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دانلود مقالات لاتین در زمینه الگوریتم ژنتیک ، شبکه های عصبی و منطق فازی رفتن به صفحه : قبلی  1, 2, 3 ... , 14, 15, 16  بعدی
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

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امتیاز: 210699
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پست تاریخ: یکشنبه 10 خرداد 1394 - 16:02    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

SELECTION OF SUITABLE RECORDS FOR NONLINEAR ANALYSIS USING GENETIC ALGORITHM (GA) AND PARTICLE SWARM OPTIMIZATION (PSO)


Author(s): B. Mohebi, Gh. Ghodrati Amiri * , M. Taheri
Study Type: Research | Subject: Optimal design | Received: 2014/11/17 - Accepted: 2014/11/17 - Published: 2014/11/17
Article abstract:
This paper presents a suitable and quick way to choose earthquake records in non-linear dynamic analysis using optimization methods. In addition, these earthquake records are scaled. Therefore, structural responses of three different soil-frame models were examined, the change in maximum displacement of roof was analyzed and the damage index of whole structures was measured. The soil classification of project location was divided into 4 different types according to the velocity of shear waves in the Iranian Code for Seismic Design. As a result, 8 frame models were considered. The selection and scaling were carried out in 2 stages. In the first stage, the matching with design spectrum was carried out using genetic algorithm in order to achieve the mean of structural response. In the second stage, the matching with average of structural responses were carried out using PSO to achieve 1 or 3 accelerograms with related factors in order to be used in structural analysis.
Keywords: non-linear analysis, PSO, genetic algorithm, matching range, damage index.,
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

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امتیاز: 210699
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پست تاریخ: یکشنبه 10 خرداد 1394 - 16:14    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

A Novel Methodology for Structural Matrix Identification using Wavelet Transform Optimized by Genetic Algorithm


Author(s): G. Ghodrati Amiri * , M. Talebi
Study Type: Research | Subject: Optimal design | Received: 2014/10/19 - Accepted: 2014/10/19 - Published: 2014/10/19
Article abstract:
With the development of the technology and increase of human dependency on structures, healthy structures play an important role in people lives and communications. Hence, structural health monitoring has been attracted strongly in recent decades. Improvement of measuring instruments made signal processing as a powerful tool in structural heath monitoring. Wavelet transform invention causes a great evolution in signal processing. Wavelet transform decomposes a signal into several groups based on scaled and translated basic functions. In this study, a novel methodology based on wavelet transform using complex Morlet wavelet has been introduced for system identification. This process includes a multivariable constrained optimization problem for selecting suitable complex Morlet wavelet. Using selected wavelet, modal parameters and flexibility matrix of structure can be estimated properly. Because of small modal participation of higher mode; using finite number of modes leads to flexibility matrix with acceptable accuracy. Since damages cause change in structural properties, a damage index based on flexibility matrix has been applied and its performance has been investigated in some structures.
Keywords: system identification, matrix updating, signal processing, wavelet transform, genetic algorithm,
Reference
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
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پست تاریخ: یکشنبه 10 خرداد 1394 - 16:28    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

NEURAL NETWORK-BASED RELIABILITY ASSESSMENT OF OPTIMALLY SEISMIC DESIGNED MOMENT FRAMES


Author(s): S. Gholizadeh *, V. Aligholizadeh , M. Mohammadi
Study Type: Research | Subject: Optimal design | Received: 2014/04/3 - Accepted: 2014/04/3 - Published: 2014/04/3
Article abstract:
In the present study, the reliability assessment of performance-based optimally seismic designed reinforced concrete (RC) and steel moment frames is investigated. In order to achieve this task, an efficient methodology is proposed by integrating Monte Carlo simulation (MCS) and neural networks (NN). Two NN models including radial basis function (RBF) and back propagation (BP) models are examined in this study. In the proposed methodology, MCS is used to estimate the total exceedence probability associated with immediate occupancy (IO), life safety (LS) and collapse prevention (CP) performance levels. To reduce the computational burden of MCS process, the required nonlinear responses of the generated structures are predicted by RBF and BP models. The numerical results imply the superiority of BP to RBF in prediction of structural responses associated with performance levels. Finally, the obtained results demonstrate the high efficiency of the proposed methodology for reliability assessment of RC and steel frame structures.
Keywords: Seismic reliability, performance-based design, structural optimization, Monte Carol simulation, neural network,
Reference
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
[وضعيت كاربر:آفلاین]

پست تاریخ: یکشنبه 10 خرداد 1394 - 16:34    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

GENERATION OF MULTIPLE SPECTRUM-COMPATIBLE ARTIFICIAL EARTHQUAKE ACCELEGRAMS WITH HARTLEY TRANSFORM AND RBF NEURAL NETWORK


