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An accurate examination of deformability of rock samples in response to any change in stresses is deeply dependent on the reliable determination of properties of the rock as analysis inputs. Although Young’s modulus (E) can provide valuable characteristics of the rock material deformation, the direct determination of E is considered a time-consuming and complicated analysis. The present study is aimed to introduce a new hybrid intelligent model to predict the E of granitic rock samples. Hence, a series of granitic block samples were collected from the face of a water transfer tunnel excavated in Malaysia and transferred to laboratory to conduct rock index tests for E prediction. Rock index... 

In the open-pit mines and civil projects, drilling and blasting is the most common method for rock fragmentation aims. This article proposes a new hybrid forecasting model based on firefly algorithm, as an algorithm optimizer, combined with the adaptive neuro-fuzzy inference system for estimating the fragmentation. In this regard, 72 datasets were collected from Shur river dam region, and the required parameters were measured. Using the different input parameters, six hybrid models were constructed. In these models, 58 and 14 data were used for training and testing, respectively. The proposed hybrid models were then evaluated in accordance with statistical criteria such as coefficient of... 

An accurate examination of deformability of rock samples in response to any change in stresses is deeply dependent on the reliable determination of properties of the rock as analysis inputs. Although Young’s modulus (E) can provide valuable characteristics of the rock material deformation, the direct determination of E is considered a time-consuming and complicated analysis. The present study is aimed to introduce a new hybrid intelligent model to predict the E of granitic rock samples. Hence, a series of granitic block samples were collected from the face of a water transfer tunnel excavated in Malaysia and transferred to laboratory to conduct rock index tests for E prediction. Rock index... 

In the open-pit mines and civil projects, drilling and blasting is the most common method for rock fragmentation aims. This article proposes a new hybrid forecasting model based on firefly algorithm, as an algorithm optimizer, combined with the adaptive neuro-fuzzy inference system for estimating the fragmentation. In this regard, 72 datasets were collected from Shur river dam region, and the required parameters were measured. Using the different input parameters, six hybrid models were constructed. In these models, 58 and 14 data were used for training and testing, respectively. The proposed hybrid models were then evaluated in accordance with statistical criteria such as coefficient of... 

Stock market prediction is regarded as a challenging task in financial time-series forecasting. The central idea to successful stock market prediction is achieving best results using minimum required input data and the least complex stock market model. To achieve these purposes this article presents an integrated approach based on genetic fuzzy systems (GFS) and artificial neural networks (ANN) for constructing a stock price forecasting expert system. At first, we use stepwise regression analysis (SRA) to determine factors which have most influence on stock prices. At the next stage we divide our raw data into k clusters by means of self-organizing map (SOM) neural networks. Finally, all...