Abstract The use of multi-layer perceptrons (MLP) to deter-mine the signicance of climatic variables to the establishment of insect pest species is described. Results show that the MLP are able to learn to accurately predict the establishment of a pest species within a specic geographic region. Analysis of the MLP yielded insights into the contribution of the individual input variables and allowed for the identication of those variables that were most signicant in either encouraging or inhibiting establishment. I
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...
This thesis presents a case study of applying machine learning tools to build a predictive\ud model ...
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...
The use of multi-layer perceptrons (MLP) to determine the significance of climatic variables to the ...
The use of multi-layer perceptrons (MLP) to determine the significance of climatic variables to the ...
Insect pests now pose a greater threat to crop production given the recent emergence of insecticide ...
A method is presented for applying a null-model analysis to the verification of the significance of ...
Backpropagation of errors (BP) trained Multi-Layer Perceptrons (MLP) (Rumelhart et al., 1986) have p...
The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely man...
The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely man...
Predictions of the distribution of fungal crop diseases have previously been made solely from climat...
A comparison of two artificial neural network methods for predicting the risk of insect pest species...
This document is the initial report on a systematic approach to the application of MLP to the aphid ...
This paper presents a novel methodology for multi-scale and multi-type spatial data integration in s...
A sustainable approach to pest management is Integrated Pest Management (IPM) which uses bio-control...
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...
This thesis presents a case study of applying machine learning tools to build a predictive\ud model ...
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...
The use of multi-layer perceptrons (MLP) to determine the significance of climatic variables to the ...
The use of multi-layer perceptrons (MLP) to determine the significance of climatic variables to the ...
Insect pests now pose a greater threat to crop production given the recent emergence of insecticide ...
A method is presented for applying a null-model analysis to the verification of the significance of ...
Backpropagation of errors (BP) trained Multi-Layer Perceptrons (MLP) (Rumelhart et al., 1986) have p...
The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely man...
The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely man...
Predictions of the distribution of fungal crop diseases have previously been made solely from climat...
A comparison of two artificial neural network methods for predicting the risk of insect pest species...
This document is the initial report on a systematic approach to the application of MLP to the aphid ...
This paper presents a novel methodology for multi-scale and multi-type spatial data integration in s...
A sustainable approach to pest management is Integrated Pest Management (IPM) which uses bio-control...
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...
This thesis presents a case study of applying machine learning tools to build a predictive\ud model ...
Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic a...