جستجوی مقالات مرتبط با کلیدواژه "d modeling" در نشریات گروه "فیزیک"

Dynamic Positron Emission Tomography (PET) imaging has significant potential for extracting kinetic parameters of tracers, particularly the Ki parameter. This study evaluates the use of the Dual Time Point (DTP) technique to generate parametric Ki images from two 3-minute static PET scans. A simulation study was conducted using the XCAT phantom, generating six realistic heterogeneous tumors embedded in lung and liver tissues with various levels of [18F] FDG uptake. Parametric Ki images were generated and evaluated using Patlak analysis and a population-based input function (PBIF). Additionally, TBR and CNR parameters in SUV images and parametric images produced by DTP and full dynamic methods were compared and analyzed. The results showed a significant correlation (> 0.9) between the Ki parameter derived from DTP and full dynamic imaging methods. Moreover, the high TBR parameter in DTP images compared to SUV images (70% for lung tumors, 35% for liver tumors) indicates improved contrast and image quality. Consequently, DTP images can be a suitable alternative to complete dynamic PET and SUV images in clinical settings.

In this article, the physical properties of the surface of the CdS/Si(p) material under the influence of a magnetic field were studied . The dependence of the density of surface states of the p-type Si(p) semiconductor on the magnetic field and temperature has been studied. For the first time, a mathematical model has been developed to determine the temperature dependence of the density of surface states of a semiconductor under the influence of a strong magnetic field. Mathematical modeling of the processes was carried out using experimental values of the continuous energy spectrum of the density of surface states, obtained at various low temperatures and strong magnetic fields, whithin the band gap of silicon. The possibility of calculating discrete energy levels is demonstrated.

In standard gravimetric correction methods, after the raw gravity data sets were corrected for drift, tide, latitude, and free-air effects to obtain free air anomalies, the effect of the mass between the reference surface and ground surface is eliminated in two steps including Bouguer and terrain corrections. But this study removes this effect in one step through the forward modeling method. To do this, two things are necessary for finding more accurate answers. First, how is the underground discretization, and to what extent a network of Digital Terrain Model (DTM) is available? Quad tree mesh accessible in Simulation and Parameter Estimation in Geophysics (SimPEG) is a very accurate and advanced meshing algorithm to discretize subsurface based on our requirements. This meshing system can choose the size of cells in the desired locations. Hence, using this flexible discretization, it is possible to define the smaller cells in borders, near the topographic region, which helps a for more precise answers. Having a dense DTM, the SRTM GeoTiff pictures are downloaded from USGS Earth explorer with 1 arc-second (90 m) resolution (https://doi.org/10.5066/F7PR7TFT), and then height information is extracted from these pictures through GeoToolkit (http://toolkit.geosci.xyz) script. Assuming a flat geoid for our study area, topography is extracted from the SRTM and the pictures are interpolated to estimate the elevation at the gravity observation points. The gravity effect of the model space (the space between the reference surface and topography) is computed via numerical forward modeling assuming a constant density (2.67 gr/cm3). This procedure is done by the Simulation module in SimPEG and is considered as the Bouguer and terrain corrections simultaneously. These corrections are subtracted from the free-air anomalies, which yields the complete Bouguer anomaly. This method is powerful in contrast to other standard methods. In standard methods, Bouguer correction considers Bouguer slab approximation. Therefore, accuracy is lost. Also, in large-scale problems, curvature correction becomes necessary. Also, terrain correction for removing the effects of the mass between the lowlands and heights of the region is inevitable. Terrain correction considers two approximations. First, it uses average height. Hence this procedure has a low precision. Secondly it divides the surrounding area into three zones (near, middle, and far) and computes the effects of middle and far zones with lower precision. Therefore, it decreases the accuracy of the results. The mentioned method is tested on 399 ground gravity data with a grid spacing of about 5 km prepared by the National Cartographical Center of Iran (NCC) in an area of about 200 km in 200 km located in parts of Central Zagros and Central Iran. The results obtained from this one-stage correction method are more accurate and less complicated in doing compared to the results of the usual procedure. Because in this method, we have no simplifying assumptions such as infinite Bouguer slab in Bouguer correction or using relative heights in terrain correction that exist in standard methods.

