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Publication Metadata only Prediction of soil nitrogen content using E-nose and radial basis function(2019-01-18) Jigme Norbu; Theerapat Pobkrut; Treenet Thepudom; Thinley Namgyel; Teerayut Chaiyasit; Yu Thazin; Teerakiat Kerdcharoen; Mahidol University, e-nose coupled with Radial Basis Function (RBF) is employed to determine the amount of nitrogen (N) which is one of the main nutrients in the soil. The results demonstrate that not only does the e-nose clearly discriminate the odors of soilPublication Metadata only Bagging of Duo Output Neural Networks for Single Output Regression Problem(2010-01-01) Somkid Amornsamankul; Pawalai Kraipeerapun; Mahidol University; Ramkhamhaeng Universityneural networks, and the ensemble of support vector machine with linear, polynomial, and radial basis function kernels. © 2010 IEEE.Publication Metadata only Solving regression problem with complementary neural networks and an adjusted averaging technique(2010-12-01) Pawalai Kraipeerapun; Sathit Nakkrasae; Chun Che Fung; Somkid Amornsamankul; Ramkhamhaeng University; Murdoch University; Mahidol University; South Carolina Commission on Higher Educationindustry. We found that our proposed technique provides better performance when compared to the traditional CMTNN, backpropagation neural network, and support vector regression with linear, polynomial, and radial basis function kernels. © 2010 SpringerPublication Metadata only Applying duo output neural networks to solve single output regression problem(2009-12-01) Pawalai Kraipeerapun; Somkid Amornsamankul; Chun Che Fung; Sathit Nakkrasae; Ramkhamhaeng University; Mahidol University; Murdoch Universitywith linear, polynomial, and radial basis function kernels. © 2009 Springer-Verlag Berlin Heidelberg.Publication Metadata only Quantitative structure-property relationship study of spectral properties of green fluorescent protein with support vector machine(2013-01-05) Chanin Nantasenamat; Kakanand Srungboonmee; Saksiri Jamsak; Natta Tansila; Chartchalerm Isarankura-Na-Ayudhya; Virapong Prachayasittikul; Mahidol University; Prince of Songkla University. Such descriptors were mapped onto a higher dimensional space via kernel functions (e.g. linear, polynomial and radial basis function kernels) and learning is then performed using SVM. The predicted spectral properties were well correlated with their experimentalPublication Metadata only The hydration structure of 18-crown-6/K+complex as studied by Monte Carlo simulation using ab initio fitted potential(2006-09-01) Sriprajak Krongsuk; Teerakiat Kerdcharoen; Supot Hannongbua; Center for Nanoscience and Nanotechnology; Mahidol Universitythe structural properties of the complex in an aqueous solution using the Monte Carlo simulation method. The radial distribution function (RDF) centered at K+to the oxygen atom of water shows a sharp first peak at 2.88 Å. The corresponding coordination number...The intermolecular potential between a 18-crown-6/K+complex and a water molecule is derived from 1200 energy points obtained from quantum chemical calculations using the 6-31G** basis set. The ab initio fitted potential was then applied to study