Author(s): G. Ghodrati Amiri *, K. Iraji , P. Namiranian
Study Type: Research | Subject: Applications | Received: 2014/04/3 - Accepted: 2014/04/3 - Published: 2014/04/3
Article abstract:
The Hartley transform, a real-valued alternative to the complex Fourier transform, is presented as an efficient tool for the analysis and simulation of earthquake accelerograms. This paper is introduced a novel method based on discrete Hartley transform (DHT) and radial basis function (RBF) neural network for generation of artificial earthquake accelerograms from specific target spectrums. Acceleration time histories of horizontal earthquake ground motion are obtained by the capability of learning of RBF neural network to expand the knowledge of the inverse mapping from the response spectrum to earthquake accelerogram. In the first step, Hartley transform is used to decompose earthquake accelerograms, then a RBF neural network is trained to learn to relate the response spectrum to Hartley spectrum. Finally, the generated accelerogram using inverse discrete Hartley transform is obtained from target spectrum. Approximately 200 uniformly scaled horizontal ground motion records from recent Iran’s earthquakes are used to decompose with real Hartley transform and train networks.
Keywords: Hartley transform, RBF neural network, artificial earthquake accelerograms,
Reference
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مرجع کاربردی طراحی سازه های فولادی با نرم افزار ETABS 2013 و SAFE ورژن 12 : http://goo.gl/zkqFfH

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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
[وضعيت كاربر:آفلاین]

پست تاریخ: یکشنبه 10 خرداد 1394 - 16:35    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

STRUCTURAL RESPONSE OBSERVER BASED ON ARTIFICIAL NEURAL NETWORK


Author(s): A. Gholizad * , S. D. Ojaghzadeh Mohammadi
Study Type: Research | Subject: Applications | Received: 2014/04/3 - Accepted: 2014/04/3 - Published: 2014/04/3
Article abstract:
Structural vibration control is one of the most important features in structural engineering. Real-time information about seismic resultant forces is required for deciding module of intelligent control systems. Evaluation of lateral forces during an earthquake is a complicated problem considering uncertainties of gravity loads amount and distribution and earthquake characteristics. An artificial neural network (ANN) has been trained in this article to estimate these forces. This ANN was trained on the results of time history analysis of a three-story building under 702 different loadings. Results of numerical examples verify that the trained ANN can predict the expected forces with negligible deviations.
Keywords: Structural vibration control, Dynamic response estimation, Multilayer perceptron artificial neural network,
Reference
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مرجع کاربردی طراحی سازه های فولادی با نرم افزار ETABS 2013 و SAFE ورژن 12 : http://goo.gl/zkqFfH

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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
[وضعيت كاربر:آفلاین]

پست تاریخ: یکشنبه 10 خرداد 1394 - 16:36    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

OPTIMAL SENSOR PLACEMENT FOR MODAL IDENTIFICATION OF A STRAP-BRACED COLD FORMED STEEL FRAME BASED ON IMPROVED GENETIC ALGORITHM


Author(s): F. Zahedi Tajrishi * , A. R. Mirza Goltabar Roshan
Study Type: Research | Subject: Applications | Received: 2014/04/3 - Accepted: 2014/04/3 - Published: 2014/04/3
Article abstract:
This paper is concerned with the determination of optimal sensor locations for structural modal identification in a strap-braced cold formed steel frame based on an improved genetic algorithm (IGA). Six different optimal sensor placement performance indices have been taken as the fitness functions; two based on modal assurance criterion (MAC), two based on maximization of the determinant of a Fisher information matrix (FIM), one aim on the maximization of the modal energy and the last is a combination of two aforementioned indices. The decimal two-dimension array coding method instead of binary coding method is applied to code the solution. Forced mutation operator is applied whenever the identical genes produce via the crossover procedure. An improvement is also introduced to mutation operator of the IGA. A verified computational simulation of a strap-braced cold formed steel frame model has been implemented to demonstrate the effectiveness and application of the proposed method. The obtained optimal sensor placements using IGA are compared with those gained by the conventional methods based on several criteria such as norms of FIM and minimum in off-diagonal terms of MAC. The results showed that the proposed IGA can provide sensor locations as well as the conventional methods. More important, based on the criteria, four of the six fitness functions, can identify the vibration characteristics of the frame model accurately. It is shown through the example that in comparison with the MAC-based performance indices, the use of the FIM-based fitness functions results in more acceptable and reasonable configurations.
Keywords: Optimal sensor placement, improved genetic algorithm, cold formed steel, strap brace, modal analysis, modal assurance criterion,
Reference
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
[وضعيت كاربر:آفلاین]

پست تاریخ: یکشنبه 10 خرداد 1394 - 16:38    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

