Forecasting Strategy

Forecasting strategies aim to accurately predict future values in time series data, crucial for diverse applications like supply chain management and healthcare. Current research emphasizes improving forecast accuracy by addressing data quality issues (e.g., missing values) through innovative techniques like image inpainting and by developing hybrid deep learning models—combining CNNs, LSTMs, and GRUs—to capture complex temporal and spatial patterns. These advancements enhance predictive performance and interpretability, leading to more reliable forecasts and improved decision-making across various sectors. The development of dynamic strategies that adapt to the specific characteristics of different time series is also a significant area of focus.

Papers

June 8, 2024

Hinge-FM2I: An Approach using Image Inpainting for Interpolating Missing Data in Univariate Time Series
Noufel Saad, Maaroufi Nadir, Najib Mehdi, Bakhouya Mohamed
Time Series Constructive Approach Time Series Forecasting Forecasting Performance Missing Data Forecasting Strategy

June 6, 2024

Can Language Models Use Forecasting Strategies?
Sarah Pratt, Seth Blumberg, Pietro Kreitlon Carolino, Meredith Ringel Morris
Language Model Human Prediction LLM Based Forecasting Performance accuratE Prediction Forecasting Strategy

May 24, 2024

MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model
Md Abrar Jahin, Asef Shahriar, Md Al Amin
Deep Learning Demand Forecasting Interpretable Forecast Forecasting Strategy

February 13, 2024

Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting
Riku Green, Grant Stevens, Telmo de Menezes e Silva Filho, Zahraa Abdallah
Classification Code Predictive Model Multi Step Prediction Horizon Univariate Time Series Forecasting Forecasting Strategy Dynamic Strategy

July 24, 2023

Big Data - Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques
Md Abrar Jahin, Md Sakib Hossain Shovon, Jungpil Shin, Istiyaque Ahmed Ridoy, M. F. Mridha
Machine Learning State of the Art Forecasting Big Data Inventory Management Data Preprocessing Supply Chain Resilience Forecasting Analysis Forecasting Strategy

November 7, 2021

DVS: Deep Visibility Series and its Application in Construction Cost Index Forecasting
Tianxiang Zhan, Yuanpeng He, Hanwen Li, Fuyuan Xiao
Application Proficiency Time Series Forecasting Univariate Time Series Forecasting Visibility Graph Forecasting Strategy Index Forecasting

Forecasting Strategy

Papers

Hinge-FM2I: An Approach using Image Inpainting for Interpolating Missing Data in Univariate Time Series

Can Language Models Use Forecasting Strategies?

MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model

Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting

Big Data - Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques

DVS: Deep Visibility Series and its Application in Construction Cost Index Forecasting