Modelling of river discharges using neural networks derived from support vector regression

Neural networks are often used to model complex and nonlinear systems, as they can approximate nonlinear systems with arbitrary accuracy and can be trained from data. Amongst the neural networks, Associative Memory Networks (AMNs) are often used, since they are less computation intensive, and yet good generalization results can be obtained. However, this can only be achieved if the structure of the AMNs is suitably chosen. An approach to choose the structure of the AMNs is to use the Support Vectors (SVs) obtained from the Support Vector Machines. The SVs are obtained from a constrained optimization for a given data set and an error bound. For convenience, this class of AMNs is referred to as the Support Vector Neural Networks (SVNNs). In this paper, the modelling of river discharges with rainfall as input using the SVNN is presented, from which the nonlinear dynamic relationship between rainfall and river discharges is obtained. The prediction of river discharges from the SVNN can give early warning of severe river discharges when there are heavy rainfalls.published_or_final_versio

Modelling of river discharges and rainfall using radial basis function networks based on support vector regression

Associative memory networks (AMNs) based on radial basis functions (RBFs) are often used to model complex and nonlinear systems, as they can approximate nonlinear systems with arbitrary accuracy and can be trained from data. However, good generalization results can only be obtained if the structure of the RBF network is suitably chosen. An approach to select the structure of the RBF networks based on the support vectors (SVs) of the support vector machine (SVM) has been proposed. The main advantage of this approach is that the structure of the network can be obtained objectively, as the SVs of the SVM are obtained from a constrained optimization for a given error bound. For convenience, this class of AMNs is referred to as support vector radial basis function networks (SVRBFNs). In this paper, the modelling of the relationship between rainfall and river discharges of the Fuji river using the SVRBFN is presented. As there are large outliers in the modelling errors arising from the data collection process, they are removed first before retraining the SVRBFN using the adjusted data, in order to obtain a better approximation of the relationship between rainfall and river discharges. The generalization ability of the SVRBFN is verified using the test data that are the most recent not used in the training of the network. The prediction of river discharges for given rainfalls can be computed from the SVRBFN, which can provide early warning of severe river discharges when there is heavy and prolonged rainfall.link_to_subscribed_fulltex

Clinicopathologic significance of bcl-2 expression in the surgical treatment of oral tongue carcinoma

Aim: There is still controversy on the incidence of positive expression of bcl-2 and its prognostic significance for oral tongue carcinoma patients who are treated by surgery. The present study aims at resolving the controversy on the clinicopathologic significance of bcl-2 in a well selected group of patients who satisfy the recruitment criteria: (1) oral tongue carcinoma, (2) squamous cell carcinoma, (3) primary surgical treatment. Method: Bcl-2 expression was studied by immunohistochemistry on glossectomy specimens of 73 patients. The expression of bcl-2 was correlated with clinicopathologic data. Results: Of the 73 tumours, 11% had positive expression of bcl-2. Bcl-2 expression was not significantly correlated with tumour grade, stage, nodal metastasis and survival. Conclusion: Bcl-2 expression played a minor role in oral tongue carcinoma. It had no significant correlation with tumour grade, stage and nodal metastasis. It also had no prognostic value on survival for patients who were treated by primary surgery. © 2002 Elsevier Science Ltd. All rights reserved.link_to_subscribed_fulltex

The clinicopathologic significance of p53 and p21 expression in the surgical management of lingual squamous cell carcinoma

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