نتایج جستجو برای: basis function neural network

تعداد نتایج: 2248031  

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه شیراز 1378

در سالیان اخیر توجه زیادی روی موضوع تشخیص خطا در واحدهای مختلف شیمیائی بوسیله روشهای مختلف شده است . که یکی از این روشها شبکه های عصبی می باشد که شامل سه مرحله، آموزش ، بازخوانی و عمومیت بخشیدن می باشد. در این مقاله با استفاده از شبکه های عصبی مصنوعی (network artificial neural) از نوع (rbf)radial basis function و (bp) backpropagation خطاهای ایجاد شده در برج تقطیر تشخیص داده می شود. جهت آموزش اب...

Journal: :journal of tethys 0

estimation of reservoir water saturation (sw) is one of the main tasks in well logging. many empirical equations are available, which are, more or less, based on archie equation. the present study is an application of radial basis function neural network (rbfnn) modeling for estimation of water saturation responses in a carbonate reservoir. four conventional petrophysical logs (pls) including d...

Reservoir characterization and asset management require comprehensive information about formation fluids. In fact, it is not possible to find accurate solutions to many petroleum engineering problems without having accurate pressure-volume-temperature (PVT) data. Traditionally, fluid information has been obtained by capturing samples and then by measuring the PVT properties in a laboratory. In ...

Journal: :جغرافیا و توسعه ناحیه ای 0
کمال امیدوار معصومه نبوی زاده

precipitation is one of important parameters of climatology and atmospheric science that have more importance in human life. recently, extensive flood and drought entered many damage to most parts of the world. precipitation forecasting and alerts management role is responsible for these problems. today, artificial neural networks are one of developed method that applied for estimate and predic...

Journal: :international journal of information science and management 0
k. salahshoor ph.d. , department of automation and instrumentation, petroleum university of technology, tehran m. r. jafari m.s. , department of automation and instrumentation, petroleum university of technology, tehran

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تبریز 1389

به منظور تخمین زمانی- مکانی مقدار بارش ماهیانه، با توجه به پیچیدگی پدیده و در دسترس نبودن اطلاعات فیزیکی کافی و عدم اطلاع دقیق از روابط و معادلات ریاضی حاکم بر مسئله، معمولاً به سراغ ارائ? مدلهای جعبه سیاه، که مستقل از پارامترهای فیزیکی موثر بر پدیده و معادلات حاکم بین آنها می باشد، باید رفت. در این پایان نامه مدلی ترکیبی و جعبه سیاه تحت عنوان ann-rbf به منظور تخمین زمانی- مکانی مقدار بارش ماهی...

Journal: :پژوهش های علوم دامی ایران 0
جواد ایزی حیدر زرقی

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...

Journal: :international journal of environmental research 0

the application of neural networks to model a laboratory scale inverse fluidized bed reactor has been studied. a radial basis function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. in the proposed model, the trained neural network represents the kinetics of biological decomposition of organic matters in the reactor. the neural network has b...

2010
RYAD ZEMOURI RAFAEL GOURIVEAU PAUL CIPRIAN PATIC Ryad Zemouri Rafael Gouriveau Paul Ciprian Patic

In maintenance field, prognostic is recognized as a key feature as the prediction of the remaining useful life of a system which allows avoiding inopportune maintenance spending. Assuming that it can be difficult to provide models for that purpose, artificial neural networks appear to be well suited. In this paper, an approach combining a Recurrent Radial Basis Function network (RRBF) and a pro...

2002
Kenneth McGarry John MacIntyre

The goal of knowledge transfer is to take advantage of previous training experience to solve related but new tasks. This paper tackles the issue of transfer of knowledge between radial basis function neural networks. We present some preliminary work illustrating how a neural network trained on one task (the source) can be used to assist in the synthesis of a new but similar task (the target).

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