Sharif Digital Repository

Recently, in many countries, power systems are moving towards creating a competitive structure for trading electrical energy. These changes, along with the numerous advantages of the Distributed Generators (DGs), have created more incentives for distribution companies to use these kinds of generators more than ever before. The Volt/Var control is one of the most important control schemes in distribution networks, which can be affected by DGs. This paper presents a new approach for the Volt/ Var control in distribution networks. The output reactive powers of the DGs, Static Var Compensators (SVCs), Load Tap Changers (LTCs) and the settings of the local controllers are chosen as the control... 

Aims: Due to large sized genetic database of population in a given society, researchers face serious problem to analyze genetic data and provide accurate genetic identification. Variation in molecular markers such as SNPs, mtDNAs, STRs and Y-chromosome are utilized for different purposes, including genetic identification. In our country due to natural disasters and imposed war, the use of this technology was considered and according to the requirements, an optimal database was designed that has the capability of analyzing genetic data. Methods: After obtaining individual genetic information, a software was designed for the analysis of genetic information as well as to serve as a common... 

Application of Cogeneration systems based gas turbine for heat and power production is increasing. Because of finite natural energy resources and increasing energy demand the cost effective design of energy systems is essential. CGAM problem as a cogeneration system is considered here for analyzing. Two new approaches are considered, first in thermodynamic model of gas turbine and cogeneration system considering blade cooling of gas turbine and second using genetic algorithm for optimization. The problem has been optimized from thermodynamic and thermoeconomic view point. Results show that Turbine Inlet Temperature (TIT) in thermodynamic optimum condition is higher than thermoeconomic one,... 

A Co-Mo/graphene oxide (GO) catalyst has been synthesized for the first time for application in a defined hydrodesulfurization (HDS) process to produce sulfur free naphtha. An intelligent model based upon the neural network technique has then been developed to estimate the total sulfur output of this process. Process operating variables include temperature, pressure, LHSV and H2/feed volume ratio. The three-layer, feed-forward neural network developed consists of five neurons in a hidden layer, trained with Levenberg–Marquardt, back-propagation gradient algorithm. The predicted amount of residual total sulfur is in very good agreement with the corresponding experimental values revealing a... 

The minimum cost subgraph for joint distributed source and network coding has been studied using a linear programming approach. This problem considers some statistically correlated information sources in a network, where sending over each link has a defined cost. The desired solution to this problem is a set of coding rates over the graph links, that minimizes the total communication costs. But in this problem, the placement of the sources is pre-defined, which is not necessarily optimal. In this paper, for the first time, we find a "good" placement for the sources using a genetic programming approach. This problem can be seen as the generalized mirror sites problem, where sources are not... 

We introduce kernel smoothing method to extract the global trend of a time series and remove short time scales variations and fluctuations from it. A multifractal detrended fluctuation analysis (MF-DFA) shows that the multifractality nature of TEPIX returns time series is due to both fatness of the probability density function of returns and long range correlations between them. MF-DFA results help us to understand how genetic algorithm and kernel smoothing methods act. Then we utilize a recently developed genetic algorithm for carrying out successful forecasts of the trend in financial time series and deriving a functional form of Tehran price index (TEPIX) that best approximates the time... 

Statistical and biochemical studies have revealed nonrandom patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, since it is known that, when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, we have taken into consideration both relative frequencies of amino acids and relative gene copy frequencies of tRNAs in genomic sequences in order to introduce a fitness function which models the mistranslational probabilities more accurately in modern organisms. The... 

Zamin, which is a high level artificial life environment have been successfully used as a test bed for a number of cognitive and AI studies. Here we have tried to test the evolution of a pleasure computing mechanism in Zamin's artificial creatures and have extended their mental capabilities to cover uncertainty in action selection mechanism. The results show some improvements in both genetic evolution process and learning capabilities. More specifically, we have evolved an internal pleasure system in Zamin creatures for the first time, quite unsupervised. In addition creatures could learn much more efficient behavioral patterns than what they could before  

Over the past decade, the power industry in many countries around the world has been undergoing massive changes to introduce competition. In power systems under transmission open access, an optimal schedule of generation of units to satisfy the demand at the minimum production and transmission costs with consideration of system operation constraints is an important issue. In this paper, a method for centralized economic dispatch in deregulated power systems is presented. The considered constraints are minimum and maximum power generation of units, capacity of transmission lines and ramp rate limits. Genetic algorithm is used to solve a nonlinear objective function. Simulations are performed... 