IMPROVING THE SEISMIC BEHAVIOR OF NONLINEAR STEEL STRUCTURES USING OPTIMAL MTMDS


Author(s): M. Mohebbi *, S. Moradpour , Y. Ghanbarpour
Study Type: Research | Subject: Applications | Received: 2014/04/6 - Accepted: 2014/04/11 - Published: 2014/04/11
Article abstract:
In this research, optimal design and assessment of multiple tuned mass dampers (MTMDs) capability in mitigating the damage of nonlinear steel structures subjected to earthquake excitation has been studied. Optimal parameters of TMDs on nonlinear multi-degree-of-freedom (MDOF) structures have been determined based on minimizing the maximum relative displacement (drift) of structure where for solving the optimization problem the genetic algorithm (GA) has been used successfully. For numerical analysis, three and nine storey 2-D moment resisting nonlinear steel frames subjected to far-field and near-field earthquakes and optimal MTMDs has been designed for different values of mass ratio and TMDs number. According to the results of numerical simulations, it can be said that MTMDs mechanism could reduce the damage of nonlinear steel structures where the effectiveness increases by increasing TMDs mass ratio. Also the performance of MTMDs depends on earthquake characteristics, mass ratio and TMDs configuration where in this research; the effective case has been locating TMDs on top floor in parallel configuration.
Keywords: Nonlinear steel structure, seismic behavior, multiple tuned mass damper (MTMD), genetic algorithm (GA),
Reference
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
[وضعيت كاربر:آفلاین]

پست تاریخ: یکشنبه 10 خرداد 1394 - 17:24    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

USING LATIN HYPERCUBE SAMPLING BASED ON THE ANN-HPSOGA MODEL FOR ESTIMATION OF THE CREATION PROBABILITY OF DAMAGED ZONE AROUND UNDERGROUND SPACES


Author(s): H. Fattahi, S. Shojaee *, M A. Ebrahimi Farsangi , H. Mansouri
Study Type: Research | Subject: Applications | Received: 2013/07/20 - Accepted: 2013/07/29 - Published: 2013/07/29
Article abstract:
The excavation damaged zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. In this paper, a methodology was examined for computing the creation probability of damaged zone by Latin hypercube sampling based on a feed-forward artificial neural network (ANN) optimized by hybrid particle swarm optimization and genetic algorithm (HPSOGA). The HPSOGA was carried out to decide the initial weights of the neural network. A case study in a test gallery of the Gotvand dam, Iran was carried out and creation probabilities of 0.191 for highly damaged zone (HDZ) and 0.502 for EDZ were obtained.
Keywords: latin hypercube sampling, artificial neural network, particle swarm optimization, genetic algorithm, The creation probability of damaged zone,
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
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پست تاریخ: یکشنبه 10 خرداد 1394 - 17:56    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

OPTIMUM WEIGHTED MODE COMBINATION FOR NONLINEAR STATIC ANALYSIS OF STRUCTURES


Author(s): K. Shakeri *
Study Type: Research | Subject: Optimal analysis | Received: 2013/03/28 - Accepted: 2013/04/27 - Published: 2013/04/27
Article abstract:
In recent years some multi-mode pushover procedures taking into account higher mode effects, have been proposed. The responses of considered modes are combined by the quadratic combination rules, while using the elastic modal combination rules in the inelastic phases is not valid. Here, an optimum weighted mode combination method for nonlinear static analysis is presented. Genetic algorithm is used for optimization of the modal weight. The proposed procedure is applied for a sample building. The results show that the resulted response from the proposed method has minimal error in comparison with the response of the nonlinear time history analysis.
Keywords: pushover; modal combination; optimization; genetic algorithm,
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عضو شده در: 7 مهر 1385
پست: 37412

تشکر: 3351
تشکر شده 18469 بار در 8611 پست

محل سکونت: همدان iran.gif


امتیاز: 210699
[وضعيت كاربر:آفلاین]

پست تاریخ: یکشنبه 10 خرداد 1394 - 18:30    عنوان:   پاسخگویی به این موضوع بهمراه نقل قول

OPTIMUM SHAPE DESIGN OF DOUBLE-LAYER GRIDS BY QUANTUM BEHAVED PARTICLE SWARM OPTIMIZATION AND NEURAL NETWORKS


Author(s): S. Gholizadeh *, P. Torkzadeh , S. Jabarzadeh
Study Type: Research | Subject: Optimal design
Article abstract:
In this paper, a methodology is presented for optimum shape design of double-layer grids subject to gravity and earthquake loadings. The design variables are the number of divisions in two directions, the height between two layers and the cross-sectional areas of the structural elements. The objective function is the weight of the structure and the design constraints are some limitations on stress and slenderness of the elements besides the vertical displacements of the joints. To achieve the optimization task a variant of particle swarm optimization (PSO) entitled as quantum-behaved particle swarm optimization (QPSO) algorithm is employed. The computational burden of the optimization process due to performing time history analysis is very high. In order to decrease the optimization time, the radial basis function (RBF) neural networks are employed to predict the desired responses of the structures during the optimization process. The numerical results demonstrate the effectiveness of the presented methodology
Keywords: double-layer grid; optimum shape design; time history analysis; quantum-behaved particle swarm optimization; radial basis function neural network,
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