Computational Intelligence Model for Estimating Intensity of Blast-Induced Ground Vibration in a Mine Based on Imperialist Competitive and Extreme Gradient Boosting Algorithms     

Ding  Ziwei  Nguyen  Hoang  Bui  Xuan-Nam  Zhou  Jian  Moayedi  Hossein 《Natural Resources Research》2020,29(2):751-769

Natural Resources Research - In this paper, we developed a novel hybrid model ICA–XGBoost for estimating blast-produced ground vibration in a mine based on extreme gradient boosting (XGBoost)...  相似文献   

Simulating winter wheat production potential under near-future climate change in arid regions of northeast Iran     

Saberali  Seyed Farhad  Shirmohammadi-Aliakbarkhani  Zahra  Nastari Nasrabadi  Hossein 《Theoretical and Applied Climatology》2022,148(3-4):1217-1238

Theoretical and Applied Climatology - Water scarcity is the key challenge in arid regions, which exacerbates under climate change (CC) and must be considered to assess the impacts of CC on cropping...  相似文献   

Applicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods   总被引：3，自引：0，他引：3  

Fatemeh Falah  Samira Ghorbani Nejad  Omid Rahmati  Mania Daneshfar  Hossein Zeinivand 《国际地球制图》2017,32(10):1069-1089

Groundwater is the most valuable natural resource in arid areas. Therefore, any attempt to investigate potential zones of groundwater for further management of water supply is necessary. Hence, many researchers have worked on this subject all around the world. On the other hand, the Generalized Additive Model (GAM) has been applied to environmental and ecological modelling, but its applicability to other kinds of predictive modelling such as groundwater potential mapping has not yet been investigated. Therefore, the main purpose of this study is to evaluate the performance of GAM model and then its comparison with three popular GIS-based bivariate statistical methods, namely Frequency Ratio (FR), Statistical Index (SI) and Weight-of-Evidence (WOE) for producing groundwater spring potential map (GSPM) in Lorestan Province Iran. To achieve this, out of 6439 existed springs, 4291 spring locations were selected for training phase and the remaining 2147 springs for model evaluation. Next, the thematic layers of 12 effective spring parameters including altitude, plan curvature, slope angle, slope aspect, drainage density, distance from rivers, topographic wetness index, fault density, distance from fault, lithology, soil and land use/land cover were mapped and integrated using the ArcGIS 10.2 software to generate a groundwater prospect map using mentioned approaches. The produced GSPMs were then classified into four distinct groundwater potential zones, namely low, moderate, high and very high classes. The results of the analysis were finally validated using the receiver operating characteristic (ROC) curve technique. The results indicated that out of four models, SI is superior (prediction accuracy of 85.4%) following by FR, GAM and WOE, respectively (prediction accuracy of 83.7, 77 and 76.3%). The result of groundwater spring potential map is helpful as a guide for engineers in water resources management and land use planning in order to select suitable areas to implement development schemes and also government entities.  相似文献   

Practical Investigations on Use of Weighted Joint Density to Decrease the Limitations of RQD Measurements     

Mohammad Haftani  Hossein A. Chehreh  Abolfazl Mehinrad  Kheirollah Binazadeh 《Rock Mechanics and Rock Engineering》2016,49(4):1551-1558

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Design of a support vector machine with different kernel functions to predict scour depth around bridge piers     

Hassan Sharafi  Isa Ebtehaj  Hossein Bonakdari  Amir Hossein Zaji 《Natural Hazards》2016,84(3):2145-2162

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A Simple Limit Equilibrium Approach for Calculation of Ultimate Bearing Capacity of Shallow Foundations on Two-Layered Granular Soils     

Mahmoud Ghazavi  Amir Hossein Eghbali 《Geotechnical and Geological Engineering》2008,26(5):535-542

The bearing capacity of shallow foundations in a non-homogeneous soil profile has been a challenging task in geotechnical engineering. In this paper, a limit equilibrium method is used for calculating bearing capacity factors of shallow foundations constructed on a two-layered granular soil profile. The main objective has been to determine the ultimate bearing capacity computed from equivalent bearing capacity factors N_q and N_γ and comparing that with numerical analysis using finite element methods. It will be shown that the data obtained form the developed method are well comparable with those obtained from FE approach, specially when the difference between shear strength parameters of layers is low which is a practical case for sedimentary soil profiles and also for artificially compacted soils. A computer program has been developed to investigate the influence of various parameters on bearing capacity factors.  相似文献   

Modelling thermal comfort of visitors at urban squares in hot and arid climate using NN-ARX soft computing method     

Shahab Kariminia  Shervin Motamedi  Shahaboddin Shamshirband  Jamshid Piri  Kasra Mohammadi  Roslan Hashim  Chandrabhushan Roy  Dalibor Petković  Hossein Bonakdari 《Theoretical and Applied Climatology》2016,124(3-4):991-1004

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Risk Analysis and Prediction of Floor Failure Mechanisms at Longwall Face in Parvadeh-I Coal Mine using Rock Engineering System (RES)     

Sajjad Aghababaei  Gholamreza Saeedi  Hossein Jalalifar 《Rock Mechanics and Rock Engineering》2016,49(5):1889-1901

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Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models   总被引：1，自引：0，他引：1  

Hossein Mojaddadi Rizeei  Maryam Adel Saharkhiz  Noordin Ahmad 《国际地球制图》2016,31(10):1158-1177

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.  相似文献   

Effect of dry density,soil texture and time-spatial variable water content on the soil thermal conductivity     

Saeid Nikoosokhan  Hossein Nowamooz  Cyrille Chazallon 《Geomechanics and Geoengineering》2016,11(2):149-158

Study of the heat transfer process in saturated and unsaturated soils requires, basically, a relationship between thermal conductivity and the characteristics of the soil, such as water content, dry density and texture of the soil. This study intends to produce a generic model that can predict soil thermal conductivity with the help of easily measurable parameters. The proposed model is first calibrated using measured thermal conductivities from literature data. In order to validate the proposed model the predicted thermal conductivity of this proposed model as well as existing ones are compared with the measured thermal conductivity in literature for different soils. Validation of the proposed model was also performed on our experimental results obtained for a compacted Misillac sand and in-situ clay loam soils. The results show an average of 15% improvement in prediction accuracy for the proposed model compared to the existing models, considering all soil textures. Moreover, we perform a model to estimate thermal conductivity over time throughout the profile of soil in the context of seasonal variation of temperature. The proposed model shows an important effect of heterogeneity on the thermal conductivity variations of a double layered soil.  相似文献