期刊文献+

INTERACTIVE KNOWLEDGE LEARNING BY ARTIFICIAL INTELLIGENCE FOR SMALLHOLDERS

原文传递
导出
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.
出处 《Frontiers of Agricultural Science and Engineering》 CSCD 2023年第4期648-653,共6页 农业科学与工程前沿(英文版)
  • 相关文献

参考文献3

二级参考文献24

共引文献1156

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部