A review on prognostic techniques for non-stationary and non-linear rotating systems
MS Kan, ACC Tan, J Mathew - Mechanical Systems and Signal Processing, 2015 - Elsevier
The field of prognostics has attracted significant interest from the research community in
recent times. Prognostics enables the prediction of failures in machines resulting in benefits …
recent times. Prognostics enables the prediction of failures in machines resulting in benefits …
Cooperative learning for radial basis function networks using particle swarm optimization
This paper presents a new evolutionary cooperative learning scheme, able to solve function
approximation and classification problems with improved accuracy and generalization …
approximation and classification problems with improved accuracy and generalization …
Investigation of fractal market hypothesis and forecasting time series stock returns for Tehran Stock Exchange and London Stock Exchange
M Moradi, M Jabbari Nooghabi… - International Journal of …, 2021 - Wiley Online Library
An alternative investment theory to the widely utilized efficient market hypothesis, fractal
market hypothesis analyses the daily randomness of the market and the turbulence …
market hypothesis analyses the daily randomness of the market and the turbulence …
Training algorithms for radial basis function networks to tackle learning processes with imbalanced data-sets
Nowadays, many real applications comprise data-sets where the distribution of the classes
is significantly different. These data-sets are commonly known as imbalanced data-sets …
is significantly different. These data-sets are commonly known as imbalanced data-sets …
Global and local modelling in RBF networks
Radial basis function networks are traditionally known as local approximation networks as
they are composed by a number of elements which, individually, mainly take care of the …
they are composed by a number of elements which, individually, mainly take care of the …
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
In the classification problem field, we often encounter many real application areas in which
the data do not have an equitable distribution among the different classes of the problem. In …
the data do not have an equitable distribution among the different classes of the problem. In …
[图书][B] Advances in Computational Intelligence: 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12 …
I Rojas, G Joya, A Catala - 2015 - books.google.com
This two-volume set LNCS 9094 and LNCS 9095 constitutes the thoroughly refereed
proceedings of the 13th International Work-Conference on Artificial Neural Networks …
proceedings of the 13th International Work-Conference on Artificial Neural Networks …
Characterization of concentrating photovoltaic modules by cooperative competitive radial basis function networks
AJ Rivera, B García-Domingo, MJ del Jesus… - Expert Systems with …, 2013 - Elsevier
Concentrating Photovoltaic (CPV) technology attempts to optimize the efficiency of solar
energy production systems. As conventional Photovoltaic (PV) technology, suffers from …
energy production systems. As conventional Photovoltaic (PV) technology, suffers from …
Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass
The production of biofuels is a process that requires the adjustment of multiple parameters.
Performing experiments in which these parameters are changed and the outputs are …
Performing experiments in which these parameters are changed and the outputs are …
Intra-specific competitive co-evolutionary artificial neural network for data classification
This paper presents an alternative approach of competitive co-evolutionary (ComCoE)
artificial neural network (ANN) developed for data classification. The motivation of this work …
artificial neural network (ANN) developed for data classification. The motivation of this work …