Journal of Engineering, Project, and Production Management, 2026, 16(6), 2025-339
An Economic Benefit Prediction Method for Investment Projects Based on An Improved Fuzzy Real Options Approach
1 Lecturer,
School of Accounting, Xijing University, Xi’an 710123, China
2 Student, School of Accounting,
Xijing University, Xi’an 710123, China
3 Instructor, School of Accounting,
Xijing University, Xi’an 710123, China
4 Professor, College of Management,
Xi’an University of Science and Technology, Xi’an 710054, China,
5 Associate Professor, College of
Management, Xi’an University of Science and Technology, Xi’an 710054,
China, E-mail: wanngting@outlook.com (corresponding author)
Project Management
Received December 16, 2025; revised January 28, 2026; accepted June 5, 2026
Available online June 17, 2026
Abstract: To optimize current economic benefit forecasting methods and address their uncertainty and ambiguity in uncertain market environments, this study constructs a comprehensive economic benefit forecasting model for investment projects using an Improved Fuzzy Real Options (IFRO) method, a Bidirectional Long Short-Term Memory Network (BiLSTM), and a fuzzy clustering algorithm, thereby improving its forecasting accuracy. The study first analyzes the improved fuzzy Real Options (ROs) method, showing a Root Mean Square Error (RMSE) of 4.3 and a mean percentage error of only 1.1% when forecasting uncertainty risk in investment projects. Furthermore, the accuracy of investment decision-making reaches 92.1% after using this method to predict project uncertainty risk, demonstrating that the (IFRO) method can accurately assess the uncertainty risk of investment projects. The constructed economic benefit forecasting model is then evaluated, showing a trend prediction accuracy of 92.1%. After optimization based on the economic benefit forecasting results, the cost-benefit ratio of the decision-making project reaches 3.2, indicating that the constructed economic benefit forecasting model can accurately predict the economic benefits of investment projects. This model quantifies the uncertainty risks and enhances the accuracy of trend predictions, thereby providing enterprise managers with a multi-dimensional decision-making basis. It helps them dynamically adjust investment strategies and optimize resource allocation in complex market environments, ultimately achieving maximum returns under control.
Keywords: Real options method, economic benefit prediction, bidirectional long short-term memory network, fuzzy clustering algorithm, uncertainty, improved fuzzy real options method.
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Citation: Wang, T., Liu, Y., Si, Y., Lyu, J., and Yuan, X. (2026). An Economic Benefit Prediction Method for Investment Projects Based on An Improved Fuzzy Real Options Approach. Journal of Engineering, Project, and Production Management, 16(6), 2025-339.
