Abstract: This paper researches on using RBF neural network for singularity detection in chaotic time series. History data are used for off-line training to RBF network, and then comparing the result ...

Landslide prediction necessitates viewing the past, present, and future states of a slope as a constantly changing dialectical unity, with prediction laws derived from known past and present ...

Abstract: It is known that centers, widths, and weights are three mainly considered factors in constructing a radial basis function (RBF) network. This paper aims at constructing a compact RBF network ...

本記事では、トム・ミッチェルの名著『Machine Learning』第8章の後半を元に、AIのインスタンスベース学習の核心を探求します。RBFネットワークが、いかにしてニューラルネットとk-近傍法を融合させたのか、そして 事例ベース推論（CBR） がAIに人間のような ...

Implementations of a radial basis function (RBF) neural network adaptive PID controller. Uses neural net and error information from PID control to adapt the control ...

Introduction: Intelligent vehicles and autonomous driving have been the focus of research in the field of transport, but current autonomous driving models have significant errors in lateral tracking ...