نتایج جستجو برای: step neural network rmsnn

تعداد نتایج: 1073649  

Journal: :تحقیقات آب و خاک ایران 0
ایمان جوادزرین کارشناس ارشد، گروه مهندسی علوم خاک، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران. بابک متشرع زاده دانشیار گروه مهندسی علوم خاک، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران

the aim followed in this study was to compare the performance of multiple regression vs neural network models to predict the activity of antioxidant enzymes super oxide dismutase (sod), cat alase (cat), ascorbate pero xidase (apx) and peroxidase (pox) in the shoots of wheat (triticum aestivum), alvand cultivar in a soil polluted with cadmium. the treatments consisted of four levels of cadmium (...

ژورنال: پیاورد سلامت 2017
خواجه پور, حسن, خواجه پور, عصمت, سالاری, راحله, لنگری زاده, مصطفی,

Background and Aim: Bacterial meningitis detection is a complicated problem because of having several components in order to be diagnosed and distinguished from other types of meningitis. Fuzzy logic and neural network, frequently used in expert systems, are able to distinguish such diseases. The purpose of this paper is to compare Fuzzy logic and artificial neural networks for distinguishing b...

ژورنال: محاسبات نرم 2013

The uniformity of yarn is one of the major quality parameters which significantly influences on yarn characteristics, warping, weaving, and ultimately fabric production. This parameter depends on fiber properties and spinning process directly. In this study, yarn non-uniformity in a worsted spinning system was predicted by using a hybrid technique involving Kohonen's self-organized and percep...

Nowadays, estimating the ampere consumption and achieve to the optimum condition from the perspective of energy consumption is one of the most important steps to reduce the production costs. In this research it is tried to develop an accurate model for estimating the ampere consumption by using the artificial neural networks (ANN).In the first step, experimental studies were carried out on 7 ca...

Journal: Geopersia 2018

The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalanformations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta...

Journal: :تحقیقات اقتصادی 0
عبدالرسول قاسمی استادیار دانشکده ی اقتصاد دانشگاه علامه طباطبایی علی اصغر بانویی دانشیار دانشکده ی اقتصاد دانشگاه علامه طباطبایی فاطمه آقائی کارشناسی ارشد دانشکده اقتصاد دانشگاه علامه طباطبایی

forecasting of macroeconomic variables has specific importance in economic topics. indeed, different models are invented to forecast variables to help economic policy makers in adopting appropriate monetary and fiscal policies. in this paper, the performance of integrated model of input-output (io) and neural network is investigated in forecasting final demand and total production and the resul...

Journal: :journal of rehabilitation in civil engineering 2014
ali kheyroddin hosein naderpour masoud ahmadi

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...

2017
Jorge Calvo-Zaragoza Gabriel Vigliensoni Ichiro Fujinaga

One of the most complex stages of optical music recognition workflows is the detection and isolation of musical symbols. Traditionally, this goal is achieved by performing preprocesses of binarization and staff-line removal. However, these are commonly performed using heuristics that do not generalize widely when applied to different types of documents such as medieval scores. In this paper we ...

B. Ahmadi-Nedushan, M. Payandeh-Sani,

This article presents numerical studies on semi-active seismic response control of structures equipped with Magneto-Rheological (MR) dampers. A multi-layer artificial neural network (ANN) was employed to mitigate the influence of time delay, This ANN was trained using data from the El-Centro earthquake. The inputs of ANN are the seismic responses of the structure in the current step, and the ou...

This paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (CCFST) stub columns under axial loading condition based on Artificial Neural Networks (ANNs) by using a large wide of experimental investigations. The input parameters were selected based on past studies such as outer diameter of column, compressive strength...

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