We consider the problem of learning a nite automaton with recurrent n e u r a l networks from positive evidence. We train Elman recurrent neural networks with a set of sentences in a language and extract a nite automaton by clustering the states of the trained network. We observe that the generalizations beyond the training set, in the language recognized by the extracted automaton, are due to ...

In this paper a multi agent model for predicting monthly maximum and minimum quote prices has been proposed. This model is based on the training of Elman neural networks and using particle swarm optimization for obtaining the best parameters of the neural networks. Also one method for reducing the effects of overfitting problem is suggested. This method averages the outputs of an ensemble netwo...

Cooperative coevolution decomposes an optimisation problem into subcomponents and collectively solves them using evolutionary algorithms. Memetic algorithms provides enhancement to evolutionary algorithms with local search. Recently, the incorporation of local search into a memetic cooperative coevolution method has shown to be efficient for training feedforward networks on pattern classificati...

— For predicting the shelf life of processed cheese stored at 7-8º C, Elman single and multilayer models were developed and compared. The input variables used for developing were applied in order to compare the prediction ability of the developed models. The Elman models got simulated very well and showed excellent agreement between the experimental data and the predicted values, suggesting tha...

The internal leakage of a hydraulic cylinder is an inevitable system failure that seriously affects the working efficiency system. Therefore, it very important to accurately identify and predict data in cylinder. In this paper, model proposed simulate small cylinders, convert amount oil into strain signals through high-precision gauges train collected using various neural networks form computat...

Artificial neural networks (ANNs) are computational modeling tools that have recently emerged and found extensive acceptance in many disciplines for modeling complex realworld problems. ANN-based models are empirical in nature, however they can provide practically accurate solutions for precisely or imprecisely formulated problems and for phenomena that are only understood through experimental ...

This work has been partially supported by the Science-Technology Development Project of Jilin Province of P.R. China (Grant No. 20030520) and the Key Science-Technology Project of the National Education Ministry of P.R. China (Grant No. 02090). Address correspondence to Professor Y.C. Liang, College of Computer Science and Technology, Jilin University, Changchun 130012, P.R. China. E-mail: lian...

In the paper we present a new approach based on application of neural networks to detect SQL attacks. SQL attacks are those attacks that take advantage of using SQL statements to be performed. The problem of detection of this class of attacks is transformed to time series prediction problem. SQL queries are used as a source of events in a protected environment. To differentiate between normal S...