Open Access
ARTICLE
C.M.T. Tien1, N. Thai-Quang1, N. Mai-Duy1, C.-D. Tran1, T. Tran-Cong1
CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.6, pp. 425-469, 2015, DOI:10.3970/cmes.2015.104.425
Abstract In this paper, we propose a three-point coupled compact integrated radial basis function (CCIRBF) approximation scheme for the discretisation of second-order differential problems in one and two dimensions. The CCIRBF employs integrated radial basis functions (IRBFs) to construct the approximations for its first and second derivatives over a three-point stencil in each direction. Nodal values of the first and second derivatives (i.e. extra information), incorporated into approximations by means of the constants of integration, are simultaneously employed to compute the first and second derivatives. The essence of the CCIRBF scheme is to couple the extra information of the nodal first… More >
Open Access
ARTICLE
Wang Yang1,2, Juanjuan Li1, Jian Yang1,3, Lin Wei4
CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.6, pp. 471-491, 2015, DOI:10.3970/cmes.2015.104.471
Abstract Harvesting is the most difficult and costly operation in cassava production. Currently, most cassava harvest still depends on manual tools. Effective mechanized harvesters are necessary to improve harvesting quality and reduce production cost. Therefore, it is very important to figure out key information for designing an effective tuber lifting system used in bionic “dig-pull” harvesters. A numerical simulation model of human-stem-tuber-soil system was developed to carry out numerical simulation of manually pulling tuber. Coupling algorithm of Lagrange and smoothed particle hydrodynamics (SPH) was used in the model. Lifting mechanism of experienced farmer was studied at a micro level. Influence of… More >
Open Access
ARTICLE
Liming Yang1, Yongping Gao2, Qun Sun3
CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.6, pp. 493-506, 2015, DOI:10.3970/cmes.2015.104.493
Abstract Minimax probability machine (MPM) has been recently proposed and shown its advantage in pattern recognition. In this paper, we present a new minimax probabilistic approach (MPA),which can provide an explicit lower bound on prediction accuracy. Applying the Chebyshev-Cantelli inequality, the MPA is posed as a second order cone program formulation and solved effectively. Following that, this method is exploited directly to recognize the purity of hybrid seeds using near-infrared spectroscopic data. Experimental results in different spectral regions show that the proposed MPA is competitive with the existing minimax probability machine and support vector machine in generalization, while requires less computational… More >
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