Forecasting Model

Time series forecasting models aim to predict future values based on historical data, a crucial task across diverse fields from finance and energy to healthcare and environmental science. Current research emphasizes improving accuracy and robustness through advanced architectures like transformers, recurrent neural networks (RNNs, including LSTMs), and hybrid models combining machine learning with statistical methods, often incorporating external data sources like news or market indicators to enhance predictive power. These advancements are significant because accurate forecasting enables better resource allocation, risk management, and informed decision-making in various sectors, ultimately leading to improved efficiency and outcomes.

Papers

January 31, 2023

Time Series Forecasting via Semi-Asymmetric Convolutional Architecture with Global Atrous Sliding Window
Yuanpeng He
Time Series Time Series Forecasting Forecasting Model Time Series Datasets Sliding Window Fuzzy Time Series

January 13, 2023

Composite model of seismic monitoring data analysis during mining operations on the example of the Kukisvumchorrskoye deposit of JSC Apatit
Ilia Revin
Mining Complex Forecasting Model Earthquake Monitoring Model Combination

August 24, 2022

Identifying and Overcoming Transformation Bias in Forecasting Models
Sushant More
Forecasting Model Bias Correction Space Bias Tweedie Distribution

June 25, 2022

Multi-Variate Time Series Forecasting on Variable Subsets
Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran
Scientific Inference Time Series Forecasting Multivariate Time Series Forecasting Forecasting Model Inference Task High Quality Subset

June 17, 2022

Random Forest of Epidemiological Models for Influenza Forecasting
Majd Al Aawar, Ajitesh Srivastava
Random Forest Forecasting Model Influenza Virus Tree Ensemble Model Influenza Forecasting

May 20, 2022

Trend analysis and forecasting air pollution in Rwanda
Paterne Gahungu, Jean Remy Kubwimana
Machine Learning Forecasting Model Air Pollution Trend Analysis

May 5, 2022

KnitCity: a machine learning-based, game-theoretical framework for prediction assessment and seismic risk policy design
Adèle Douin, J. P. Bruneton, Frédéric Lechenault
New Machine Game Theoretic Forecasting Model Earthquake Engineering Seismic Wave

April 1, 2022

A Global Modeling Approach for Load Forecasting in Distribution Networks
Miha Grabner, Yi Wang, Qingsong Wen, Boštjan Blažič, Vitomir Štruc
Load Forecasting Global Model Forecasting Model Smart Meter Distribution System Efficient Time Series Forecasting

March 14, 2022

A Comparative Study on Forecasting of Retail Sales
Md Rashidul Hasan, Muntasir A Kabir, Rezoan A Shuvro, Pankaz Das
Comparative Study Time Series Forecasting E Commerce State of the Art Forecasting Forecasting Model Integrated Moving Average Retail Store

February 17, 2022

Multi-Objective Model Selection for Time Series Forecasting
Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann
Time Series Forecasting Multi Objective Forecasting Model Univariate Time Series Forecasting Forecasting Method

February 3, 2022

Review of automated time series forecasting pipelines
Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, Martin Rätz, Dirk Müller, Veit Hagenmeyer, Ralf Mikut
Time Series Narrative Review Time Series Forecasting Forecasting Model Forecasting Method Energy Pipeline Forecasting Pipeline

December 22, 2021

Dynamic Combination of Heterogeneous Models for Hierarchical Time Series
Xing Han, Jing Hu, Joydeep Ghosh
Forecasting Model Heterogeneous Model Item Combination Hierarchical Time Series Quantile Forecast Forecasting Pipeline