In this study, the reflective behavior of sloped porous seawalls were investigated experimentally using physical modeling. Regular waves of wide range of heights and periods were used. Tests were carried out for a constant water depth of 0.27m and for different inclinations of seawall (i.e. θ = 45, 60, 75 and 90 ̊). It was found that the parameters of wave steepness, relative water depth, surf similarity parameter and the slope of seawall were influencing in predicting the reflection from the sloped porous seawall. The reflection coefficient (Kr) for sloped seawalls ranged from 0.36–0.77 and for the vertical porous seawall it was 0.59–0.83, whereas for the vertical plane wall, it was almost 1. The reduction in the wave reflection for the sloped seawalls as compared to the vertical porous seawall was about 28%. New empirical equations were developed for estimating the wave reflection coefficients from the proposed seawalls using nonlinear regression analysis. These found were calibrated using SPSS based on the experimental result. The results of this study will be useful in the design of energy dissipating type vertical quay walls in ports, sloped seawalls for shore protection from erosion and sloped caisson breakwaters.

Recently, we generated the evolution equations of the parton distribution functions (PDF) usually used in the hadrons phenomenology using the stochastic modeling of the non-equilibrium statistical mechanics in the momentum space. The evolution equations obtained from stochastic modeling are the same as the Dokshitzer–Gribov–Lipatov–Altarelli–Parisi (DGLAP) evolution equations, but are obtained by a more simplistic mathematical procedure based on the non-equilibrium statistical mechanics and the theory of Markov processes. In this paper, we analytically solve the parton evolution equation for the non-singlet quark distribution function in the small-x (the longitudinal momentum fraction) region through the Kramers-Moyal expansion of the master equation. Finally, we compare the cutoff dependent non-singlet quark distribution function obtained from the analytical solution by considering the strong ordering and the angular ordering constraints with the ordinary non-singlet quark distribution function produced by the MMHT2014 group. In general, we show that our results at the small x and moderate Q2 (the energy scale) are in good agreement with the results of the MMHT2014 group.

Low-induction-number frequency-domain geoelectromagnetic (LIN-GeoFEM) instruments are ground conductivity meters that use a small coil transmitter (Tx) and one coil receiver (Rx). This coil–coil system is designed to propagate alternating electromagnetic fields through the earth at small Tx–Rx separations and low frequency and receive the EM field coupling in the shallow subsurface to provide direct measures of the apparent electrical conductivity. This measured property is a complicated average of spatially distributed localized electrical conductivities in the subsurface. Instruments capable of operating as LIN FEM instruments include the EM38, EM31, and EM34 (Geonics Ltd., Mississauga, ON), the DUALEM instruments series (DUALEM, Inc., Milton, ON), the GEM instrument series (Geophex Ltd., Raleigh, NC) and CMD series (GF Instruments, s.r.o.). The Tx and Rx coils can be oriented relative to each other and the earth's surface. Orientations considered in this study are horizontal coplanar (HCP) (both coils lie flat on the ground) and vertical coplanar (VCP) (coils are upright and coplanar). The range of LIN FEM instruments applications for environmental and hydrologic characterization and monitoring is large and increasing.The LIN-GeoFEM applications are industrially feasible as long as there is a reasonably fast algorithm that is accurate enough to invert the survey data. Furthermore, forward modeling plays a key role in the inversion procedure. The linear integral equation (IE) method is a powerful tool in EM forward modeling for geophysical applications, especially for simple background conductivity structures. The main advantage of the IE method in comparison with the finite difference (FD) and finite element (FE) methods is its fast and accurate simulation of the response for models with compact 2-D or 3-D bodies in a layered background. The main limitation of the IE method is that the background conductivity model must have a simple structure to allow for an efficient Green’s function calculation. Fortunately, the most widely used background models in LIN-GeoFEM explorations are those formed by horizontally homogeneous layers. A main issue is that the EM field integral equation is nonlinear. However, an approximate linear equation is obtained for the electromagnetic induction at low induction numbers using the Born approximation. A 2D forward modeling code for LIN-GeoFEM is developed based on the integral equation (IE) method. Here, a linear relation between model parameters and apparent conductivity values is proposed. The 2D problem is obtained from 3D using numerical integration along the y-axis (strike direction) from minus infinity to infinity. So, the linear approximation is applied to the 2D inversion of LIN measurements. We use a damped minimum length solution using depth weighting to solve this problem iteratively. Thus, we obtain a better estimate of conductivity in a few iterations. Using this 2D linear inversion or imaging technique, we can produce reasonably good results of inverting jointly and individually VCP and HCP for low and moderate conductivity contrasts.To validate the algorithm, we consider two 2D synthetic scenarios and field data acquired on a thick conductive dyke in the Bloemfontein Nature Reserve region in South Africa. The first synthetic scenario consists of one 3 W.m conductive horizontal or vertical prism immersed in a 100 W.m resistive host. In this example, the recovered models from the inversion of the HCP (VMD) and VCP (HMD) data show good results for the vertical and horizontal prism, respectively. The second scenario simulates four 20 W.m conductive vertical and horizontal prisms in a 100 W.m resistive background. The recovered conductivity from the inversion of the VCP data has the weakest results, especially in the case of vertical prisms. In the conductivity section from the inversion of HCP data, the existence of the four anomalous bodies is evident. However, the image obtained from the joint inversion of HCP and VCP data has generated useful information about the true model in all recovered models. The result of jointly inverting VCP and HCP field data confirms the presence of the dyke as a zone of low conductivities.

