Authors: Joshua Ebere Chukwuere

Published on: March 20, 2024

Impact Score: 8.0

Arxiv code: Arxiv:2403.13536

Summary

• What is new: Utilizing machine learning techniques to generate predictive models for unemployment rates in developing nations amid Industry 4.0.
• Why this is important: Obstacles in obtaining data, ensuring model precision, and upholding ethical standards in predicting unemployment rates in developing nations.
• What the research proposes: A predictive conceptual model using machine learning techniques like regression analysis and neural networks.
• Results: Effective in understanding and addressing factors contributing to unemployment, capable of predicting future rates and tracking progress in reducing unemployment.

Technical Details

Technological frameworks used: Predictive conceptual model framework

Models used: Regression analysis, Neural networks

Data used: Economic growth, Inflation, Population increase, Education levels, Technological progress data

Potential Impact

Decision-makers, enterprises in developing nations; economic growth and employment sectors.

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