Journal of Artificial Intelligence in Electrical Engineering
Volume:3 Issue: 12, Winter 2015

Due to increasing expansion of energy consumption and also the decrease and tendency towards ending fossil energy reserves، the current energy cycle needs to use alternative energy specially wind energy، because it’s considerably cheaper than other recycling sources. The present research investigates suitable possibility of exploiting wind energy to create wind power station in Soltanieh zone of Zanajn province by considering technical cases. Some researches have been carried out on possibility assessment، measurement and comparison of power density. In technical possibility investigation، several turbines were investigated to calculate obtainable annual energy capacity coefficient of each turbine. Then these were compared to select the best type of turbine. According to the results، wind turbine owned by Vestas Company، model V100، rated power of 1800 kW and capacity coefficient of 33. 1% was selected as the best turbine.

Nowadays, Robots account for most part of our lives in such a way that it is impossible for us to do many of affairs without them. Increasingly, the application of robots is developing fast and their functions become more sensitive and complex. One of the important requirements of Robot use is a reliable software operation. For enhancement of reliability, it is a necessity to design the fault tolerance system. In this paper, we will present a genetic algorithm and learning automata with high reliability to evaluate the software designed into the robot against soft-error with minimum performance over-head. This method relies on experiment; hence, we use the program sets as criteria in evaluation stages. Indeed, we have used the error injection method in the execution of experimental processes. Relevant data, regarding program execution behavior were collected and then analyzed. To evaluate the behavior of program, errors entered using the simple scalar simulation software.

A Back Propagation Artificial Neural Network (BPANN) is a well-known learning algorithm predicated on a gradient descent method that minimizes the square error involving the network output and the goal of output values. In this study, 261 GPS/Leveling and 8869 gravity intensity values of Iran were selected, then the geoid with three methods “ellipsoidal stokes integral”, “BPANN”, and “collocation” were evaluated. Finally obtained results were compared and best the method was introduced. In Iran, the consequences showed that “BPANN” has been superior than other methods. Root Mean Square Error of this algorithm was less than ±0.292 m. Therefore, we concluded that BPANN can be used for geoid determination as an excellent alternative to the classic methods.

This paper expands a model different from existing models to analyze the cost and benefit of a reinforced concrete solar chimney power plant (RCSCPP) built in the desert regions of Iran. Based on the model and some assumptions for values of parameters, this paper calculates total net present value (TNPV) and the minimum electricity price in each phase by dividing the whole service period into four phases. The results showed that the minimum electricity price in the first phase is higher than the current market price of electricity, but the minimum prices in the other phases are far less than the current market price. The analysis indicated that huge advantages of the RCSCPP over coal-fired power plants could be embodied in phases 2–4. In addition, the sensitivity analysis performed in this paper discovered that TNPV is very sensitive to changes in the solar electricity price and inflation rate, but responds only slightly to changes in carbon credits price, income tax rate and interest rate of loans. Our analysis predicts that RCSCPPs have very good application prospect.

This study on the design of PID controllers for flexible single-arm robot system optimization PSO method is focused so that the coefficients of the PID controller are reduced. In this study, PID controller and PSO algorithm have been described and then by using MATLAB, PID control was simulated. Then by PSO algorithm, attempts to reduce the PID coefficients are given by simulation. Finally PID coefficients'' values were compared with and without the PSO algorithm. The results showed that by using the number of birds and birds number steps, both equal to 30 (the sixth), the lowest values of the coefficients, are 0.741, 0.1491and 0, respectively.

In this article, the effect of cells'' radius on the behavior of wavelength switching optical filter and the effect of the radius of the optical filters'' key characteristics such as wavelength resonance on an optical filter based on photonic crystals, have been investigated. Currently, the most common applied mechanism for designing optical filter based on photonic crystals is using two mechanisms such as (a) The resonant cavities and (b) Ring resonators. The applied mechanism in optical filter used in this article is the resonant cavities. In this filter, filtering act is operated by using cavity located between output Waveguide and input waveguide and it has been used to design filter at the first extracted band structure and we have applied forbidden band photonic based-crystal by using PWE method. Then, the calculations related to filter output spectrum were carried out by using an FDTD method. Thus, the effect of cells'' radius on the behavior of wavelength switching optical filter has been investigated in this study.