INTERACTIVE KNOWLEDGE LEARNING BY ARTIFICIAL INTELLIGENCE FOR SMALLHOLDERS  

作　　者：Weili ZHANG Renlian ZHANG Hongjie JI Anja SEVERIN Zhaojun LI 

机构地区：[1]Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China. [2]Electrical Engineering and Information Technology Faculty,Technical University of Munich,Munich 80333,Germany

出　　处：《Frontiers of Agricultural Science and Engineering》2023年第4期648-653,共6页农业科学与工程前沿（英文版）

摘　　要：Enhancement of farming management relies heavily on enhancing farmer knowledge.In the past,both the direct learning approach and the personnel extension system for improving fertilization practices of smallholders has proven insufficiently effective.Therefore,this article proposes an interactive knowledge learning approach using artificial intelligence as a promising alternative.The system consists of two parts.The first is a dialog interface that accepts information from farmers about their current farming practices.The second part is an intelligent decision system,which categorizes the information provided by farmers in two categories.The first consists of onfarm constraints,such as fertilizer resources,split application times and seasons.The second comprises knowledge-based practices by farmers,such as nutrient in-and output balance,ratios of different nutrients and the ratios of each split nutrient amount to the total nutrient input.The interactive knowledge learning approach aims to identify and rectify incorrect practices in the knowledge-based category while considering the farmer's available finance,labor,and fertilizer resources.Investigations show that the interactive knowledge learning approach can make a strong contribution to prevention of the overuse of nitrogen and phosphorus fertilizers,and mitigating agricultural non-point sourcepollution.

关 键 词：FINANCE PREVENTION FARMING 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] S126[自动化与计算机技术—控制科学与工程]