Research and Application of the Project Initiation Assessment Model for Tobacco Industry Rural Revitalization Projects
Pages 524 - 529
Abstract
This study introduces an innovative evaluation model for project initiation assessment in rural revitalization efforts within the tobacco industry, leveraging the capabilities of Random Forest and Back Propagation (BP) neural network algorithms. Initially, expert scores are recalculated based on their professional competence. The Random Forest algorithm is then employed to select relevant evaluation indicators, followed by the BP neural network to achieve precise and efficient project scoring. This dual-algorithm approach not only enhances the accuracy of project selection but also allows the model to dynamically adapt to evolving conditions in the tobacco industry and rural policies. The results demonstrate that this model significantly improves the efficiency and accuracy of project evaluations, providing a valuable tool for advancing rural revitalization initiatives.
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Dai Yongping, Zhang Fuqiang, Xu Xuehan. 2018. Countermeasures for Tobacco Industry's Services in Rural Revitalization Strategy. Rural Science and Technology, 2018(26), 29-30.
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Index Terms
- Research and Application of the Project Initiation Assessment Model for Tobacco Industry Rural Revitalization Projects
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Published In
June 2024
1206 pages
ISBN:9798400710247
DOI:10.1145/3690407
Copyright © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
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Published: 24 October 2024
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CAIBDA 2024
CAIBDA 2024: 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms
June 21 - 23, 2024
Zhengzhou, China
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