Search for: genetic-algorithm
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    A new approach based on ant algorithm for Volt/Var control in distribution network considering distributed generation

    , Article Iranian Journal of Science and Technology, Transaction B: Engineering ; Volume 29, Issue 4 , 2005 , Pages 385-398 ; 03601307 (ISSN) Niknam, T ; Ranjbar, A. M ; Shirani, A. R ; Ostadi, A ; Sharif University of Technology
    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... 

    A new approach to optimization of cogeneration systems using genetic algorithm

    , Article International Journal of Energy and Environmental Engineering ; Volume 1, Issue 1 , 2010 , Pages 37-48 ; 20089163 (ISSN) Zomorodian, R ; Rezasoltani, M ; Ghofrani, M. B ; Sharif University of Technology
    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,... 

    Artificial intelligence techniques for modeling and optimization of the HDS process over a new graphene based catalyst

    , Article Phosphorus, Sulfur and Silicon and the Related Elements ; Volume 191, Issue 9 , 2016 , Pages 1256-1261 ; 10426507 (ISSN) Hajjar, Z ; Kazemeini, M ; Rashidi, A ; Tayyebi, S ; Sharif University of Technology
    Taylor and Francis Ltd  2016
    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... 

    Forecasting smoothed non-stationary time series using genetic algorithms

    , Article International Journal of Modern Physics C ; Volume 18, Issue 6 , 2007 , Pages 1071-1086 ; 01291831 (ISSN) Norouzzadeh, P ; Rahmani, B ; Norouzzadeh, M. S ; Sharif University of Technology
    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... 

    Evolution of pleasure system in zamin artificial world

    , Article Proceedings of the Fifteenth IASTED Internatinal Conference on Modeling and Simulation, Marina Del Rey, CA, 1 March 2004 through 3 March 2004 ; 2004 , Pages 272-277 ; 10218181 (ISSN) Halavati, R ; Haratizadeh, S ; Bagheri Shouraki, S ; Sharif University of Technology
    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  

    Dynamic economic dispatch in restructured power systems considering transmission costs using genetic algorithm

    , Article Canadian Conference on Electrical and Computer Engineering; Technology Driving Innovation, 2004, Niagara Falls, 2 May 2004 through 5 May 2004 ; Volume 3 , 2004 , Pages 1625-1628 ; 08407789 (ISSN) Hosseini, S. H ; Kheradmandi, M ; Sharif University of Technology
    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... 

    Evolution of communication

    , Article Proceedings of the Seventh IASTED International Conference on Artificial Intelligence and Soft Computing, Banff, 14 July 2003 through 16 July 2003 ; Volume 7 , 2003 , Pages 274-277 ; 0889863679 (ISBN) Halavati, R ; Bagheri Shouraki, S ; Sharif University of Technology
    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  

    Reliability consideration in optimization of cascaded hydrothermal power systems

    , Article International Journal of Power and Energy Systems ; Volume 23, Issue 1 , 2003 , Pages 6-14 ; 10783466 (ISSN) Modarres, M ; Farrokhzad, D ; Sharif University of Technology
    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... 

    Optimal synthesis of planar and spatial mechanism for path generation using regression deviation

    , Article Scientia Iranica ; Volume 12, Issue 2 , 2005 , Pages 190-198 ; 10263098 (ISSN) Zohoor, H ; Tavakoli Nia, H ; Sharif University of Technology
    Sharif University of Technology  2005
    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  

    Design of variable fractional delay FIR filters using genetic algorithm

    , Article 2003 10th IEEE International Conference on Electronics, Circuits and Systems, ICECS2003, Sharjah, 14 December 2003 through 17 December 2003 ; Volume 1 , 2003 , Pages 48-51 ; 0780381637 (ISBN); 9780780381636 (ISBN) Khamei, K ; Nabavi, A ; Hessabi, S ; 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,... 

    A hybrid method of neural networks and genetic algorithm in econometric modeling and analysis

    , Article Journal of Applied Sciences ; Volume 8, Issue 16 , 2008 , Pages 2825-2833 ; 18125654 (ISSN) Hasheminia, H ; Akhavan Niaki,S. T ; Sharif University of Technology
    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  

    Which method is better for the kinetic modeling: decimal encoded or binary genetic algorithm?

    , Article Chemical Engineering Journal ; Volume 130, Issue 1 , 2007 , Pages 29-37 ; 13858947 (ISSN) Boozarjomehry, R. B ; Masoori, M ; Sharif University of Technology
    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... 

    Comparing Performance of M.V, E.G.P and M.V.S Based on Genetic Algorithm in Iranian Capital Market

    , M.Sc. Thesis Sharif University of Technology Sanati, Ali (Author) ; Bahramgiri, Mohsen (Supervisor)
    The portfolio selection problem is always one of the most important problems of finance and investments due to its great implication and vital role in financial institutions. Many of researches in this area are based on the mean-variance model, originally proposed by Markoitz. In the last two decades, however, researchers and investors have attracted to some new models that import some new factors other than mean and variance in the portfolio decision problem, such as different risk measures, etc. In this research we compare performances of mean-variance, Elton-Gruber-Padberg (EGP) and mean-variance-skewness based on genetic algorithm in Tehran Stock Exchange. Moreover, in order to find the... 

