A reasoning-based strategy for exploring the synergy among alternative crops

  • Authors:

  • Hércules Antonio Do Prado;Edilson Ferneda;Ricardo Coelho De Faria

  • Affiliations:

  • Graduate Program on Knowledge and IT Management, Catholic University of Brasilia, Brasília, DF, Brazil and Embrapa, Management and Strategy Secretariat, Brasília, DF, Brazil;Graduate Program on Knowledge and IT Management, Catholic University of Brasilia, Brasília, DF, Brazil;Undergraduate Program on Economy, Catholic University of Brasilia, Brasília, DF, Brazil

  • Venue:
  • KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
  • Year:
  • 2010

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Abstract

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 synergistic 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.