S. Samarasinghe

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used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year. 1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model(More)
EXTENDED ABSTRACT Mastitis, one of the most significant diseases in dairy herds, is a highly complex sequence of events with various biological causes and associated physiological and behavioral effects that occur as bacterial infection progresses. The aim of the research is to develop a model for on-line detection of mastitis for robotic milking stations.(More)
Artificial neural networks to identify naturally existing disease severity status Your article is protected by copyright and all rights are held exclusively by Springer-Verlag London. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted(More)
EXTENDED ABSTRACT Neural Networks have the capability to approximate nonlinear functions to a high degree of accuracy owing to its nonlinear processing in the hidden layer neurons. However, the optimum network structure that is required for solving a particular problem is still an active area of research. In the past, several network pruning methods based(More)
The distribution of glutamate receptor subunits in human spinal cord has yet to be fully elucidated. The aim of this study was to examine the distribution of mRNAs for the subunits of the AMPA type of glutamate receptor (GluR A, B, C and D) in control human spinal cord using in situ hybridization and to examine in parallel the expression of these mRNAs in(More)
In this paper, prediction capability of a hybrid Artificial Neural Networks (ANN) was investigated to solve the groundwater inverse problem. Initially, a Multi Layer Perceptron (MLP) network was developed and it was found that network produced better results when the target range of the parameters is smaller. Therefore, a Self-Organising Network (SON) was(More)
image processing: Part 1. Tension parallel-and perpendicular-to-grain and comparisons with isotropic behaviour. Silva Fennica 34(3): 251–259. Displacement fields for tensile loaded rubber and wood in parallel-and perpendicular-to-grain were obtained from digital image correlation. The results showed that the digital image correlation can reveal fine details(More)
Weather data in its raw form frequently contains irrelevant and noisy information. Often the hardest task in model development, regardless of the technique used, is translating independent variables from their raw form into data relevant to a particular model. A sequential or cascading temporal correlation analysis was used to identify weather sequences(More)
Flood water in Lake Manapouri is released according to strictly formulated flood rules. B e Real-time Flood Assistant is an expert system which incorporates Lake Manapouri flood rules and the txperience of the control room operators at Transpower NZ Ltd. to assist them in the release of flood water. The expert system is being developed in Level5 Object. The(More)
Classification is a central endeavour in Biology. Heterogeneity of biological systems makes classification more challenging, but this is crucial for effective disease control and management. This study is a computational modelling attempt to classify a plant disease using visual symptoms to ease crop management programmes. Weligama coconut leaf wilt disease(More)