Radial basis function
View article: IMPLEMENTASI SUPPORT VECTOR MACHINE DENGAN RANDOM OVERSAMPLING UNTUK MENGATASI DATA TAK SEIMBANG PADA KLASIFIKASI PENDERITA PENYAKIT CARDIOVASCULAR
IMPLEMENTASI SUPPORT VECTOR MACHINE DENGAN RANDOM OVERSAMPLING UNTUK MENGATASI DATA TAK SEIMBANG PADA KLASIFIKASI PENDERITA PENYAKIT CARDIOVASCULAR Open
Support Vector Machine (SVM) adalah salah satu metode machine learning yang digunakan untuk pengklasifikasikan dengan membagi data menjadi dua kelas yang berbeda. Prinsip kerja SVM adalah mencari fungsi pemisah (hyperplane) yang terbaik. A…
View article: AI-Driven Time-Variant Reliability Assessment of an Elevated Water Tank Over Its Service Life Using Radial Basis Function and Artificial Neural Networks
AI-Driven Time-Variant Reliability Assessment of an Elevated Water Tank Over Its Service Life Using Radial Basis Function and Artificial Neural Networks Open
This study introduces a time-dependent reliability assessment of elevated reinforced-concrete water towers, highlighting the combined influence of material behaviour and environmental actions. The proposed framework integrates Kriging and …
View article: Application of RBF neural network based on improved Harris eagle algorithm optimization for free-form surface machining error prediction
Application of RBF neural network based on improved Harris eagle algorithm optimization for free-form surface machining error prediction Open
With the aim of addressing the problem of low efficiency in free-form surface machining error inspection, an improved Harris hawk optimization-radial basis function (IHHO-RBF) neural network prediction model is proposed in this work. In th…
View article: Human-Inspired Force–Motion Imitation Learning with Dynamic Response for Adaptive Robotic Manipulation
Human-Inspired Force–Motion Imitation Learning with Dynamic Response for Adaptive Robotic Manipulation Open
Recent advances in bioinspired robotics highlight the growing demand for dexterous, adaptive control strategies that allow robots to interact naturally, safely, and efficiently with dynamic, contact-rich environments. Yet, achieving robust…
View article: GEODESIC: Genomic Evolution On Davis-Embedded Surfaces for Integrated Cancer Detection
GEODESIC: Genomic Evolution On Davis-Embedded Surfaces for Integrated Cancer Detection Open
Empirical Validation Suite (8 Studies) Comprehensive validation of the GEODESIC framework for multi-cancer early detection (MCED), demonstrating that cancer mutations and methylation patterns embed into a flower manifold with orthogonal ra…
View article: GEODESIC: Genomic Evolution On Davis-Embedded Surfaces for Integrated Cancer Detection
GEODESIC: Genomic Evolution On Davis-Embedded Surfaces for Integrated Cancer Detection Open
Empirical Validation Suite (8 Studies) Comprehensive validation of the GEODESIC framework for multi-cancer early detection (MCED), demonstrating that cancer mutations and methylation patterns embed into a flower manifold with orthogonal ra…
View article: FWT’s properties.
FWT’s properties. Open
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under sig…
View article: Extracted natural frequencies.
Extracted natural frequencies. Open
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under sig…
View article: General diagram of the nonlinear FWT.
General diagram of the nonlinear FWT. Open
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under sig…
View article: Federated averaging algorithm pseudocode.
Federated averaging algorithm pseudocode. Open
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under sig…
View article: Efficient meshless phase-field modeling of crack propagation by using adaptive load increments and variable node densities
Efficient meshless phase-field modeling of crack propagation by using adaptive load increments and variable node densities Open
This study employs the fourth-order phase-field method (PFM) to investigate crack propagation. The PFM incurs significant computational costs due to its need for a highly dense node arrangement for accurate crack propagation. This study pr…
View article: Adaptive finite‐time disturbance‐observer‐based fault‐tolerant control for output‐constrained PMLM system with unknown dead‐zone input and uncertain control coefficient
Adaptive finite‐time disturbance‐observer‐based fault‐tolerant control for output‐constrained PMLM system with unknown dead‐zone input and uncertain control coefficient Open
This paper investigates the disturbance‐observer‐based finite‐time fault‐tolerant control problem for an output‐constrained permanent magnet linear motor system characterized by unknown dead‐zone inputs and uncertain control coefficients. …
View article: Efficient Meshless Phase-Field Modeling of Crack Propagation by Using Adaptive Load Increments and Variable Node Densities
Efficient Meshless Phase-Field Modeling of Crack Propagation by Using Adaptive Load Increments and Variable Node Densities Open
This study employs the fourth-order phase-field method (PFM) to investigate crack propagation. The PFM incurs significant computational costs due to its need for a highly dense node arrangement for accurate crack propagation. This study pr…
View article: A meshless data-tailored approach to compute statistics from scattered data with adaptive radial basis functions
A meshless data-tailored approach to compute statistics from scattered data with adaptive radial basis functions Open
Constrained radial basis function (RBF) regression has recently emerged as a powerful meshless tool for reconstructing continuous velocity fields from scattered flow measurements, particularly in image-based velocimetry. However, existing …
View article: Comparative evaluation of MLFN and RBFN in integrated seismic inversion: physics-guided pseudo-well augmentation for 3D acoustic impedance modeling in an offshore clastic field, southwest Iran
Comparative evaluation of MLFN and RBFN in integrated seismic inversion: physics-guided pseudo-well augmentation for 3D acoustic impedance modeling in an offshore clastic field, southwest Iran Open
Accurate three-dimensional acoustic impedance modeling in offshore clastic reservoirs remains a significant challenge due to sparse well control and the highly nonlinear relationship between seismic attributes and subsurface elastic proper…
