Investigating the impact of the internet on managing green financial innovation and improving agricultural conditions in water-scarce Asian regions using ANN modeling

Autor: Xiaohan Sheng, Guangmin Liu
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-024-72117-4
Popis: Abstract This research focuses on the importance of management strategies, green innovation, and sustainable practices in the agricultural sector. These factors are crucial for job creation, food security, and environmental conservation. Particularly in water-scarce regions, effective management is necessary to overcome natural resource constraints and encourage a shift towards digital agriculture (AGRI). The study aims to identify and analyze the challenges and issues related to agricultural research and technology in Asian countries. The collected data were analyzed using exploratory factor analysis in the SPSS software. The analysis revealed a range of issues and challenges for agricultural development, including those related to the structure and policy framework, the availability and quality of resources and infrastructures, and the provision of effective support services, all of which encompassed factors such as research and technology investment, research management, productivity, research culture, networking, and the integration of higher education and agricultural research. To estimate the efficiency of technology development, agricultural development, and support services for AGRI, an artificial neural network (ANN) was utilized. The ANN was trained by incorporating changes in management strategies, green innovation, and sustainability across a broader range of experimental scenarios. The evaluation of the ANN's predictions showed that improvements in management strategies and the adoption of green innovation and sustainability significantly impacted the productivity of technology development, agricultural development, and support services for AGRI. The accuracy of the ANN's predictions was further assessed using linear regression. The results indicated an acceptable level of error when compared to the target results obtained from experimental tests. Overall, this study emphasizes the importance of effective management, green innovation, and sustainable practices in driving advancements in technology and agricultural development.
Databáze: Directory of Open Access Journals
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