Name
Title | ||
|---|---|---|
Understanding Helicoverpa armigera Pest Population Dynamics related to Chickpea Crop Using Neural Networks |
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. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ICDM.2003.1251017 | ICDM |
Keywords | Field | DocType |
forone week,major cause,neural networks,techniques onpest surveillance data,insect pest,understanding helicoverpa armigera pest,population dynamics,cicerarietinum l.,pest surveillance data,pest population dynamic,chickpea crop,pod borer,crop loss,pest attack,pest control,crops,neural nets,neural network,population dynamic,statistical analysis,data mining,pest management | Population,Helicoverpa armigera,Biotechnology,Computer science,Crop,Pest control,Integrated pest management,PEST analysis,Artificial intelligence,Artificial neural network,Machine learning,Statistical analysis | Conference |
ISBN | Citations | PageRank |
0-7695-1978-4 | 1 | 0.48 |
References | Authors | |
1 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rajat Gupta | 1 | 9 | 2.67 |
| B. V. L. Narayana | 2 | 1 | 0.48 |
| P. Krishna Reddy | 3 | 55 | 8.53 |
| G. V. Ranga Rao | 4 | 1 | 0.48 |
| C. L. L. Gowda | 5 | 1 | 0.48 |
| Y. V. R. Reddy | 6 | 1 | 0.48 |
| G. Rama Murthy | 7 | 1 | 0.82 |