Time series analysis using normalized PG-RBF network with regression weights

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Time series analysis using normalized PG-RBF network with regression weights

This paper proposes a framework for constructing and training a radial basis function (RBF) neural network. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. The structure of the Gaussian functions is modi"ed using a pseudoGaussian function (PG) i...

متن کامل

Time series analysis using RBF networks with FIR/IIR synapses

Radial basis functions networks (RBF) with dynamic synapses are introduced. The novelty aspect consists in replacing the standard scalar values of the output weights by discrete-time FIR/IIR filters. LMS-type learning algorithms are derived and simulation results for prediction of chaotic time series are reported. ( 1998 Elsevier Science B.V. All rights reserved.

متن کامل

Vehicle's velocity time series prediction using neural network

This paper presents the prediction of vehicle's velocity time series using neural networks. For this purpose, driving data is firstly collected in real world traffic conditions in the city of Tehran using advance vehicle location devices installed on private cars. A multi-layer perceptron network is then designed for driving time series forecasting. In addition, the results of this study are co...

متن کامل

Time series forecasting using a hybrid RBF neural network and AR model based on binomial smoothing

ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Neurocomputing

سال: 2002

ISSN: 0925-2312

DOI: 10.1016/s0925-2312(01)00338-1