An early warning of corporate financial crises has long been the focus of investors and enterprises. Integrated early warning models for financial crises perform better than normal models, but most ...
Radial Basis Function-based Kolmogorov-Arnold Networks (RBF-KAN) This repository implements Radial Basis Function (RBF)-based Kolmogorov-Arnold Networks (KAN), a neural network architecture based on ...
Radial Basis Function Neural Networks-Based Surrogate Model for Dynamic Multi-Objective Optimization
Abstract: This paper introduces a novel surrogate modeldriven strategy to solve dynamic multi-objective optimization problems (DMOPs) with time-varying objective functions. This strategy holds promise ...
This paper introduces Bayesian regularised radial basis function network (BR-RBFN) as a novel approach to capture the 1-day daily future stock price movement. Naturally, the existence of prolonged ...
Abstract: Prediction of stock market indices is an interesting and challenging research problem in financial data mining area because movement of stock indices are nonlinear and they are dependent ...
Dr. James McCaffrey of Microsoft Research explains how to design a radial basis function (RBF) network -- a software system similar to a single hidden layer neural network -- and describes how an RBF ...
SPECIAL ISSUE NO. 106. Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development (SUMMER 2020), pp. 255-258 (4 pages) Published By: Coastal Education & Research ...
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