Search results for: M. Sedghi
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7

Search results for: M. Sedghi

7 Experimental Study of Flag Flutter in Uniform Flow

Authors: A. Sadeghi, M. Sedghi, M. R. Emami Azadi, R. Gharraei Khosroshahi

Abstract:

Flags are objects with very low bending stiffness and under wind forces start to vibrate and finally to flutter. Even in lower velocities of wind their flutter can be seen. In this research physical property of fabric is determined by performing tensile tests. Then with performing laboratory experiments in wind tunnel, determination of initial flapping speed and also study of displacement amplitude at leech and calculation of their frequency would be targeted. Laboratory tests are performed in a wind tunnel and with different velocities of wind flow for specimens with different dimensions. The results show that extension of specimens' width increase flutter initiation velocity and increase of specimen length decreases it. Also by increasing wind velocity displacement amplitude at leech of specimens are decreased. This displacement has a straight relation with specimens' length and width.

Keywords: flag, flutter, wind velocity, flutter amplitudes, wind tunnel

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6 Time Series Modelling and Prediction of River Runoff: Case Study of Karkheh River, Iran

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R2) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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5 Determination of the Best Fit Probability Distribution for Annual Rainfall in Karkheh River at Iran

Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best-fit probability distribution of annual rainfall based on 50 years sample (1966-2015) in the Karkheh river basin at Iran using six probability distributions: Normal, 2-Parameter Log Normal, 3-Parameter Log Normal, Pearson Type 3, Log Pearson Type 3 and Gumbel distribution. The best fit probability distribution was selected using Stormwater Management and Design Aid (SMADA) software and based on the Residual Sum of Squares (R.S.S) between observed and estimated values Based on the R.S.S values of fit tests, the Log Pearson Type 3 and then Pearson Type 3 distributions were found to be the best-fit probability distribution at the Jelogir Majin and Pole Zal rainfall gauging station. The annual values of expected rainfall were calculated using the best fit probability distributions and can be used by hydrologists and design engineers in future research at studied region and other region in the world.

Keywords: Log Pearson Type 3, SMADA, rainfall, Karkheh River

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4 Evaluation of Best-Fit Probability Distribution for Prediction of Extreme Hydrologic Phenomena

Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

The probability distributions are the best method for forecasting of extreme hydrologic phenomena such as rainfall and flood flows. In this research, in order to determine suitable probability distribution for estimating of annual extreme rainfall and flood flows (discharge) series with different return periods, precipitation with 40 and discharge with 58 years time period had been collected from Karkheh River at Iran. After homogeneity and adequacy tests, data have been analyzed by Stormwater Management and Design Aid (SMADA) software and residual sum of squares (R.S.S). The best probability distribution was Log Pearson Type III with R.S.S value (145.91) and value (13.67) for peak discharge and Log Pearson Type III with R.S.S values (141.08) and (8.95) for maximum discharge in Jelogir Majin and Pole Zal stations, respectively. The best distribution for maximum precipitation in Jelogir Majin and Pole Zal stations was Log Pearson Type III distribution with R.S.S values (1.74&1.90) and then Pearson Type III distribution with R.S.S values (1.53&1.69). Overall, the Log Pearson Type III distributions are acceptable distribution types for representing statistics of extreme hydrologic phenomena in Karkheh River at Iran with the Pearson Type III distribution as a potential alternative.

Keywords: Karkheh River, Log Pearson Type III, probability distribution, residual sum of squares

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3 Application of Stochastic Models to Annual Extreme Streamflow Data

Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

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2 Flood Predicting in Karkheh River Basin Using Stochastic ARIMA Model

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R2).

Keywords: time series modelling, stochastic processes, ARIMA model, Karkheh river

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1 Investigating the Effect of Brand Equity on Competitive Advantage in the Banking Industry

Authors: Rohollah Asadian Kohestani, Nazanin Sedghi

Abstract:

As the number of banks and financial institutions working in Iran has been significantly increased, the attracting and retaining customers and encouraging them to continually use the modern banking services have been important and vital issues. Therefore, there would be a serious competition without a deep perception of consumers and fitness of banking services with their needs in the current economic conditions of Iran. It should be noted that concepts such as 'brand equity' is defined based on the view of consumers; however, it is also focused by shareholders, competitors and other beneficiaries of a firm in addition to bank and its consumers. This study examines the impact of brand equity on the competitive advantage in the banking industry as intensive competition between brands of different banks leads to pay more attention to the brands. This research is based on the Aaker’s model examining the impact of four dimensions of brand equity on the competitive advantage of private banks in Behshahr city. Moreover, conducting an applied research and data analysis has been carried out by a descriptive method. Data collection was done using literature review and questionnaire. A 'simple random' methodology was selected for sampling staff of banks while sampling methodology to select consumers of banks was the distribution of questionnaire between staff and consumers of five private banks including Tejarat, Mellat, Refah K., Ghavamin and, Tose’e Ta’avon banks. Results show that there is a significant relationship between brand equity and their competitive advantage. In this research, software of SPSS 16 and LISREL 8.5, as well as different methods of descriptive inferential statistics for analyzing data and test hypotheses, were employed.

Keywords: brand awareness, brand loyalty, brand equity, competitive advantage

Procedia PDF Downloads 105