View article: A meshless data-tailored approach to compute statistics from scattered data with adaptive radial basis functions
A meshless data-tailored approach to compute statistics from scattered data with adaptive radial basis functions Open
Constrained radial basis function (RBF) regression has recently emerged as a powerful meshless tool for reconstructing continuous velocity fields from scattered flow measurements, particularly in image-based velocimetry. However, existing …
View article: A fuzzy neural network approach for predicting and optimizing the dynamic stiffness of the Stewart platform
A fuzzy neural network approach for predicting and optimizing the dynamic stiffness of the Stewart platform Open
This study proposes a fuzzy neural network-based prediction and optimization method to address the challenge of modeling dynamic stiffness in Stewart platforms. Traditional approaches, such as the Newton-Euler method and finite element ana…
View article: Performance Analysis of SVM Kernels in Sentiment Classification on Indonesian Local Skincare Dataset
Performance Analysis of SVM Kernels in Sentiment Classification on Indonesian Local Skincare Dataset Open
Purpose: Sentiment analysis is an important aspect of understanding consumers' views on products, especially in the growing skincare industry. This study aims to compare the accuracy and effectiveness of various kernels in the Support Vect…
View article: Three-dimensional deformation modeling via data-adaptively distributed radial basis functions using InSAR and GNSS
Three-dimensional deformation modeling via data-adaptively distributed radial basis functions using InSAR and GNSS Open
View article: Three-dimensional deformation modeling via data-adaptively distributed radial basis functions using InSAR and GNSS
Three-dimensional deformation modeling via data-adaptively distributed radial basis functions using InSAR and GNSS Open
View article: Two-step Generalized RBF-Generated Finite Difference Method on Manifolds
Two-step Generalized RBF-Generated Finite Difference Method on Manifolds Open
Solving partial differential equations (PDEs) on manifolds defined by randomly sampled point clouds is a challenging problem in scientific computing and has broad applications in various fields. In this paper, we develop a two-step general…
View article: Two-step Generalized RBF-Generated Finite Difference Method on Manifolds
Two-step Generalized RBF-Generated Finite Difference Method on Manifolds Open
Solving partial differential equations (PDEs) on manifolds defined by randomly sampled point clouds is a challenging problem in scientific computing and has broad applications in various fields. In this paper, we develop a two-step general…
View article: Radial Coherential Dynamics: Emergent Radial Structure from ∇Φ₍c₎ in Pre-Geometric Coherence Framework (v1.6.5)
Radial Coherential Dynamics: Emergent Radial Structure from ∇Φ₍c₎ in Pre-Geometric Coherence Framework (v1.6.5) Open
This preprint introduces the radial component of coherential dynamics derived from the foundational relation ∇Φ₍c₎ = –k₍c₎(1 – C), expanding the Supremacía Coherencial framework into a specific, testable geometrical consequence. Radial Coh…
View article: Radial Coherential Dynamics v1.7: Mathematical Foundations and Pre-Geometric Framework
Radial Coherential Dynamics v1.7: Mathematical Foundations and Pre-Geometric Framework Open
This document presents version 1.7 of Radial Coherential Dynamics (RCD), a theoretical framework in which spacetime emerges from a primordial coherential field rather than existing as a fundamental entity. RCD v1.7 consolidates the mathema…
View article: Radial Coherential Dynamics: Emergent Radial Structure from ∇Φ₍c₎ in Pre-Geometric Coherence Framework (v1.6.5)
Radial Coherential Dynamics: Emergent Radial Structure from ∇Φ₍c₎ in Pre-Geometric Coherence Framework (v1.6.5) Open
This preprint introduces the radial component of coherential dynamics derived from the foundational relation ∇Φ₍c₎ = –k₍c₎(1 – C), expanding the Supremacía Coherencial framework into a specific, testable geometrical consequence. Radial Coh…
View article: Ultra-precision control of dual-axis scanning mechanism based on PSO-RBF neural network
Ultra-precision control of dual-axis scanning mechanism based on PSO-RBF neural network Open
Broadband ultra-high resolution spectrometers require arc-second level grating positioning accuracy to achieve picometer to femtometer spectral resolution. Traditional control approaches exhibit significant limitations when confronting sys…
View article: Radial Coherential Dynamics v1.7: Mathematical Foundations and Pre-Geometric Framework
Radial Coherential Dynamics v1.7: Mathematical Foundations and Pre-Geometric Framework Open
This document presents version 1.7 of Radial Coherential Dynamics (RCD), a theoretical framework in which spacetime emerges from a primordial coherential field rather than existing as a fundamental entity. RCD v1.7 consolidates the mathema…
View article: Efficient online quantum circuit learning with no upfront training
Efficient online quantum circuit learning with no upfront training Open
Optimization is a promising candidate for studying the utility of variational quantum algorithms (VQAs). However, evaluating cost functions using quantum hardware introduces runtime overheads that limit exploration. Surrogate-based methods…
View article: Hybrid ab initio and empirical machine learning models for the potential energy surface
Hybrid ab initio and empirical machine learning models for the potential energy surface Open
We propose a methodology to generate hybrid machine learning models for the potential energy surface trained simultaneously on data from ab initio electronic structure calculations and on thermodynamic and/or structural observables from ex…
View article: Modeling and Comparative Study on Cure Kinetics for CFRP: Autocatalytic vs. Neural Network vs. Angle Information-Enhanced RBF Models
Modeling and Comparative Study on Cure Kinetics for CFRP: Autocatalytic vs. Neural Network vs. Angle Information-Enhanced RBF Models Open
Carbon fiber reinforced polymer (CFRP) components require precise curing process control to ensure quality, but traditional phenomenological cure kinetics models face limitations in handling nonlinearity and data diversity. This study addr…