首页> 外文会议>International conference on knowledge-based and intelligent information and engineering systems;KES 2010 >A Reasoning-Based Strategy for Exploring the Synergy among Alternative Crops
【24h】

A Reasoning-Based Strategy for Exploring the Synergy among Alternative Crops

机译:探索替代作物之间协同作用的基于推理的策略

获取原文

摘要

This paper focuses on the problem of choosing one among many alternatives, each one expressed as a combination of factors. The problem is approached with a reasoning-based strategy that takes into account the relations among the alternatives discovered by means of a data mining technique. The problem of choosing a combination of different vegetables based on the syner-gistic effects of the combination and considering some socioeconomic variables is taken as a case study. The idea is to identify combinations that lead to gains in productivity, profitability, and lower costs. Experts recognize that some combinations of cultures can generate synergistic effects that can lead to profits or losses, depending on the production variables involved. However, the analysis of the results of the cultivation of multiple varieties involves a space of possibilities whose treatment is not trivial. Among the alternatives available, this study explored the Combinatorial Neural Model (CNM) that assures the hypotheses generation for all possible combinations, within limits defined by the model parameters. The study was carried out on data collected from farms in the Brazilian Federal District. Two approaches to the problem are presented: (i) the first one based on univariate and bi-dimensional data analysis and (ii) a multidimensional analysis based on the CNM results.
机译:本文着重于在众多选择中选择一个的问题,每个选择都表示为多种因素的组合。该问题是通过基于推理的策略来解决的,该策略考虑了通过数据挖掘技术发现的替代方案之间的关系。以结合蔬菜的协同效应并考虑一些社会经济变量来选择不同蔬菜的蔬菜为例。这个想法是要找出可以提高生产率,盈利能力和降低成本的组合。专家认识到,某些文化组合可以产生协同效应,这可能会导致利润或损失,具体取决于所涉及的生产变量。但是,对多个品种的种植结果进行的分析涉及一个可能性空间,其处理并非易事。在可用的替代方案中,本研究探索了组合神经模型(CNM),该模型可确保在模型参数定义的限制内所有可能组合的假设生成。该研究是根据从巴西联邦区的农场收集的数据进行的。提出了解决该问题的两种方法:(i)第一种基于单变量和二维数据分析的方法;(ii)基于CNM结果的多维分析的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号