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Volumn , Issue , 2006, Pages 1840-1845

Using MLP to determine abiotic factors influencing the establishment of insect pest species

Author keywords

[No Author keywords available]

Indexed keywords

BIODIVERSITY; CLIMATOLOGY; GEOGRAPHICAL REGIONS; PEST CONTROL;

EID: 40649119699     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (12)
  • 1
    • 40649110217 scopus 로고    scopus 로고
    • Crop Protection Compendium - Global Module, 5th Edition. ©CAB International, Wallingford, UK 2003.
    • Crop Protection Compendium - Global Module, 5th Edition. ©CAB International, Wallingford, UK 2003.
  • 2
    • 0033578441 scopus 로고    scopus 로고
    • Neural network models to study relationships between lead concentration in grasses and permanent urban descriptors in Athens city (Greece)
    • Dimopulos, I., Chronopoulos, J., Chronopoulou-Sereli, A., and Lek, S. Neural network models to study relationships between lead concentration in grasses and permanent urban descriptors in Athens city (Greece). Ecological Modelling 120:157-165. 1999.
    • (1999) Ecological Modelling , vol.120 , pp. 157-165
    • Dimopulos, I.1    Chronopoulos, J.2    Chronopoulou-Sereli, A.3    Lek, S.4
  • 4
    • 33747380221 scopus 로고    scopus 로고
    • Prediction of global distribution of insect pest species in relation to climate using an ecological informatics method
    • Accepted
    • Gevrey, M. and Worner, S.P. Prediction of global distribution of insect pest species in relation to climate using an ecological informatics method. Environmental Entomology (Accepted). 2006.
    • (2006) Environmental Entomology
    • Gevrey, M.1    Worner, S.P.2
  • 5
    • 3542994517 scopus 로고    scopus 로고
    • Predictive modelling and spatial mapping of freshwater fish and decapod assemblages using GIS and neural networks
    • Joy, M.K. and Death, R.G. Predictive modelling and spatial mapping of freshwater fish and decapod assemblages using GIS and neural networks. Freshwater Biology 49:1036-1052. 2004.
    • (2004) Freshwater Biology , vol.49 , pp. 1036-1052
    • Joy, M.K.1    Death, R.G.2
  • 6
    • 40649115889 scopus 로고    scopus 로고
    • Predicting ecologically important vegetation variables from remotely sensed optical/radar data using neural networks
    • S. Lek and J-F. Guegan, eds
    • Kimes, D.S., Nelson, R.F. and Fifer, S.T. Predicting ecologically important vegetation variables from remotely sensed optical/radar data using neural networks. In: Artificial Neuronal Networks: Application to Ecology and Evolution. S. Lek and J-F. Guegan, eds. 2000.
    • (2000) Artificial Neuronal Networks: Application to Ecology and Evolution
    • Kimes, D.S.1    Nelson, R.F.2    Fifer, S.T.3
  • 8
    • 0037102687 scopus 로고    scopus 로고
    • Illuminating the "black box": A randomization approach for understanding variable contributions in artificial neural networks
    • Olden, J.D. and Jackson, D.A. Illuminating the "black box": a randomization approach for understanding variable contributions in artificial neural networks. Ecological Modelling 154:135-150. 2002.
    • (2002) Ecological Modelling , vol.154 , pp. 135-150
    • Olden, J.D.1    Jackson, D.A.2
  • 9
    • 3242721368 scopus 로고    scopus 로고
    • An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data
    • Olden, J.D., Joy, M.K. and Death, R.G. An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data. Ecological Modelling 178:389-397. 2004.
    • (2004) Ecological Modelling , vol.178 , pp. 389-397
    • Olden, J.D.1    Joy, M.K.2    Death, R.G.3
  • 10
    • 0030130727 scopus 로고    scopus 로고
    • A Quantitative Study of Experimental Evaluations of Neural Network Learning Algorithms: Current Research Practice
    • Prechelt, L. A Quantitative Study of Experimental Evaluations of Neural Network Learning Algorithms: Current Research Practice. Neural Networks 9(3) 457-462. 1996.
    • (1996) Neural Networks , vol.9 , Issue.3 , pp. 457-462
    • Prechelt, L.1
  • 12
    • 33747603206 scopus 로고    scopus 로고
    • Modelling global insect pest species assemblages to determine risk of invasion
    • Accepted
    • Worner, S.P. and Gevrey, M. Modelling global insect pest species assemblages to determine risk of invasion. Journal of Applied Ecology. (Accepted) 2006.
    • (2006) Journal of Applied Ecology
    • Worner, S.P.1    Gevrey, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.