In this paper, using the non-equilibrium molecular dynamics (NEMD) simulation approach, and the effective medium approximation (EMA) method, we investigate the effect of graphene nanoscale filler, as an enhancer, on the effective thermal conductivity of polyethylene-based nanocomposites. Our results suggest that the thermal conductivity of polyethylene at room temperature was estimated to be nearly 0.21 W/m.K, through using the reactive bond order (AIREBO) interatomic potential. This study shows that by increasing the volume fraction of graphene nanofillers, the effective thermal conductivity of the nanocomposite increases. We also observed that by increasing the volume fraction of graphene from 1% to 3%, the normalized thermal conductivity of nanocomposite increases to nearly 55%..

Regarding climate changes and global warming, it seems that the behavior of climate elements in the future should be predicted and known. Therefore, in this study, using modeling by a set of ARIMA statistical models, models on the time series of the mean annual temperature at Mehrabad station in Tehran during 1951-2015 were fitted to investigate a significant model by trial and error in order to identify the most appropriate model. Since the time series of the observations had a normal distribution, modeling was performed on the time series without applying Box Cox transformation. First, for static and non-static investigations, the time series of annual mean temperature observations was plotted simply in diagrams. In addition, the first and second order regression line equations were used to further ensure the type of time series behavior of the mean annual temperature. The results showed that the time series behavior of temperature at this station is linear. Since the time series behavior was linear, the order d = 1 was determined. Second, the first-order differentiation was performed on the time series. In the third step, the order p and q were determined using autocorrelation and partial autocorrelation of the differentiated values ( ). After investigating the significance of the order of the components of each of the models, the following models were selected as significant models, respectively:1) ARIMA(0,1,12) ARIMA(2,1,0Since the first significant model was observed with suspicion, as a result each of the components (p, d, q) of the above two models were tested up to the 3th order. Finally, these two models were selected as significant models. Also, Akaike information criterion (AIC) was considered to determine the most appropriate model among the above two models. ARIMA model (0,1,1  had the minimum value of AIC compared to the other model. As a result, using this model, the temperature time series at this station was predicted from the end of the period to ¼ of the first time series. Given the concept of uncertainty, which underlies descriptive and inferential statistics, as a result, it seems that uncertainties should be expressed with high statistical certainty. In this regard, we used statistical tests of autocorrelation, Pearson correlation coefficient, standard normal homogeneity, cumulative deviations, milestones, sign on the time series of ARIMA model residues (0,1,1 , and drawing methods for residual normality, residual independence, constant residual variance and portmanteau test to consider further criteria to increase the statistical reliability of the applied model. The results of all statistical tests showed the random residual time series of the model.  These tests showed that the best model for modeling the time series of the mean annual temperature at Mehrabad station, Tehran is ARIMA model (0,1,1 . Since the upper and lower limits of the predicted series as well as the predicted observations show the same behavior of the temperature time series at Mehrabad station, it can be said that the estimation of the predicted numerical values is still appropriate for this model to predict the temperature variable at this station. Finally, the results showed that the mean temperature of the predicted series is likely to be 17.742 ͦ C, and the mean annual temperature will increase by 0.038 ͦ C compared to the previous year.

