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1.

The use of spontaneous potential (SP) anomalies is well known in the geophysical literatures because of its effectiveness and significance in solving many complex problems in mineral exploration. The inverse problem of self-potential data interpretation is generally ill-posed and nonlinear. Methods based on derivative analysis usually fail to reach the optimal solution (global minimum) and trapped in a local minimum. A new simple heuristic solution to SP anomalies due to 2D inclined sheet of infinite horizontal length is investigated in this study to solve these problems. This method is based on utilizing whale optimization algorithm (WOA) as an effective heuristic solution to the inverse problem of self-potential field due to a 2D inclined sheet. In this context, the WOA was applied first to synthetic example, where the effect of the random noise was examined and the method revealed good results using proper MATLAB code. The technique was then applied on several real field profiles from different localities aiming to determine the parameters of mineralized zones or the associated shear zones. The inversion parameters revealed that WOA detected accurately the unknown parameters and showed a good validation when compared with the published inversion methods.

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In this paper, we evaluate the predictive performance of an adaptive neuro-fuzzy inference system (ANFIS) using six different membership functions (MF). In combination with a geographic information system (GIS), ANFIS was used for land subsidence susceptibility mapping (LSSM) in the Marand plain, northwest Iran. This area is prone to droughts and low groundwater levels and subsequent land subsidence damages. Therefore, a land subsidence inventory database was created from an extensive field survey. Areas of land subsidence or areas showing initial signs of subsidence were used for training, while one-third of inventory database were reserved for testing and validation. The inventory database randomly divided into three different folds of the same size. One of the folds was chosen for testing and validation. Other two folds was used for training. This process repeated for every fold in the inventory dataset. Thereafter, land subsidence related factors, such as hydrological and topographical factors, were prepared as GIS layers. Areas susceptible to land subsidence were then analyzed using the ANFIS approach, and land subsidence susceptibility maps were created, whereby six different MFs were applied. Lastly, the results derived from each MF were validated with those areas of the land subsidence database that were not used for training. Receiver operating characteristics (ROC) curves were drawn for all LSSMs, and the areas under the curves were calculated. The ROC analyses for the six LSSMs yielded very high prediction values for two out of the six methods, namely the difference of DsigMF (0.958) and GaussMF (0.951). The integration of ANFIS and GIS generally led to high LSSM prediction accuracies. This study demonstrated that the choice of training dataset and the MF significantly affects the results.  相似文献   
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Water Resources - This paper presents the results of the groundwater quality assessment, on the Serbian Danube, Sava and Morava River water area, for irrigation purposes. The analysis was done at...  相似文献   
4.
The Sinai Peninsula has attracted the attention of many geological and geophysical studies as it is influenced and bounded by major tectonic events. Those are (1) the Mesozoic to Early Cenozoic tectonically active opening of the Tethys, (2) the Late Cretaceous to Early Tertiary (Laramide) Syrian arc system, due to closing of the Tethys (3) the Oligo-Miocene Gulf of Suez rifted basin, and (4) the Late Miocene to Recent transform Dead Sea–Gulf of Aqaba rift. Additionally, the shear zones inside Sinai such as the Ragabet El-Naam and Minsherah-Abu Kandu Shear Zones. Each of these major tectonic events has affected dramatically the structure evolution of the northern Sinai area. The present paper estimates the 3D density contrast model using the gravity data of northern Sinai. The estimated 3D density contrast model elucidated the peculiarities of the main structural elements in the region. The estimated 3D density contrast model showed the high and low gravity anomalies that form the main mountains and main valleys in northern Sinai. The estimated low density zones are in agreement with the inferred faults resulting from the first horizontal derivative. Comparing the 3D model with the tectonic history of the region and the results of the first horizontal derivative and least square separation increased the reliability of the model.  相似文献   
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An exploration program aided by field investigation, exploration drilling, detailed sampling, lithological and petrological studies, geochemical investigation, and resource calculation leads to the discovery of a potential phosphate resource in northeast Jordan close to the international border with Saudi Arabia and Iraq. The studied phosphate is of the Middle Eocene age that belongs to the Wadi Shallala Formation. It is equivalent to the phosphate deposits recorded in the lower part of the Umm Wual Formation in the Turayf region of Saudi Arabia and the Eocene Ratga Formation in the Ethna phosphate deposit west of Iraq. The phosphorites in the region are broadly similar in mineralogical composition and geochemical affinities. X-ray diffraction indicates the presence of francolite with variable amounts of calcite and quartz. Most samples consist of phosphate clasts embedded in carbonate and silica matrix and cement. P2O5 content is up to 32.3 % with an average equal to 18.6 %. The impurity is caused by the presence of variable amounts of SiO2 and CaO. The F% and F/P2O5 ratio in studied phosphates is lower compared with that in phosphates from Jordan and Saudi Arabia. The geological and geochemical results were integrated for resource estimation. Three high-grade phosphate layers with ≥23 % P2O5 were considered in the calculations. The phosphate resource is classified as an inferred resource. The total volume of the resource is about 649 million tons. The average P2O5 content is 24.57, and the stripping ratio is 1:5.8.  相似文献   
10.
This study applied the time series analysis approach to model and predict univariate dissolved oxygen and temperature time series for four water quality assessment stations at Stillaguamish River located in the state of Washington. The order series method was applied to fulfill the normality assumption for modeling the univariate time series. Then, the AR(I)MA models were applied to study the stationary and nonstationary time series, the Auto-Regressive Fractionally Integrated Moving Average model was applied to study the time series with long memory. The results showed there existed three different structures for the univariate water quality time series at Stillaguamish River watershed. The identified time series model for each univariate water quality time series was found to be capable of predicting future values with reasonable accuracy. Overall, the time series modeling approach may be an efficient tool in assessment of the water quality in the river system.  相似文献   
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