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Edy?Tonnizam Mohamad Danial?Jahed ArmaghaniEmail author Mahdi?Hasanipanah Bhatawdekar?Ramesh?Murlidhar Mohd?Nur?Asmawisham?Alel 《Environmental Earth Sciences》2016,75(2):174
Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R 2), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site. 相似文献
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Zhou Jian Zhu Shuangli Qiu Yingui Armaghani Danial Jahed Zhou Annan Yong Weixun 《Acta Geotechnica》2022,17(4):1343-1366
Acta Geotechnica - The squeezing behavior of surrounding rock can be described as the time-dependent large deformation during tunnel excavation, which appears in special geological conditions, such... 相似文献
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Haris Ahmed KHAN Ali Asghar SHAHID Muhammad Jahangir KHAN Taher ZOUAGHI Maria Dolores ALVAREZ Syed Danial Mehdi NAQVI 《《地质学报》英文版》2023,97(1):256-268
This research is focused on the analysis of the sequence stratigraphic units of F3 Block, within a wave-dominated delta of Plio–Pleistocene age. Three wells of F3 block and a 3D seismic data, are utilized in this research. The conventional techniques of 3D seismic interpretation were utilized to mark the 11 surfaces on the seismic section. Integration of seismic sequence stratigraphic interpretation, using well logs, and subsequent 3D geostatistical modeling, using seismic data, aided to evaluat... 相似文献
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Mahdi Hasanipanah Danial Jahed Armaghani Hassan Bakhshandeh Amnieh Mohammadreza Koopialipoor Hossein Arab 《Geotechnical and Geological Engineering》2018,36(4):2247-2260
Flyrock is an adverse effect produced by blasting in open-pit mines and tunneling projects. So, it seems that the precise estimations and risk level assessment of flyrock are essential in minimizing environmental effects induced by blasting. The first aim of this research is to model the risk level associated with flyrock through rock engineering systems (RES) methodology. In this regard, 62 blasting were investigated in Ulu Tiram quarry, Malaysia, and the most effective parameters of flyrock were measured. Using the most influential parameters on flyrock, the overall risk of flyrock was obtained as 32.95 which is considered as low to medium degree of vulnerability. Moreover, the second aim of this research is to estimate flyrock based on RES and multiple linear regression (MLR). To evaluate performance prediction of the models, some statistical criteria such as coefficient of determination (R2) were computed. Comparing the values predicted by the models demonstrated that the RES has more suitable performance than MLR for predicting the flyrock and it could be introduced as a powerful technique in this field. 相似文献
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Manoj Khandelwal Amir Mahdiyar Danial Jahed Armaghani T. N. Singh Ahmad Fahimifar Roohollah Shirani Faradonbeh 《Environmental Earth Sciences》2017,76(11):399
Coal, as an initial source of energy, requires a detailed investigation in terms of ultimate analysis, proximate analysis, and its biological constituents (macerals). The rank and calorific value of each type of coal are managed by the mentioned properties. In contrast to ultimate and proximate analyses, determining the macerals in coal requires sophisticated microscopic instrumentation and expertise. This study emphasizes the estimation of the concentration of macerals of Indian coals based on a hybrid imperialism competitive algorithm (ICA)–artificial neural network (ANN). Here, ICA is utilized to adjust the weight and bias of ANNs for enhancing their performance capacity. For comparison purposes, a pre-developed ANN model is also proposed. Checking the performance prediction of the developed models is performed through several performance indices, i.e., coefficient of determination (R 2), root mean square error and variance account for. The obtained results revealed higher accuracy of the proposed hybrid ICA-ANN model in estimating macerals contents of Indian coals compared to the pre-developed ANN technique. Results of the developed ANN model based on R 2 values of training datasets were obtained as 0.961, 0.955, and 0.961 for predicting vitrinite, liptinite, and inertinite, respectively, whereas these values were achieved as 0.948, 0.947, and 0.957, respectively, for testing datasets. Similarly, R 2 values of 0.988, 0.983, and 0.991 for training datasets and 0.989, 0.982, and 0.985 for testing datasets were obtained from developed ICA-ANN model. 相似文献
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The effect of fully submerged boulders on the flow structure in channels has been studied by some researchers. However, many natural streams have bed material with boulders that are not fully submerged under water. In many natural streams, boulders cover between 1% and 10% of the area of the stream reach. The effect of non-submerged boulders on the velocity profile and flow characteristics is very important for assessing riverbed deformation. The objectives of this paper are to find the pattern of velocity distribution around a non-submerged boulder and to compare it with the classical studies on flow resistance and Reynolds stress distribution in open channels. Also, by considering the variation in the Reynolds stress distribution at different locations around a non-submerged boulder, the effect of a non-submerged boulder on the estimation of shear velocity and resistance to flow has been investigated. Results indicates that inside the scour hole caused by a non-submerged boulder in a river velocity distributions are irregular. However, velocity distributions are regular outside the scour hole. The presence of the boulder causes a considerable deviation of the Reynolds shear stress from the classic distribution, showing a non-specific distribution with negative values. The classical methods for calculating shear velocity are not suitable because these methods do not give detailed velocity and Reynolds stress distributions in natural rivers with a lot of boulders. Thus, the effect of a non-submerged boulder on the estimation of the resistance to flow by considering the variations in velocity and Reynolds stress distributions at different locations around a non-submerged boulder is important and needs to be studied in a natural river instead of just in laboratory flumes. The negative values in Reynolds stress distribution around a boulder indicate that the classical methods are unable to predict resistance to flow, and also show strong turbulence inside the scour hole where the complex flow conditions present ambiguous Reynolds stress distributions. In the current study, to obtain a reasonable estimation of parameters in natural rivers, the classical method has been modified by considering velocity and Reynolds stress distributions through the boundary layer method. 相似文献
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Azam Shahnazar Hima Nikafshan Rad Mahdi Hasanipanah M. M. Tahir Danial Jahed Armaghani Mahyar Ghoroqi 《Environmental Earth Sciences》2017,76(15):527
Ground vibration is one of the common environmental effects of blasting operation in mining industry, and it may cause damage to the nearby structures and the surrounding residents. So, precise estimation of blast-produced ground vibration is necessary to identify blast-safety area and also to minimize environmental effects. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) was proposed to predict blast-produced ground vibration in Pengerang granite quarry, Malaysia. For this goal, 81 blasting were investigated, and the values of peak particle velocity, distance from the blast-face and maximum charge per delay were precisely measured. To demonstrate the performance of the hybrid PSO–ANFIS, ANFIS, and United States Bureau of Mines empirical models were also developed. Comparison of the predictive models was demonstrated that the PSO–ANFIS model [with root-mean-square error (RMSE) 0.48 and coefficient of determination (R 2) of 0.984] performed better than the ANFIS with RMSE of?1.61 and R 2 of 0.965. The mentioned results prove the superiority of the newly developed PSO–ANFIS model in estimating blast-produced ground vibrations. 相似文献