Zhao Kai
Department of management, Harbin Finance University, Harbin, Heilongjiang, 150030, China
Chi De Shui
Faculty of Business administration, Harbin Cambridge University, Heilongjiang, Harbin, 150000, China

DOI:https://doi.org/10.5912/jcb2502


Abstract:

With the increasing global emphasis on sustainable development, green biotechnology has emerged as a key enabler in addressing pressing environmental challenges and promoting economic growth. The integration of ecological resource monitoring with economic benefits has become an important area of research, as it provides insights into how biotechnology can balance environmental preservation with economic progress. By leveraging the advantages of green biotechnology, industries can optimize resource utilization, mitigate ecological damage, and achieve cost-effective solutions for sustainable development. This study focuses on the commercial value of green biotechnology, particularly in the context of ecological resource monitoring and its correlation with economic benefits. Using neural network algorithms, this research establishes a model to analyze and predict the relationship between ecological monitoring data and economic outcomes. The results demonstrate that the application of green biotechnology significantly enhances the efficiency of ecological monitoring and contributes to economic optimization. The improved algorithm proposed in this study achieves higher accuracy—9.14% higher than the traditional BP algorithm—thereby providing a reliable framework for evaluating the economic potential of green biotechnology in ecological applications.