An SVM-based machine learning method for the separation of alteration zones in Sungun porphyry copper deposit     

Maliheh Abbaszadeh  Ardeshir Hezarkhani  Saeed Soltani-Mohammadi 《Chemie der Erde / Geochemistry》2013

Sungun porphyry copper deposit is in East Azarbaijan province, NW of Iran. There exist four hypogene alteration types in Sungun: potassic, propylitic, potassic–phyllic, and phyllic. Copper mineralization is essentially associated more with the potassic and less with the phyllic alterations and their separation is, therefore, quite important. This research has tried to separate these two alteration zones in Sungun porphyry copper deposit using the Support Vector Machine (SVM) method based on the fluid inclusion data, and seven variables including homogenization temperatures, salinity, pressure, depth, density and the Cu grade have been measured and calculated for each separate sample. To apply this method, use is made of the radial basis function (RBF) as the kernel function. The best values for λ and C (the most important SVM parameters) that perform well in the training and test data are 0.0001 and 1, respectively. If these values for λ and C are applied, the phyllic and potassic alteration zones in the training and test data will be separated with an accuracy of about 95% and 100%, respectively. This method can help geochemists in separating the alteration zones because classifying and separating samples microscopically is not only very hard, but also quite time and money consuming.  相似文献   

Sorption of lead by chemically modified rice bran     

T. Fatima  R. Nadeem  A. Masood  R. Saeed  M. Ashraf 《International Journal of Environmental Science and Technology》2013,10(6):1255-1264

In this work, the effectiveness of native and chemically modified rice bran to remove heavy metal Pb(II) ions from aqueous solution was examined. Chemical modifications with some simple and low-cost chemicals resulted in enhancement of the adsorption capacities and had faster kinetics than native rice bran. Experiments were conducted in shake flasks to monitor the upshot of parameters over a range of pH, initial Pb(II) concentrations and contact times using a batch model study. The sorption capacities q (mg g^?1) increased in the following order: NaOH (147.78), Ca(OH)₂ (139.08), Al(OH)₃ (127.24), esterification (124.28), NaHCO₃ (118.08), methylation (118.88), Na₂CO₃ (117.12) and native (80.24). The utmost uptake capacity q (mg g^?1) was shown by NaOH-pretreated rice bran. The results showed that, using NaOH-modified rice bran, the chief removal of Pb(II) was 74.54 % at pH 5, primary Pb(II) concentration 100 mg L^?1 and contact time 240 min. Equilibrium isotherms for the Pb(II) adsorption were analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm model, showing Pb(II) sorption as accessible through the high value of the correlation coefficient (R ² = 0.993), showed a q _max value of 416.61 mg g^?1. The kinetic model illustrated adsorption rates well, depicted by a second order, which gives an indication concerning the rate-limiting step. Thermodynamic evaluation of the metal ion ?G ^o was carried out and led to the observation that the adsorption reaction is spontaneous and endothermic in nature. NaOH chemically modified rice bran was a superb biosorbent for exclusion of Pb(II) and proved to be excellent for industrial applications.  相似文献   

Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method     

Eysa Salajegheh  Saeed Gholizadeh  Mohsen Khatibinia 《地震工程与工程振动(英文版)》2008,7(1):13-24

The optimal seismic design of structures requires that time history analyses （THA） be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function （RBF） neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization （BPSO） is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.  相似文献   

Evaluation of Tailings from a Porphyry Copper Mine based on Joint Simulation of Contaminants     

Sohrabian  Babak  Hosseinzadeh Gharehgheshlagh  Hojjat  Soltani-Mohammadi  Saeed  Abdollahi Sharif  Jafar 《Natural Resources Research》2020,29(2):983-1005

Natural Resources Research - Tailings from porphyry copper mines contain environmentally harmful amounts of elements such as copper, molybdenum, lead and cobalt. Geostatistical simulation of...  相似文献   

Application of different clustering approaches to hydroclimatological catchment regionalization in mountainous regions,a case study in Utah State     

Elnaz Sharghi  Vahid Nourani  Saeed Soleimani  Fahreddin Sadikoglu 《山地科学学报》2018,15(3):461-484

With respect to the different hydrological responses of catchments, even the adjacent ones, in mountainous regions, there are a great number of motivations for classifying them into homogeneous clusters. These motivations include prediction in ungauged basins (PUB), model parameterization, understanding the potential impact of environmental changes, transferring information from gauged catchments to the ungauged ones. The present study investigated the similarity of catchments through the hydro-climatological pure time-series of a 14-year period from 2001 to 2015. Data sets encompass more than 13,000 month-station streamflow, rainfall, and temperature data obtained from 27 catchments in Utah State as one of the eight mountainous states of the USA. The identification, analysis, and interpretation of homogeneous catchments were investigated by applying the four approaches of clustering, K-means, Ward, and SOM (Self-Organized Map) and a newly proposed Wavelet-Entropy-based (WE-SOM) clustering method. By using two clustering evaluation criteria, 3, 5, and 6 clusters were determined as the best numbers of clusters, depending on the method employed, where each cluster represents different hydro-climatological behaviors. Despite the absence of geographic characteristics in input data matrix, the results indicated a regionalization in agreement with topographic characteristics. Considering the dependency of the hydrological behavior of catchments on the physiographic field aspects and characteristics, WE-SOM method demonstrated a more acceptable performance, compared to the other three conventional clustering methods, by providing more clusters. WE-SOM appears to be a promising approach in catchment clustering. It preserves the topological structure of data which can, as a result, be proofed in a greater number of clusters by dividing data into higher numbers of distinct clusters with similar altitudes of catchments in each cluster. The results showed the aptitude of wavelets to quantify the time-based variability of temperature, rainfall and streamflow, in the way contributing to the regionalization of diverse catchments.  相似文献   

