In the past, we attempted to use a multilayer perceptron neural network as a means to prevent those unknown language inputs from being misidentified as one of the target languages in language identification system. However, the use of multilayer perceptron neural network could not utilize the temporal information from the utterances. Results show that with the use of phonemic unigram as input f...

The ion-sensitive field-effect transistor (ISFET) that is designed to detect a specific ionic activity is susceptible to interfering ions in mixed-ion environments causing the sensor to produce deceptive signals. The objective of this work is to improve the interpretation of ISFET signals in mixed-ion environments. The focus of the research is relating sensor signal to the targeted ion concentr...

estimating of forest equipment productivity is an important aspect of managing cost in forestry, which leads to reduction of operations expenses. in other words, high capital cost in forest harvesting, is a good reason to argue forest engineering research and time modeling. this paper applied one of the artificial intelligence subsets, which are called artificial neural networks (anns), to pred...

Recently, the authors described a training method for a convolutional neural network of threshold neurons. Hidden layers are trained by by clustering, in a feed-forward manner, while the output layer is trained using the supervised Perceptron rule. The system is designed for implementation on an existing low-power analog hardware architecture, exhibiting inherent error sources affecting the com...

Artificial neural network was considered in previous studies for prediction of engine performance and emissions. ICA methodology was inspired in order to optimize the weights of multilayer perceptron (MLP) of artificial neural network so that closer estimation of output results can be achieved. Current paper aimed at prediction of engine power, soot, NOx, CO2, O2, and temperature with the ai...

Due to lack of theory of elasticity, estimation of ultimate torsional strength of reinforcement concrete beams is a difficult task. Therefore, the finite element methods could be applied for determination of strength of concrete beams. Furthermore, for complicated, highly nonlinear and ambiguous status, artificial neural networks are appropriate tools for prediction of behavior of such states. ...

Wear monitoring systems often use neural networks for a sensor fusion with multiple input patterns. Systems for a continuous online supervision of wear have to process pattern sequences. Therefore recurrent neural networks have been investigated in the past. However, in most cases where only noisy input or even noisy output patterns are available for a supervised learning, success is not forthc...

Neural networks are applied, among other things, to classify medical data to various disease classes. It is a great advance if data relevance and complicated relations between input data and output values (classifications) can thoroughly be analyzed. Nevertheless, basic techniques for neural network algorithms commonly disallow such chances. We developed methods to analyze such relevance and re...