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Abstract: Road header performance prediction plays a significant role in the successful implementation of a tunneling project; so that, there is a need for accurate prediction of the advance rate of tunneling. However, there is relatively less study on predicting the performance of such machinery by using soft computing techniques although they have some advantages over the other methods. On the other hand, often models applied for road header performance prediction neglect interaction between machine and rock mass parameters. The Takagi–Sugeno (TS) fuzzy system model, one of the most popular fuzzy models, can be applied to solve complex problems by transferring a nonlinear system into a set of linear subsystems. However, in many situations, it is not convenient to identify all the rules; so, using the fuzzy clustering techniques in which the rules are resulted from measured data can be useful and valuable. In this paper, a new model based on the geological and geotechnical site conditions is developed to predict the road header performance. The model is developed using soft computing technique that applies the concept of fuzzy logic to take into account the uncertainty and complexity derived from the interaction between rock properties and road header parameters. The prediction capabilities offered by TS fuzzy model based on subtractive clustering method are demonstrated by using field data of obtained from Tabas coal mine in Iran. [Copyright &y& Elsevier]

Developing a precise and accurate model of gold price is critical to assets management because of its unique features. In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) model have been used for modeling the gold price, and compared with the traditional statistical model of ARIMA (autoregressive integrated moving average). The three performance measures, the coefficient of determination (R 2), root mean squared error (RMSE), mean absolute error (MAE), are utilized to evaluate the performances of different models developed. The results show that the ANFIS model outperforms other models (i.e. ANN and ARIMA model), in terms of different performance criteria during the training and validation phases. Sensitivity analysis showed that the gold price changes are highly dependent upon the values of silver price and oil price. [ABSTRACT FROM PUBLISHER]

Using the balanced scorecard approach based on sustainable development parameters is a powerful and useful methodology to evaluate the sustainable performance of organization or company. In this paper, a new approach based on sustainability balanced scorecard (SBSC) and multi criteria decision making (MCDM) approaches is developed for evaluating the performance of oil producing companies in Iran. For reflecting the interdependent relationships among factors influencing the problem under consideration, analytical network process (ANP), a branch of the MCDM techniques, is employed. However, using the ANP method for calculating the preference ratings of alternatives is a time-consuming and bothersome process; therefore, COPRAS (COmplex PRoportional ASsessment) technique is adopted to prioritize the feasible alternatives in terms of linguistic variables. Based on this study, the results demonstrate the effectiveness of the proposed model. The performance evaluation model proposed by using a combination of the MCDM methods and the SBSC approach helps authorities to make an attempt for achieving a competitive advantage. [ABSTRACT FROM AUTHOR]