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1

Uncertainty analysis of the stability parameters of rock walls

Mokhtar S., Yousefirad M.

Archives of Civil Engineering

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2020

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Vol. 66, nr 4

703--721

EN

The purpose of this paper is to investigate the effects of natural uncertainties and effective parameters on the stability of plate-type rock walls. For this, the effective factors and geo-mechanical properties in the study area were obtained using field experiments. Stability analysis of rock walls was investigated for 40 scenarios in dry and saturated states. These parameters were then evaluated using Easyfit software and Markov chain analysis and Monte Carlo simulation by Rock Plane software. Comparison of the results of numerical and uncertainty methods shows that the rock walls with 60-80 degree slope are stable; and In saturated state they require stability due to the reduction of shear strength. Fixation of the rock walls was also investigated, indicating an optimum angle of 30° for the installation of the rock screw. The results show that the Monte Carlo simulation provides a simpler interpretation and the uncertainty methods are more accurate and reliable than the numerical methods.

2

The use of certain staffing requirements as a means of benchmarking academic staff structure

Ekhosuehi V. U., Omosigho S. E.

Mathematica Applicanda

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2018

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Vol. 46, no. 2

259--272

EN

Considering the statutory staffing requirements by the National Universities Commission in Nigeria, this study develops a model to benchmark the academic staff structure that will meet the staffing requirements. The model utilises the absorbing Markov chain framework as its theoretical underpinning. An upper bound on the structure that will mature to meet the statutory staffing requirement is developed. Empirical data are used to demonstrate the utility of the model.

PL

Biorąc pod uwagę ustawowe wymogi dotyczące personelu stawiane przez Narodową Komisję Uniwersytetów w Nigerii, opracowano model porównawczy struktury kadry akademickiej, która spełnia wymagania kadrowe. Podstawą teoretyczną modelu jest struktura łańcucha Markowa ze stanami pochłaniającymi. Graniczne stany struktury pojawiają się przy spełnianiu wymogów ustawowych. Dane empiryczne służą do wykazania przydatności modelu.

3

Application of Gray-Fuzzy-Markov Chain Method for Day-Ahead Electric Load Forecasting

Asrari A., Javan D. S., Javidi M. H., Monfared M.

Przegląd Elektrotechniczny

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2012

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R. 88, nr 3b

228-237

EN

Short-term load forecasting (STLF) plays a decisive role in electric power system operation and planning. Accurate load forecasting not only reduces the generation costs of power systems, but also serves to maximize profit for participants in electricity markets. In recent years, power markets have grown more deregulated and competitive, adding to the complexity and uncertainties of load, and making it more difficult for conventional techniques to accurately forecast the load. To improve the accuracy of load forecasting, this paper suggests a hybrid method, called Gray-Fuzzy-Markov Chain Method (GFMCM), comprising three stages. In the first stage, daily load is forecasted by Gray model, with its training deviations classified, in a second stage, by fuzzy-set theory, and finally, fed into Markov chain model to predict future relative errors that might be supplied by the Gray model. The proposed approach has been verified by the historical data of power consumption in Ontario, PJM and Iranian electricity markets. The obtained forecasts by GFMCM proved to have better prediction properties compared to the other forecasting techniques, such as Gray models, specifically GM(1,1) and GM(1,2), ARIMA time series, wavelet-ARIMA and multi-layer perceptron (MLP) neural network.

PL

W celu poprawy jakości przewidywania zużycia energii autorzy zaproponowali hybrydową metodę GMMCM (Gray-Fuzzy-Markov Chan Method). W pierwszym etapie prognoza obciążeń jest prowadzona przy wykorzystaniu modelu Gray, następnie stosuje się metody logiki rozmytej. Błąd prognozowania analizowany jest metodą Markova.