Machine learning–assisted efficient demand forecasting using endogenous and exogenous indicators for the textile industry-Reference-Cited by-同舟云学术

Machine learning–assisted efficient demand forecasting using endogenous and exogenous indicators for the textile industry

Published:2022-07-15 Issue: Volume: Page:1-20
ISSN:1367-5567
Container-title:International Journal of Logistics Research and Applications
language:en
Short-container-title:International Journal of Logistics Research and Applications

Author:

Yasir Muhammad¹,Ansari Yasmeen²,Latif Khalid³,Maqsood Haider⁴,Habib Adnan⁵,Moon Jihoon⁶,Rho Seungmin⁶

Affiliation:

1. School of Management, FAST National University of Computer and Emerging Sciences, Islamabad, Pakistan

2. Department of Finance, College of Administrative and Financial Sciences, Saudi Electronic University, Jeddah, Saudi Arabia

3. Department of Commerce, Government College University Faisalabad, Faisalabad, Pakistan

4. Department of Management Sciences, Bahria University Islamabad, Islamabad, Pakistan

5. Department of Computer Engineering, UET Taxila, Taxila, Pakistan

6. Department of Industrial Security, Chung-Ang University, Seoul, South Korea

Funder

Korea Institute for Advancement of Technology

Korea Government

National Research Foundation of Korea

Ministry of Education

Publisher

Informa UK Limited

Subject

Management Science and Operations Research,Management Information Systems,Business and International Management,Strategy and Management,Management of Technology and Innovation

Link

https://www.tandfonline.com/doi/pdf/10.1080/13675567.2022.2100334

Reference55 articles.

1. Towards Sustainable Textile and Apparel Industry: Exploring the Role of Business Intelligence Systems in the Era of Industry 4.0

2. Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)

3. Principles of Forecasting

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