نتایج جستجو برای: Genetic Algorithm Artificial neural network

تعداد نتایج: 2159205  

پایان نامه :دانشگاه آزاد اسلامی - دانشگاه آزاد اسلامی واحد تهران مرکزی - دانشکده برق و الکترونیک 1390

there are many approaches for solving variety combinatorial optimization problems (np-compelete) that devided to exact solutions and approximate solutions. exact methods can only be used for very small size instances due to their expontional search space. for real-world problems, we have to employ approximate methods such as evolutionary algorithms (eas) that find a near-optimal solution in a r...

Journal: :computational methods in civil engineering 2011
a. shahjouei g. ghodrati amiri

through the last three decades different seismological and engineering approaches for the generation of artificial earthquakes have been proposed. selection of an appropriate method for the generation of applicable artificial earthquake accelerograms (aeas) has been a challenging subject in the time history analysis of the structures in the case of the absence of sufficient recorded accelerogra...

Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...

ژورنال: علوم آب و خاک 2010
آخوندعلی, علی محمد, امیری چایجان, رضا, زارع ابیانه, حمید, شریفی, محمدرضا, طبری, حسین, معروفی, صفر,

In mountainous basins, snow water equivalent is usually used to evaluate water resources related to snow. In this research, based on the observed data, the snow depth and its water equivalent was studied through application of non-linear regression, artificial neural network as well as optimization of network's parameters with genetic algorithm. To this end, the estimated values by artificial n...

Journal: :basic and clinical neuroscience 0
yashar sarbaz shahriar gharibzadeh farzad towhidkhah masood banaie ayyoob jafari

in this study, we focused on the gait of parkinson’s disease (pd) and presented a gray box model for it. we tried to present a model for basal ganglia structure in order to generate stride time interval signal in model output for healthy and pd states. because of feedback role of dopamine neurotransmitter in basal ganglia, this part is modelled by “elman network”, which is a neural network stru...

Journal: :آب و خاک 0
محبوبه زارع زاده مهریزی امید بزرگ حداد

abstract one of the major factors on the amount of water resources is river flow which is so dependent to the hydrologic and meteorologic phenomena. simulation and forecasting of river flow makes the decision maker capable to effectively manage the water resources projects. so, simulation and forecasting models such as artificial neural networks (anns) are commonly used for simulation and predi...

Journal: :iranian journal of medical physics 0
javad haddadnia biomedical engineering department, hakim sabzevari university, center for research of advanced medical technologies, sabzevar university of medical sciences, sbzevar, iran

introduction this study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. the medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. by analyzing this information, the best diagnostic parameters among the available parameters are selected and ...

Introduction:  It is of utmost importance to predict cardiovascular diseases correctly. Therefore, it is necessary to utilize those models with a minimum error rate and maximum reliability. This study aimed to combine an artificial neural network with the genetic algorithm to assess patients with myocardial infarction and congestive heart failure.   Materials & Methods: This study utilized a m...

Journal: :nutrition and food sciences research 0
hajar abbasi islamic azad university, esfahan branch (khorasgan), arghavanieh, jey st., esfahan, iran. post code: 81551-39998, p.o.box: 81595-158 seyyed mahdi seyedain ardabili department of food science and technology, faculty of agriculture and natural resources, science and research branch, islamic azad university, tehran, iran mohammad amin mohammadifar department of food science and technology, faculty of nutrition sciences, food science and technology / national nutrition and food technology research institute, shahid beheshti university of medical sciences, po box 19395-47471, tehran, iran zahra emam-djomeh transfer phenomena laboratory, department of food science, technology and engineering, faculty of agricultural engineering and technology, agricultural campus of the university of tehran, po box 4111, 31587-11167 karadj, iran

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

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