Understanding Helicoverpa armigera Pest Population Dynamics related to Chickpea Crop Using Neural Networks

  • Authors:

  • Rajat Gupta;B. V. L. Narayana;P. Krishna Reddy;G. V. Ranga Rao;C. L. L. Gowda;Y. V. R. Reddy;G. Rama Murthy

  • Affiliations:

  • -;-;-;-;-;-;-

  • Venue:
  • ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
  • Year:
  • 2003

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Abstract

Insect pests are a major cause of crop loss globally. Pestmanagement will be effective and efficient if we canpredict the occurrence of peak activities of a given pest.Research efforts are going on to understand the pestdynamics by applying analytical and other techniques onpest surveillance data sets. In this study we make an effortto understand pest population dynamics using NeuralNetworks by analyzing pest surveillance data set ofHelicoverpa armigera or Pod borer on chickpea (Cicerarietinum L.) crop. The results show that neural networkmethod successfully predicts the pest attack incidences forone week in advance.