Advanced Computational Forecasting for Agri-Business Supply Chain Resilience-Reference-Cited by-同舟云学术

Advanced Computational Forecasting for Agri-Business Supply Chain Resilience

Published:2024-06-28 Issue: Volume: Page:36-55
ISSN:2327-3275
Container-title:Advances in Business Information Systems and Analytics
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Author:

Rath Kali Charan¹,Panda Lakshmi Prasad²^ORCID,Rao N. V. Jagannadha³,Mohanta Gopal Krushna⁴,Panda Anmol⁵^ORCID

Affiliation:

1. Department of Mechanical Engineering, GIET University, India

2. Government College of Engineering, Kalahandi, India

3. School of Management Studies, GIET University, Gunupur, India

4. Department of Mechanical Engineering; GIET University, Gunupur, India

5. GIET University, India

Abstract

This chapter focuses on using advanced statistical methods to improve predictions in the agri-business sector. It integrates cutting-edge computational techniques and statistical models to address supply chain disruptions in agriculture. The main goal is to create a robust forecasting framework that predicts market trends, demand fluctuations, and enhances supply chain resilience. The novelty lies in combining advanced statistical methodologies like time series analysis, predictive modeling, and data-driven insights for a comprehensive approach. This aims to improve supply chain management in agri-business by fostering adaptability and resilience in changing market conditions.

Publisher

IGI Global

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