Because of declining high-grade ore deposits and increasing demands for metal resources, exploration of low-grade metal deposits, such as porphyries, have become feasible. Besides, humankind has spent most of the shallow metal ore deposits, and new prospecting projects focus on deeper deposits. Therefore, geophysical methods have gained more attention due to their ability to determine buried ore bodies' physical properties. Hence, most countries, including Iran, make significant investments in the geophysical exploration of deep porphyry deposits. According to widely accepted Lowell and Guilbert's model for porphyry copper deposits, the ore-bearing zones mainly concentrate at the edge of the potassic alteration zone. Pyrite, a highly conductive and chargeable metallic mineral, is a significant attribute in the potassic alteration. The model also states that the high susceptible magnetite-bearing rocks mainly occur at the bottom of the pyrite shell and the ore body. Due to the occurrence and presence of susceptible and conductive metallic minerals such as magnetite and pyrite in the potassic zone near to the ore body in the copper and gold porphyry deposits, the use of magnetometry, resistivity, and inducing polarization methods give reliable information about the location, depth, and shape of the deposits. For instance, in this research, we focus on the magnetic and IP/Res data in the southern Dalli porphyry deposit, with promising Cu-Au indices, which is located at Euromieh-Dokhtar ore-bearing zone Markazi Province. First, we applied standard processing techniques to remove the aliasing and regional effect in the magnetic data. Then, using the analytic signal technique, we showed the concentration of the magnetic sources over the study area. We also applied the power spectrum and Euler deconvolution techniques to the magnetic data and estimated the magnetic sources' depths. The estimated depth from the power spectrum is between the estimated depth from Euler deconvolution for possible sources with step and pillar shapes. Next, we used the average estimated depth from each of the depth estimation techniques in a three-dimensional magnetic data inversion as the depth of the sources in depth weighting. Also, we studied the inversion results via combining the cross-section of the magnetic susceptibility model along the boreholes and the lithology and geochemical information from core samples analysis. The results indicate that the higher grades for gold and copper occur at the edge of the magnetic sources and possible magnetite mineralization zones. The inversion results using the depth weighting with the depth extracted from the power spectrum show the best correlation and spatial relation with the geochemical data. Besides the magnetic data inversion, applying Oldenburg and Li algorithms for two-dimensional inverse modeling, we extracted the underground bodies' resistivity and chargeability model along with a IP/Res profile in the study area. The resulting chargeability models show a significant relationship with the presence of gold and copper mineralization. We also compared the resulting two-dimensional resistivity and changeability models with their corresponding magnetic susceptibility at the cross-sections along with the IP/Res. The comparison shows that the possible mineralization zones coincide with larger magnetic susceptibility values, high chargeability and low resistivity. The results show good accordance with Lowell and Guilbert's model. Also, highly susceptible rock in the shallower depth indicates that the erosion process has destroyed most possible orebody.

In coastal hydrodynamics, shore structures play an important role in changes in coastal morphology and natural current conditions in the region. Generally, the construction of structures such as piers leads to a change in the pattern of coastal currents as well as other related parameters such as sedimentation rate, turbidity, and salinity. In the present study, using field measurements and model simulation of coastal currents, the effect of Nakhle Nakhoda pier construction on the coastal flow pattern is investigated. Field velocity measurements are carried out by ADCP over a 30-day period in two depth layers. Turbidity and salinity are also collected using CTD. All the data are statistically analyzed. The results show that different parameters are affected by the change of coastal current, and the greatest effect is on turbidity. The ROMS model is used to simulate the area in two modes, with and without the pier. According to the results, the construction of this structure has caused a change in the coastline and an increase of more than 40×104 square meters to the coastal area.

An accurate knowledge and understanding of wind-driven wave characteristics is one of basic requirements in marine activities and environmental studies. The present research deals modeling wind-driven wave with irregular triangular computational mesh grid in the Caspian Sea. Then, the wind-driven wave field of the Caspian Sea has been analyzed in the 2000 - 2020 period. For this purpose, the SWAN numerical model with irregular computational mesh grid was used to simulate wind-driven wave characteristics using Era-Interim reanalysis data with accuracy of 0.125 degree. The results of the modeling were validated with the measurements data in Nowshahr, Amirabad and Anzali buoys position. To increase the forecast accuracy, the model with different AGROWTH and the Whitecapping coefficients was evaluated in the Caspian Sea. Then the monthly average sea surface wind and the significant wave height field extracted for a period of 20 years. Also, dominant wind-driven wave patterns were extracted using the Empirical Orthogonal Functions (EOF) analysis method in the study area. The results show that three first main components of the EOF analysis are respectively about 70%, 20% and 5% of the total anomaly pattern of the wind-driven waves in the Caspian Sea. Therefore we can interpret separately the effect of the local waves on the general wind-driven wave pattern of the Caspian Sea.

