학술논문

Enhancing Decision-Making and Operational Efficiency Through Demand Prediction Using Machine Learning
Document Type
Conference
Source
2024 International Conference on Emerging Trends in Networks and Computer Communications (ETNCC) Emerging Trends in Networks and Computer Communications (ETNCC), 2024 International Conference on. :1-5 Jul, 2024
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Surveys
Machine learning algorithms
Reviews
Decision making
Production
Pricing
Predictive models
Market research
Scheduling
Business
machine learning
business planning
optimizing operations
market performance
Language
Abstract
Launching a new product in the market and then getting reviews about the product so that the feasibility of the product can be planned accordingly mainly depends on the survey information or data from the sources. Here, decision-making plays a significant contribution, and this is where demand prediction comes into the picture. Demand prediction will not only help in planning the business and optimizing the operations but will also help get more information about the product's performance in the market. This study mainly focuses on how machine learning algorithms and other techniques can be used to predict the demand for the product. The model proposed in this study can enhance decision-making and efficiency and lead to high-standard market performance.