摘要
无人农场在提高生产效率和农产品质量方面具有巨大潜力。然而,投资过程必须面对各种不确定性和潜在的风险。该文基于无人农场基本结构及关键技术,提出一套基于贝叶斯和证据理论下投资风险评估方法,将各类评估指标视为证据源,并将其转化为信任度函数,通过文献总结及实地调研,针对无人农场投资风险评价体系,共筛选出14个评价指标构建无人农场投资风险效益评估体系,并建立相应的数据库及评估系统,投资者可以根据自身情况选择感兴趣的评估指标,并输入相关数据,系统将基于证据理论进行计算并给出相应的风险效益评估报告。研究结果旨在为无人农场投资领域的决策者提供一个科学、全面的评估工具,促进农业生产的可持续发展与创新。
Unmanned farms have great potential to improve productivity and the quality of agricultural products.However,the investment process must face various uncertainties and potential risks.Based on the basic structure and key technology of unmanned farms,this paper proposes a set of investment risk assessment methods based on Bayesian and Dempster-Shafer Theory,which takes various evaluation indicators as evidence sources and transforms them into trust functions.A total of 14 evaluation indexes were screened to construct the unmanned farms’investment risk benefit assessment system,and a corresponding database and evaluation system was established,so that investors could choose the evaluation indicators of interest according to their own situation and input the relevant data,and the system would calculate and give the corresponding risk-benefit evaluation report based on the evidence theory.The research results aim to provide a scientific and comprehensive evaluation tool for decision-makers in the field of unmanned farm investment,and promote the sustainable development and innovation of agricultural production..
作者
王少营
WANG Shaoying(Liaocheng Vocational&Technical Colloge,Liaocheng 252000,China)
出处
《农机使用与维修》
2023年第12期15-20,共6页
Agricultural Machinery Using & Maintenance
关键词
无人农场
证据理论
模糊综合评价法
投资风险
贝叶斯网络
unmanned farms
theory of evidence
fuzzy comprehensive evaluation method
investment risk
bayesian networks
