15 papers · ranked by Valyu relevance
J. M. González-Camacho, G. de los Campos, P. Pérez, D. Gianola + 4 more
The availability of high density panels of molecular markers has prompted the adoption of genomic selection (GS) methods in animal and plant breeding. In GS, parametric, semi-parametric and non-parametric regressions models are used for predicting quantitative traits. This article shows how to use neural networks with…
Kanak Kalita, Shankar Chakraborty, S Madhu, Manickam Ramachandran + 2 more
'Xiao-Zhi Gao' 'Krzysztof Jamroziak'] High-fidelity structural analysis using numerical techniques, such as finite element method (FEM), has become an essential step in design of laminated composite structures. Despite its high accuracy, the computational intensiveness of FEM is its serious drawback. Once trained…
Khang Jie Liew, Ahmad Ramli, Ahmad Abd. Majid, Yuanquan Wang
This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the…
Ivan Kopal, Marta Harničárová, Jan Valíček, Jan Krmela + 1 more
'Ondrej Lukáč'] The presented work deals with the creation of a new radial basis function artificial neural network-based model of dynamic thermo-mechanical response and damping behavior of thermoplastic elastomers in the whole temperature interval of their entire lifetime and a wide frequency range of dynamic…
Liru Mu, Xinlong Feng, José F. F. Mendes
In this paper, the radial basis function finite difference method is used to solve two-dimensional steady incompressible Navier-Stokes equations. First, the radial basis function finite difference method with polynomial is used to discretize the spatial operator. Then, the Oseen iterative scheme is used to deal with…
Jiajia Chen, Pan Zhao, Huawei Liang, Tao Mei
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement…
Nikolaos P. Bakas
In this work, a numerical solution for the extrapolation problem of a discrete set of n values of an unknown analytic function is developed. The proposed method is based on a novel numerical scheme for the rapid calculation of higher order derivatives, exhibiting high accuracy, with error magnitude of O(10−100) or…
P. Kumudha, R. Venkatesan
Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and…
Sonia Bhattacharya, Himadri Chakraborty Bhattacharyya
Severe Thunderstorms are the extreme weather convective features. It causes local calamities in various ways. Proper prediction with lead time is an important factor to prevent such calamities from saving people. Here, both probabilistic and machine learning techniques are applied to weather data to obtain proper…
Jie Liu, Fuzhang Wang, Sohail Nadeem, Abderrahim Wakif
The aim of this paper is to introduce a novel category of radial basis functions that incorporate smoothing techniques. Initially, we employ the power augmented and shape parameter schemes to create the radial basis functions. Subsequently, we apply the newly-constructed radial basis functions using the traditional…
Qing Zhang, Abdul Rashid Abdullah, Choo Wei Chong, Mass Hareeza Ali
Gross domestic product (GDP) is an important indicator for determining a country's or region's economic status and development level, and it is closely linked to inflation, unemployment, and economic growth rates. These basic indicators can comprehensively and effectively reflect a country's or region's future economic…
Fenghua Huang, Luming Yan
To solve the poor generalization and flexibility problems that single kernel SVM classifiers have while classifying combined spectral and spatial features, this paper proposed a solution to improve the classification accuracy and efficiency of hyperspectral fused images: (1) different radial basis kernel functions…
Athanasios Donas, Ioannis Kordatos, Alex Alexandridis, George Galanis + 3 more
'George Galanis' 'Ioannis Th. Famelis' 'Yuh-Shyan Chen' 'Wei Yi'] The aim of this study is to introduce and evaluate a dual filter that combines Radial Basis Function neural networks and Kalman filters to enhance the accuracy of numerical wave prediction models. Unlike the existing methods, which focus solely on…
Maryam Masnadi-Shirazi, Shankar Subramaniam
The curse of dimensionality has long been a hurdle in the analysis of complex data in areas such as computational biology, ecology and econometrics. In this work, we present a forecasting algorithm that exploits the dimensionality of data in a nonparametric autoregressive framework. The main idea is that the dynamics…
Long Huang, Shaohua Xu, Kun Liu, Ruiping Yang + 1 more
A fuzzy radial basis adaptive inference network (FRBAIN) is proposed for multichannel time-varying signal fusion analysis and feature knowledge embedding. The model which combines the prior signal feature embedding mechanism of the radial basis kernel function with the rule-based logic inference ability of fuzzy system…