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41.
The sedimentary basin of Gavkhuni playa lake includes two sedimentary environments of delta and playa lake. These environments consist of mud, sand and salt flats. There are potentials for concentration of heavy metals in the fine-grained sediments (silt and clay) of the playa due to existence of Pb/Zn ore deposits, industrial and agricultural regions in the water catchment of Zayandehrud River terminating to this area. In order to study the concentration of heavy metals and the controlling factors on their distribution in the fine-grained sediments, 13 samples were taken from the muddy facies and concentration of the heavy metals were determined. The results showed that the heavy metal concentrations range in the sediments (in ppm) are Mn (395.5–1,040), Sr (100.4–725.76), Pb (14.66–91.06), Zn (23.59–80.9), Ni (37–73.66), Cu (13.83–29.83), Co (5.73–13.78), Ag (3.03–4.76) and Cd (2.3–5.5) in their order of abundances. The concentration of Ag is noticeable in the sediments relative to the average concentration of this element in mud sediments. The amounts of Pb and Zn are relatively high in all the samples in comparison with the other elements. The concentration of Ni is relatively high in the oxidized samples. The distribution of Pb is directly related to organic matter content of the sediments. The concentrations of Zn, Sr, Cu, Co and Cd in the samples of the playa are lower than those in the delta. The amount of illite is another factor influencing Zn and Pb concentrations. Sr is more concentrated in the sediments with the high content of calcium carbonate. The distribution pattern of Cu, Co, Pb and Mn resembles to that of the clay content of the sediments. The clay content shows positive correlations with Co, Cu and Mn concentrations and negative correlation with Ag. The Sr and Ag concentrations are positively correlated with the amount of CaCO3. The amounts of Co, Cu, Ni and Mn show negative correlations with the calcium carbonate content. Pb and Co are noticeably correlated with Mn.  相似文献   
42.
In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.  相似文献   
43.
Flyrock arising from blasting operations is one of the crucial and complex problems in mining industry and its prediction plays an important role in the minimization of related hazards. In past years, various empirical methods were developed for the prediction of flyrock distance using statistical analysis techniques, which have very low predictive capacity. Artificial intelligence (AI) techniques are now being used as alternate statistical techniques. In this paper, two predictive models were developed by using AI techniques to predict flyrock distance in Sungun copper mine of Iran. One of the models employed artificial neural network (ANN), and another, fuzzy logic. The results showed that both models were useful and efficient whereas the fuzzy model exhibited high performance than ANN model for predicting flyrock distance. The performance of the models showed that the AI is a good tool for minimizing the uncertainties in the blasting operations.  相似文献   
44.
In order to understand the post-depositional history of carbonate rocks of Guri Member (Lower to Middle Miocene), three stratigraphic sections were selected in north Bandar-Abbas in southeast of Iran. Sampling was carried out, analyzed for selective parameters such as oxygen and carbon isotopic compositions (δ18O and δ13C) and interpreted in the present study. We recognized several diagenetic processes including micritization, cementation, neomorphism, compaction, dissolution, silicification, dolomitization, fracturing and vein filling. Some of the diagenetic processes occurred at different conditions, so in order to achieve precise interpretation, samples from different carbonate components such as, micrite, fracture cement, solution pore cement, intergranular cement, and some biotic allochems were analyzed. In this study micrite samples were subdivided into two groups including micro-spary and micrite. They were recognized under Cathodoluminescence microscope. In addition, micrite samples were classified into five groups based on their depositional environments: supratidal, lagoon, coral bar, open sea, and open basin. There were minor changes in stable isotope ratios based on the sedimentary environments, stratigraphy successions, and micro-spary or micrite properties. In this study, similar calcite cements in petrography studies were differentiated by stable isotope data. Those calcite cements have formed in different diagenetic environments such as meteoric and burial cements. Paragenetic sequence of carbonate rocks were interpreted by integration of petrographic and isotopic studies. We have reconstructed diagenetic models of Guri Member into four stages including marine, meteoric, burial, and uplifting.  相似文献   
45.
Brittleness Effect on Rock Fatigue Damage Evolution   总被引:1,自引:0,他引:1  
The damage evolution mechanism of rocks is one of the most important aspects in studying of rock fatigue behavior. Fatigue damage evolution of three rock types (onyx marble, sandstone and soft limestone) with different brittleness were considered in the present study. Intensive experimental tests were conducted on the chosen rock samples and acoustic emission (AE) sensors were used in some of them to monitor the fracturing process. Experimental tests indicated that brittleness strongly influences damage evolution of rocks in the course of static and dynamic loading. AE monitoring revealed that micro-crack density induced by the applied loads during different stages of the failure processes increases as rock brittleness increases. Also, results of fatigue tests on the three rock types indicated that the rock with the most induced micro-cracks during loading cycles has the least fatigue life. Furthermore, the condition of failure surfaces of the studied rocks samples, subjected to dynamic and static loading, were evaluated and it was concluded that the roughness of failure surfaces is influenced by loading types and rock brittleness. Dynamic failure surfaces were rougher than static ones and low brittle rock demonstrate a smoother failure surface compared to high brittle rock.  相似文献   
46.
An alternative method for non-negative estimation of variance components   总被引:1,自引:1,他引:0  
A typical problem of estimation principles of variance and covariance components is that they do not produce positive variances in general. This caveat is due, in particular, to a variety of reasons: (1) a badly chosen set of initial variance components, namely initial value problem (IVP), (2) low redundancy in functional model, (3) an improper stochastic model, and (4) data’s possibility of containing outliers. Accordingly, a lot of effort has been made in order to design non-negative estimates of variance components. However, the desires on non-negative and unbiased estimation can seldom be met simultaneously. Likewise, in order to search for a practical non-negative estimator, one has to give up the condition on unbiasedness, which implies that the estimator will be biased. On the other hand, unlike the variance components, the covariance components can be negative, so the methods for obtaining non-negative estimates of variance components are not applicable. This study presents an alternative method to non-negative estimation of variance components such that non-negativity of the variance components is automatically supported. The idea is based upon the use of the functions whose range is the set of all positive real numbers, namely positive-valued functions (PVFs), for unknown variance components in stochastic model instead of using variance components themselves. Using the PVF could eliminate the effect of IVP on the estimation process. This concept is reparameterized on the restricted maximum likelihood with no effect on the unbiasedness of the scheme. The numerical results show the successful estimation of non-negativity estimation of variance components (as positive values) as well as covariance components (as negative or positive values).  相似文献   
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48.
Currently, methods of extracting spatial information from satellite images are mainly based on visual interpretations and drawing the consequences by human factor, which is both costly and time consuming. A large volume of data collected by satellite sensors, and significant improvement in spatial and spectral resolution of these images require the development of new methods for optimal use of these data in order to produce rapid economic and updating road maps. In this study, a new automatic method is proposed for road extraction by integrating the SVM and Level Set methods. The estimated probability of classification by SVM is used as input in Level Set Method. The average of completeness, correctness, and quality was 84.19, 88.69 and 76.06% respectively indicate high performance of proposed method for road extraction from Google Earth images.  相似文献   
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