The Moho discontinuity is a boundary between the crust and upper mantle that reveals the difference between them with changes in seismic velocity, density, chemical structure, and constituents. Estimating the Moho depth and studying its lateral changes is one of the important goals of geophysical studies. The current study aims to estimate the depth and topography of the Moho discontinuity in the southwestern part of the Baltic Sea, including parts of the central European system, the Trans-European Suture Zone, Caledonian Crustal Suture, and the Ringkobing-Fyn High. This area has been one of the most attractive regions for Geoscientists in the last decades due to its complicated geological structures caused by different tectonic events. For this purpose, a three-dimensional model of the crustal structures based on gravity data forward modeling in the study area has been presented. Previous seismic / non-seismic results have been used to constrain the model and reduce its degree of freedom. This model includes sedimentary sequences, crustal thickness, Moho topography, and high-velocity lower crust expansion in the region and shows the tectonic structures of the study area. This study used a combination of marine, land, and EGM2008 gravity data and modeled them with IGMAS+, Interactive Gravity and Magnetic Application System. The interactive modeling program allows the user to change the geometry as well as the density and susceptibility of the primary model and observe results quickly during the processing. In the software, the model structure could be be more user friendly by eliminating additional details and dividing the whole model into vertical sections. Our primary model consists of three main layers of sediments, crust and upper mantle. The sedimentary layer is divided into two major parts, pre-Permian and post-Carboniferous. Also, the crustal layer is divided into the upper crust and the high-density lower crust. Besides, the upper crust is composed of the upper crust of the Baltica and the upper crust of Avalonia. The last layer of the model is a part of the upper mantle. The model space consists of 16 vertical planes stretching 385 kilometers east-west with an equal distance of 15 kilometers, covering the entire study area. The initial model was developed based on seismic sections and previous models, and it has been improved using interactive forward modeling of gravity data. The result shows a good agreement between the measured and modeled Bouguer anomaly, and the Root Mean Square Error of the model is 1.12 mGal. The model correlates clearly with major tectonic units. It indicates that the Caledonian collision resulted in the amalgamation of Baltica and Avalonia is the most prominent tectonic event in the area, and the Caledonian crustal suture between them is interpreted from changes in physical parameters at crustal levels. There is a relatively thick crystalline crust in the area, and the depth of Moho discontinuity varies from 26 to 42 km. The results also indicate that the transition from the Paleozoic crust of the Central European Basin to the Precambrian crust of the Eastern European Craton occurs within the Tornquist Zone.

A three dimensional numerical model namely ROMS (Regional Ocean Modeling System) and observational data are used to study the thermohaline front of Persian Gulf Outflow in the Oman Sea. The simulation results show the formation of a thermohaline front at 80m depth in the direction of the north-east-southwest at the mouth of the Oman Sea. The seasonal thermohaline front variability was also identified, during winter a heat and salty tongue stretches from the Strait of Hormuz to the continental shelf along the south Oman coast. During summer, it shows a current departing from the coast moving forward to the middle of the Oman Sea. Thermohaline front is observed throughout the year, in summer as unified and patchy in winter. Intrusion of warm and salty water of Persian Gulf into the Gulf of Oman displays a local increase in salinity in the middle layers in 150-450m and 100-400m depths in winter and summer respectively which expresses two boundaries in the upper and lower layers. Diffusive convection and salt fingering can be seen in both the upper and lower boundaries respectively. The complex ocean flow patterns are result of monsoons in the Oman sea area. During the winter monsoon, a single cyclonic gyre is often observed near 58◦E and during the Southwest monsoon in summer, a dipolar eddy near Ras al Hamra and an anticyclone’s gyre in 25°N are detected.

