values as well as the current and past values…

(1)I spent my 4th year Computing project on implementing time series forecasting for Java heap usage prediction using ARIMA, Holt Winters etc, so I might be in a good position to advise you on this. Your best option by far is using the R language, yo…