The existence of nonrandom patterns in codon assignments is supported by many statistical and biochemical studies. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations. For example, it is known that when an error induces the conversion of an amino acid to another, the biochemical properties of the resulting amino acid are usually very similar to that of the original. Prior studies include many attempts at quantitative estimation of the fraction of randomly generated codes which, based upon load minimization, score higher than the canonical genetic code. In this study, we took into consideration both the relative... 

The evolution of communication and its consequences on living objects is a challenging subject for many researches. Due to lack of our knowledge about the real trend of this evolution, artificial life simulations can shed light on many dark points of this process. In this paper, we have used Zamin artificial life environment to test the emergence of a very simple form of communication. The usability of this new capability is tested by a simple test of coping with new environment  

This article investigates optimization of long-term operation of hydrothermal power systems consisting of cascaded reservoirs. Due to stochasticity of reservoir inflows, demand for energy, and unit forced outages, the uncertainty of this system is so significant that reliability of demand satisfaction becomes an indispensable component of the modelling process. On the other hand, existence of stochastic parameters, especially in the case of cascaded reservoirs, makes the problem very difficult to solve by applying existing optimization techniques. A hybrid genetic algorithm with dynamic tuning of its control parameters is developed that incorporates real number encoding and an analytical... 

A new approach for PID tuning, based on GA (Genetic algorithm) and Internal Model Control (IMC) technique, is presented in this paper. PID tuning is based on using Method. The IMC technique reduces the number of parameters that must be tuned for a multivariable system using PID controller. The algorithm uses GA for optimal determination of IMC variables. Simulation results present the good performance of the proposed method. © 2007 IEEE  

This method introduces the structural error of regression deviation, which is an effective method for the path generation of a vast type of planar and spatial mechanism. The proposed method avoids point-by-point comparison and requirement of timing and reflects the difference between the two curves very effectively in the objective function. By decreasing the number of the design variables, this method would help considerably in decreasing CPU time. The objective function that is based on regression error would converge to a global minimum by a genetic algorithm. At the end, the effectiveness of the method is shown by two numerical examples. © Sharif University of Technology  

This paper presents a new method for design of Variable Fractional Delay (VFD) FIR digital filters using Genetic Algorithm. In this method, each sub-filter of Farrow structure is designed separately with defined accuracy and bandwidth. Also, a variable mutation probability is employed, which improves the accuracy of the solution. Compared with exiting methods, it reduces the computational complexity and enhances the design flexibility. Sum-of-power-of-two (SOPOT) representation is applied to the filter coefficients. Therefore, SOPOT coefficients of Farrow structure are determined using a simple Genetic Algorithm without recourse to computational techniques. Using the SOPOT representation,... 

LBP coefficients are essential and determine the priority of gray differences. The objectives of this paper are to reveal this and propose a method for finding an optimal priority through the genetic algorithm. On the other hand, the genetic operators such as initialization and cross-over operators, generate invalid coefficients, defective chromosomes. This paper also recommends a rectifying method for correcting defective chromosomes. Results on the FERET and Extended Yale B datasets indicate that the proposed method has markedly higher recognition rates than LBP. © 2017 IEEE  

In this study a hybrid method of neural networks-genetic algorithms is proposed and applied in an economical case study. The results of this study show that the proposed hybrid algorithm is a more efficient modeling approach compared to either a single neural network method or a single genetic algorithm approach. Since modeling based on the observed data is also employed in other fields of science, the application of the proposed method is not restricted only to economics. © 2008 Asian Network for Scientific Information  

Kinetic modeling is an important issue, whose objective is the accurate determination of the rates of various reactions taking place in a reacting system. This issue is a pivotal element for the process design and development particularly for novel processes which are based on reactions taking place between various types of species. In this paper, the Genetic Algorithms have been used to develop a systematic computational framework for kinetic modeling of various reacting systems. This framework can be used to find the optimum values of various parameters that exist in the kinetic model of a reacting system. The Fischer-Tropsch (FT) reactions have been used as the kinetic modeling bench...