Prediction of riverine suspended sediment discharge using fuzzy logic algorithms, and some implications for estuarine settings     

Saeed Jafari Mianaei  Ali Reza Keshavarzi 《Geo-Marine Letters》2010,30(1):35-45

The ability of fuzzy logic algorithms to model relationships between stream flow and suspended sediment discharge was investigated using daily measurements of stream flow and suspended sediment discharge for the Escanaba River mouth station, situated on the shore of Lake Michigan and operated by the US Geological Survey. Three different configurations of inputs were applied, whereby the inputs were fuzzified into fuzzy subsets of variables by means of triangular membership functions. The relationships between inputs and suspended sediment discharge (output) were represented by a set of fuzzy rule expressed in IF–THEN format. The weighted average method served for defuzzification. The commonly used sediment rating curve was also applied to the data, and its performance compared with that of the three models by means of statistical analyses. For all three models, suspended sediment discharge predicted by the fuzzy logic algorithm was in satisfactory agreement with observations. Furthermore, the fuzzy logic algorithms performed better than the sediment rating curve, particularly at higher rates of suspended sediment discharge (in this study, more than 50  × 10⁶ g/day). Considered collectively, the use of fuzzy logic algorithms is suggested as a simple and effective approach for better prediction of suspended sediment discharge, also for estuaries.  相似文献   

Prediction of rainfall using artificial neural networks for synoptic station of Mashhad: a case study     

Najmeh?Khalili  Saeed?Reza?KhodashenasEmail author  Kamran?Davary  Mohammad?Mousavi?Baygi  Fatemeh?Karimaldini 《Arabian Journal of Geosciences》2016,9(13):624

In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M₅₃₁ and M₇₄₁, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models.  相似文献   

Role of early warning systems for sustainable agriculture in Iran     

Saeed Sharafi  Mahmud Ramroudi  Mehdi Nasiri  Mohammad Galavi  Gholam Ali Kamali 《Arabian Journal of Geosciences》2016,9(19):734

Drought is a complex phenomenon in meteorology and can affect agriculture. Its impacts vary greatly since they depend not only on the magnitude, timing, duration, and frequency of rainfall deficits but also on the differing responses of various plants to water stress. The essence of good drought management is to use this range of responses to the best advantage. Iran is one of the world’s largest and most productive suppliers of food and fiber. The objective of this study was, therefore, to gather and analyze standardized information on the Role of Early Warning Systems for Sustainable Agriculture for cereals and leguminous and industrial crops in Iran environmental zones. Annual average rainfall (mm year^?1) and ET_O (mm year^?1) are 76.56 and 3001, respectively, in stations with very dry climate; 195.41 and 2249, respectively, in stations with dry climate; 343.9 and 1351, respectively, in stations with semi-dry climate; 583.8 and 1153, respectively, in stations with semi-humid climate; and 1272 and 949, respectively, in stations with humid climate. The maximum and minimum of annual average rainfall happened in Rasht (1337 mm year^?1) and Zabol (57 mm year^?1) stations, and the maximum and minimum for annual average ET_O happened in Chabahar (3909.15 mm year^?1) and Anzali harbor (890.6 mm year^?1), respectively. Therefore, 13.63 % of stations have suitable conditions for crop productions and 86.37 % are in critical conditions.  相似文献   

Storage dam’s locality placing by MCDM techniques (case study: three dams in Iran)     

Saeed Reza Khodashenas  Niloufar Yarahmadi 《Arabian Journal of Geosciences》2016,9(13):612

MCDM (multi-criteria decision making) techniques are used to choose the best alternative among the relevant ones and rank the others. In this research, MCDM techniques were used to choose and rank the best places for constructing storage dams in Iran. To achieve this goal, the relevant information and data about dam construction situations were collected. Then, the recommended places for constructing storage dams were ranked by using MCDM techniques and according to the most suitable criteria which have been chosen based on experts’ opinions. To rank dam constructing project, three MCDM techniques, i.e., TOPSIS, AHP, and DEMATEL, were used. The results showed that the application of MCDM models by putting emphasis on economic, social, political, and technical criteria enables government and watershed managers to choose the best alternative(s) for constructing a storage dam.  相似文献   

Erratum to: The interannual precipitation variability in the southern part of Iran as linked to large-scale climate modes     

Farnaz Pourasghar  Tomoki Tozuka  Saeed Jahanbakhsh  Behrooz Sari Sarraf  Hooshang Ghaemi  Toshio Yamagata 《Climate Dynamics》2012,39(12):3121-3121

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