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|Title:||Protein secondary sturcture prediction using artifical neural networks and support vectors machines||Authors:||Jin, Guosheng||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Computer science and engineering::Computing methodologies
|Issue Date:||2005||Source:||Jin, G. (2005). Protein secondary sturcture prediction using artifical neural networks and support vectors machines. Master’s thesis, Nanyang Technological University, Singapore.||Abstract:||In this thesis, a novel Hybrid Neural Networks Predictor (HNNP) system for the Protein Secondary Structure Prediction (PSSP) problem is described. By explor- ing such a new hybrid system, the intention is to investigate the feasibility of the HNNP in PSSP and even achieve improvements over existing methods. The proposed system is a cascaded network of the Radial Basis Function Neural Net- work (RBFNN) and the Multi-Layer Perceptron Neural Network (MLPNN).||URI:||https://hdl.handle.net/10356/4454||DOI:||10.32657/10356/4454||Rights:||Nanyang Technological University||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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