The precise and timely manner modeling of received photon counts from gamma-ray sources has an important role in providing afore information for Airborne Gamma Ray Spectrometry (AGRS). In this manuscript, the Auto-Regressive Integrated Moving Average (ARIMA) model has been used to model AGRS. The proposed method provides gamma source and environmental disturbances ARIMA model, using known radioactive sources, to arrange the afore information for AGRS process experts to analyze the spectrometry data. The model extraction process and training will be done offline using different sizes and types of radioactive sources. The extracted models then being validated by evaluation functions to determine the type and amount of radionuclides during online AGRS. In order to evaluate the implemented modeling, the proposed ARIMA method is compared with other process modeling methods, including the Auto Regressive Moving Average ARMA in three bias, median absolute deviation (MAD) and the mean square error (MSE) criteria. The results show that the proposed method models the received photon counts much more accurate than other common methods.

Resistivity and induced polarization methods are used in exploration of porphyry metals for years. The resistivity method is used in the study of horizontal and vertical discontinuities in the electrical properties of the ground. The induced polarization method makes use of the capacitive action of the subsurface to locate zones where conductive minerals are disseminated within their host rocks. The simplicity of the equipment، the lower cost of the survey compared to the other methods and the abundance of interpretation methods make it a popular method. There are many methods to interpret resistivity and induced polarization data. Inversion method is one of the most popular methods. This method was reported as early as the 1930s. Visual and analytical methods are used for the interpretations which are used for simple structure such as faults. These methods require a certain degree of symmetry and are suitable only for simple geological situations. Complex resistivity distributions cannot be solved by analytical methods and must numerical techniques be used. But these data alone cannot determine the location of anomalies precisely. One of the main concerns of interpreters is the selection of optimum drilling points by the results of surveys. The selection of optimum drilling point have an important impact on the reduction the cost and risk، The selection of these points can be done by integration of geoelectrical and structural data. By the progress of the computer science، many methods for processing of geophysical data were also developed. These methods include fuzzy، neural networks and genetic algorithms methods. Fuzzy method is based on following steps: 1-layer fuzzy information، 2- fuzzy inference، 3- deterministic output. Fuzzy layers of information are done by membership function، and there are different kinds of membership functions. In this study resistivity and induced polarization data have been collected using dipole-dipole array in mining index of Hamyj mine located in Birjand. Hamyj mine index that is the result of remote sensing and economic geology surveys show promising mineralization in this mine. This area comprises of volcanic rocks as andesit، dasite، volcanic breccia، metamorphic tuff. The dasit extensions in the study area are more frequent. For in detail study and modeling of the mineralization the geoelctrical study with Electrod spacing of 20m has been used. Then inversion of geoelecrtical data for a profile based on Gaussian- Newton and Newton’s methods were carried out. In this study، the models have been integrated based on knowledge-driven fuzzy logic method in a GIS environment. The best profile was chosen based on the Spriman correlation. Because the resistivity and induced polarization have negative correlation، so the profile 3 was selected as the best profile by highest negative correlation. Results of inverse modeling show that in this profile the resistivity of the left and right side of this profile are different. This difference in resistivity represents the chalcopyrite in the study area. The boundary of the difference is an attribute to a fault that is located 230m from the left side. Also induced polarization data have shown a high value of chalcopyright. In fact the fault existence in the mentioned location was approved by geological surveys. The effect of layers information of resistivity and induced polarization a decision، fuzzy functions were selected for them. Also a large membership function was used for the induced polarization. Also، small membership function was used for resistivity data. For faults in this study a 5 meters distance as buffer zone was applied. The fuzzy gamma operator was also used. This operator is a combination of multiplication and addition operator. The value of fuzzy gamma operator was selected 0. 85 for the integration of layers information. The result of the fuzzy map، was converted to binary map and on this map، decision maker could easily select the optimum area. Finally، based on the results of the fuzzy modeling، the best point for drilling was proposed. Using this type of integration in order to determine the best drilling points in for porphyry copper exploration، appears to be a trusty method. Based on the fuzzy modeling for the study area the best drilling point was chosen near the fault in the study area. The results show that the optimum exploration borehole location is the point that is located at a distance 240m from the left side of the profile. Also in this study the maximum depth of drilling was calculated 50m. The applied fuzzy method in this surveyed profile with 400m length and proposed a 60m length as a promising mineralization area with high confidence. Also، in this method expert viewpoint could be applied in the procedure of integration. This method has high flexibility in integration of also information layers and could simultaneously use several information layers. This technique has simple mathematical relationship. By the results of this study this method can be used for other geophysical data.