    A Quantitative Structure-Activity Relationship Study on Multiple Sclerosis (MS) Drugs

    , M.Sc. Thesis Sharif University of Technology Torkashvand, Rezvan (Author) ; Jalali-Heravi, Mehdi (Supervisor)
    In the present work we report a quantitative structure-activity relationship (QSAR) study on S1P1 receptor’s agonists that have therapeutic potential for autoimmune disorders such as Multiple Sclerosis (MS). Such studies play an important role in drug design and lead optimization by developing a mathematical relationship between the chemical structures of compounds and their biological activities.
    We used both linear and nonlinear techniques such as MLR and ANN respectively to model these compounds together with techniques such as Stepwise-MLR, GA-MLR and GA-ANN in the variable selection step as it is an important step in every QSAR study. Since topological descriptors are well... 

    Hydrodynamic optimization of marine propeller using gradient and non-gradientbased algorithms

    , Article Acta Polytechnica Hungarica ; Volume 10, Issue 3 , 2013 , Pages 221-237 ; 17858860 (ISSN) Taheri, R ; Mazaheri, K ; Sharif University of Technology
    Here a propeller design method based on a vortex lattice algorithm is developed, and two gradient-based and non-gradient-based optimization algorithms are implemented to optimize the shape and efficiency of two propellers. For the analysis of the hydrodynamic performance parameters, a vortex lattice method was used by implementing a computer code. In the first problem, one of the Sequential Unconstraint Minimization Techniques (SUMT) is employed to minimize the torque coefficient as an objective function, while keeping the thrust coefficient constant as a constraint. Also, chord distribution is considered as a design variable, namely 11 design variables. In the second problem, a modified... 

    An optimized neural network model of desalination by vacuum membrane distillation using genetic algorithm

    , Article CHISA 2012 - 20th International Congress of Chemical and Process Engineering and PRES 2012 - 15th Conference PRES ; 2012 Tavakolmoghadam, M ; Safavi, M ; Sharif University of Technology
    An experimental based ANN model is constructed to describe the performance of vacuum membrane distillation process for desalination in different operating conditions. The vacuum pressure, feed inlet temperature, concentration of the feed salt aqueous solution, and feed flow rate are the input variables of this process, while response is the permeate flux. The neural network approach is capable for modeling this membrane distillation configuration. The application of Genetic Algorithm to optimize the ANN model parameters was also examined. This is an abstract of a paper presented at the CHISA 2012 - 20th International Congress of Chemical and Process Engineering and PRES 2012 - 15th... 

    An optimized neural network model of desalination by vacuum membrane distillation using genetic algorithm

    , Article Procedia Engineering ; Volume 42 , 2012 , Pages 106-112 ; 18777058 (ISSN) Tavakolmoghadam, M ; Safavi, M ; Sharif University of Technology
    An experimental based ANN model is constructed to describe the performance of vacuum membrane distillation process for desalination in different operating conditions. The vacuum pressure, the feed inlet temperature, the concentration of the feed salt aqueous solution and the feed flow rate are the input variables of this process, whereas the response is the permeate flux. The neural network approach was found to be capable for modeling this membrane distillation configuration. The application of Genetic Algorithm (GA) to optimize the ANN model parameters was also investigated  

    Genetic algorithm for solving fuzzy shortest path problem in a network with mixed fuzzy arc lengths

    , Article AIP Conference Proceedings, 2 December 2010 through 4 December 2010, Sarawak ; Volume 1337 , 2011 , Pages 265-270 ; 0094243X (ISSN) ; 9780735408937 (ISBN) Mahdavi, I ; Tajdin, A ; Hassanzadeh, R ; Mahdavi-Amiri, N ; Shafieian, H ; Sharif University of Technology
    We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model  

    Fault diagnosis in a yeast fermentation bioreactor by genetic fuzzy system

    , Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 29, Issue 3 , 2010 , Pages 61-72 ; 10219986 (ISSN) Tayyebi, S ; Shahrokhi, M ; Bozorgmehry Boozarjomehry, R ; Sharif University of Technology
    In this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. In one case, parameters of membership functions are selected in a conventional manner. In another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genetic algorithm. These two cases are compared based on their performances in fault diagnosis of a yeast fermentation bioreactor for three different conditions. The simulation results indicate that the fuzzy-genetic system is superior in multiple fault detection for the conditions where the minimum and... 

    A model based approach on multi-agent system and genetic algorithm to improve the process management in service oriented architecture

    , Article Journal of Telecommunication, Electronic and Computer Engineering ; Volume 8, Issue 5 , 2016 , Pages 33-40 ; 21801843 (ISSN) Nahvi, B ; Habibi, J ; Sharif University of Technology
    UniversityTeknikal Malaysia Melaka  2016
    Service oriented architecture is based on the provision of services. To enhance the performance of the systems by providing a better combination of services, it is necessary to extract more information compared to the one in the service registry. In this regard, the accomplished works have been focusing on the basic concepts of service-oriented architecture. The service composition is based on the information in service registry, provided by the service provider. Further, centralized combination with insufficient information does not meet the system performance requirements. This solution helps to facilitate resource distribution and reduces tasks of the central unit. In this paper, efforts...