Approximation of overloads for a selected tram traction substation using artificial neural networks

The paper proposes a morphological analyser supported by a neural network to inflect words written in Polish. The approach can be also applied to other languages. The main task of the analyser is to create base forms from the analysed words’ forms. Other objective is to provide grammatical information for the analysed form. Computational experiment results confirm that both objectives are fulfilled by the proposed neural network based morphological analyser. The common words are inflected with a very high quality of nearly 99.9%. Other words like geographical names and people’s names, thanks to the incorporation of neural network, inflect with a quality reaching 93.3%.

A Neural Network Based Morphological Analyser of the Natural Language

This paper presents ERP class system objective assessment method when using the neural systems GMDH basing on the Ivachnienko algorithm. An approach to ERPs evaluation aimed at their successful implementation into a class of the small and medium-sized enterprises (SMEs) is considered. The set of performance indices supporting an ERP evaluation in the context of its implementation into a given SME is proposed. Consequently the decision model binding the selected indicators of effectiveness of SME implementation with the parameters of a given ERP system and the parameters of the company as such, which introduced this system is discussed.

The ERP class system objective assessment method

The term „artificial intelligence”, despite its commonness, cannot be easily defined. It primarily results from the lack of clear and precise definition of intelligence itself. There were many different attempts of defining it. The term „artificial intelligence” was put forward and defined for the first time by John McCarthy in 1955. Currently, there are two approaches towards the issues related to 1 Dr inz. Krzysztof Rozanowski jest wykladowcą w Warszawskiej Wyzszej Szkole Informatyki. Pracuje tez w Wojskowym Instytucie Medycyny Lotniczej. ZESZYTY NAUKOWE 109-135

/pdf/sztuczna-inteligencja-rozwoj-szanse-i-zagrozenia-2f0macklkp.pdf

Sztuczna inteligencja rozwój, szanse i zagrożenia

Abstract In this paper, the problem of tool wear prediction during milling of hard-to-cut metal matrix composite Duralcan™ was presented. The conducted research involved the measurements of acceleration of vibrations during milling with constant cutting conditions, and evaluation of the flank wear. Subsequently, the analysis of vibrations in time and frequency domain, as well as the correlation of the obtained measures with the tool wear values were conducted. The validation of tool wear diagnosis in relation to selected diagnostic measures was carried out with the use of one variable and two variables regression models, as well as with the application of artificial neural networks (ANN). The comparative analysis of the obtained results enable.

A. G. Łozowski

Papers

Sztuczne sieci neuronowe [rec.]