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71.
In the equatorial plasmasphere, plasma waves are frequently observed. To improve our understanding of the mechanism generating plasma waves from instabilities, a comparison of observations, linear growth-rate calculations, and simulation results is presented. To start the numerical experiments from realistic initial plasma conditions, we use the initial parameters inferred from observational data obtained around the plasma-wave generation region by the Akebono satellite. The linear growth rates of waves of different modes are calculated under resonance conditions, and compared with simulation results and observations. By employing numerical experiments by a particle code, we first show that upper hybrid-, Z-, and whistler-mode waves are excited through instabilities driven by a ring-type velocity distribution. The simulation results suggest a possibility that energetic electrons with energies of some tens of keV confined around the geomagnetic equator are responsible for the observed enhancements of Z- and whistler-mode waves. While the comparison between linear growth-rate calculations and observations shows the different tendency of wave amplitude of Z-mode and whistler-mode waves, the wave amplitude of these wave modes in the simulation results is consistent with the observation. 相似文献
72.
Gholam Abbas Fallah-Ghalhary Majid Habibi-Nokhandan Mohammad Mousavi-Baygi Javad Khoshhal Akbar Shaemi Barzoki 《Theoretical and Applied Climatology》2010,101(1-2):217-233
This paper aims to study the relationship between large-scale synoptic patterns and rainfall in Khorasan Razavi Province. The adaptive neuro-fuzzy inference system (ANFIS) was used in this study to predict rainfall in the period between April and June in Khorasan Razavi Province. We first analyzed the relationship between average regional rainfall and the changes in synoptic patterns including sea-level pressure, sea-level pressure difference, sea-level temperature, temperature difference between sea level and the 1,000-hPa level, the temperature of the 700-hPa level, the thickness between the 500- and 1,000-hPa levels, the relative humidity at the 300-hPa level, and precipitable water content. We have examined the effect of synoptic patterns in these regions on the rainfall in the northeast region of Iran. Then, the ANFIS in the period 1970–1997 has been taught. Finally, we forecast the rainfall for the period 1998–2007. The results show that the ANFIS can predict the rainfall with reasonable accuracy. 相似文献
73.
Saeid Sadeghian Mohammad Javad Valadan Zoej Mahmoud Reza Delavar Ahmad Abootalebi 《International Journal of Applied Earth Observation and Geoinformation》2001,3(4):366
The huge capability of high resolution satellite imageries (HRSI), that includes spatial, spectral, temporal and radiometric resolutions as well as stereoscopic vision introduces them as a powerful new source for the Photogrammetry, Remote Sensing and GIS communities. High resolution data increases the need for higher accuracy of data modeling. The satellite orbit, position, attitude angles and interior orientation parameters have to be adjusted in the geometrical model to achieve optimal accuracy with the use of a minimum number of Ground Control Points (GCPs). But most high resolution satellite vendors do not intend to publish their sensor models and ephemeris data. There is consequently a need for a range of alternative, practical approaches for extracting accurate 2D and 3D terrain information from HRSI. The flexibility and good accuracy of the alternative models demonstrated with KFA-1000 and the well-known SPOT level 1A images. A block of eight KFA-1000 space photos in two strips with 60% longitudinal overlap and 15% lateral sidelap and SPOT image with rational function, DLT, 2D projective, polynomials, affine, conformal, multiquadric and finite element methods were used in the test. The test areas cover parts of South and West of Iran. Considering the quality of GCPs, the best result was found with the DLT method with a RMSE of 8.44 m for the KFA-1000 space photos. 相似文献
74.
The lognormal distribution is widely used to represent the distribution of deposit or reserve size of oil and gas fields. The purpose of this paper has been to investigate the potential usefulness of the loghyperbolic distribution as an alternative to the lognormal distribution. This hypothesis is tested using a set of data from the Denver basin. The results indicate that the loghyperbolic distribution shows a better fit to the empirical data than the lognormal distribution. 相似文献
75.
James Hollingsworth James Jackson Richard Walker Mohammad Reza Gheitanchi Mohammad Javad Bolourchi 《Geophysical Journal International》2006,166(3):1161-1177
The Kopeh Dagh is a linear mountain range separating the shortening in Iran from the stable, flat Turkmenistan platform. In its central part is an array of active right-lateral strike-slip faults that obliquely cut the range and produce offsets of several kilometres in the geomorphology and geological structure. They are responsible for major destructive earthquakes in the 19th and 20th centuries and represent an important seismic hazard for this now-populous region of NE Iran. These strike-slip faults all end in thrusts, revealed by the uplift and incision of Late Quaternary river terraces, and do not continue beyond the Atrak river valley, which forms the southern margin of the Kopeh Dagh. The cumulative offset on these strike-slip faults, and their associated rotation about vertical axes, can account for ∼60 km of N–S shortening. This value is similar to estimates of the Late Quaternary N–S right-lateral shear between central Iran and Afghanistan, which must be accommodated in NE Iran. The strike-slip faults also require ∼30 km of along-strike extension of the Kopeh Dagh, which is taken up by the westward component of motion between the South Caspian Basin and both Eurasia and Central Iran. It is probable that these motions occurred over the last ∼10 Ma. 相似文献
76.
Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine 总被引：1，自引：1，他引：0
Saeid?Mehdizadeh Javad?BehmaneshEmail author Keivan?Khalili 《Theoretical and Applied Climatology》2018,133(3-4):911-924
Soil temperature (T s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T s. For this aim, the monthly mean data of the T s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T min, T max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R s, R n, R a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u 2); and water vapor pressure (Vp) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R 2) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T max, T min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R 2 = 0.995) and for RH, V p, P, and u 2 inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R 2 = 0.996), respectively. 相似文献
77.
Javad Abolverdi Ghasem Ferdosifar Davar Khalili Ali Akbar Kamgar-Haghighi Mohammad Abdolahipour Haghighi 《Meteorology and Atmospheric Physics》2014,126(3-4):177-192
Trends in air temperature and precipitation data are investigated for linkages to global warming and climate change. After checking for serial correlation with trend-free pre-whitening procedure, the Mann–Kendall test is used to detect monotonic trends and the Mann–Whitney test is used for trend step change. The case study is Maharlo watershed, Southwestern Iran, representing a semi-arid environment. Data are for the 1951–2011 period, from four temperature sites and seven precipitation sites. A homogeneity test investigates regional similarity of the time series data. The results include mean annual, mean annual maximum and minimum and seasonal analysis of air temperature and precipitation data. Mean annual temperature results indicate an increasing trend, while a non-significant trend in precipitation is observed in all the stations. Furthermore, significant phase change was detected in mean annual air temperature trend of Shiraz station in 1977, indicating decreasing trend during 1951–1976 and increasing trend during 1977–2011. The annual precipitation analysis for Shiraz shows a non-significant decrease during 1951–1976 and 1977–2011. The result of homogeneity test reveals that the studied stations form one homogeneous region. While air temperature trends appear as regional linkage to global warming/global climate change, more definite outcome requires analysis of longer time series data on precipitation and air temperature. 相似文献
78.
79.
Evaluating Boolean,AHP and WLC methods for the selection of waste landfill sites using GIS and satellite images 总被引：2，自引：2，他引：0
Himan Shahabi Soroush Keihanfard Baharin Bin Ahmad Mohammad Javad Taheri Amiri 《Environmental Earth Sciences》2014,71(9):4221-4233
The city of Saqqez has a population of 140,000 people, making it one of the largest cities in Iran. Population growth, consumerism, and change in eating habits, such as the increased use of packaged products, is causing the accumulation of waste in this city to increase. In this study, the selection of a waste landfill site for Saqqez focused on 13 layers of geography information that was used by the IDRISI and Arc GIS software. Different models of the analytic multi-criteria decision-making process, such as an analytical hierarchy process (AHP), weighted linear combination (WLC), and Boolean logic, were used to manage layers to establish specific databases for urban waste landfills. Satellite images (Landsat ETM+ and SPOT 5), proposed sites and a land use map of the study area were also used. The results of this study indicated that two methods (AHP and WLC) in the early stages had better decision-making powers for locating landfill sites when compared to Boolean logic. Overlapping and compounding the similarities between these models in Arc GIS software, a 74-ha site was found. This site will be able to accept 130 tons of waste per day for the next 20 years. 相似文献
80.
Prediction of longitudinal dispersion coefficient in natural rivers using a cluster-based Bayesian network 总被引：1，自引：0，他引：1
Mohamad Javad Alizadeh Hosein Shahheydari Mohammad Reza Kavianpour Hamid Shamloo Reza Barati 《Environmental Earth Sciences》2017,76(2):86
The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed. However, the existing predictive techniques for this purpose exhibit great amounts of uncertainty. The main objective of this study is to present a more accurate model for predicting longitudinal dispersion coefficient in natural rivers and streams. Bayesian network (BN) approach was considered in the modeling procedure. Two forms of input variables including dimensional and dimensionless parameters were examined to find the best model structure. In order to increase the performance of the model, the clustering method as a preprocessing data technique was applied to categorize the data in separate groups with similar characteristics. An expansive data set consisting of 149 field measurements was used for training and testing steps of the developed models. Three performance evaluation criteria were adopted for comparison of the results of the different models. Comparison of the present results with the artificial neural network (ANN) model and also well-known existing equations showed the efficiency of the present model. The performance of dimensionless BN model 30% is more than dimensional ones in terms of the root mean square error. The accuracy criterion was increased from 70 to 83% by performing clustering analysis on the BN model. The BN-cluster model 43% is more accurate than ANN model in terms of the accuracy criterion. The results indicate that the BN-cluster model give 16% better results than the best available considered model in terms of the accuracy criterion. The developed model provides a suitable approach for predicting pollutant transport in natural rivers. 相似文献