نتایج جستجو برای: artificial neural network ann

تعداد نتایج: 1040345  

Bio-absorbent palm fiber was applied for removal of cationic violet methyl dye from water solution. For this purpose, a solid phase extraction method combined with the artificial neural network (ANN) was used for preconcentration and determination of removal level of violet methyl dye. This method is influenced by factors such as pH, the contact time, the rotation speed, and the adsorbent dosag...

2014
Ankit Sanghavi Sachin M. Bojewar

this paper deals with the classification of cardiovascular disease for its future analysis. If future progression of the disease can be predicted earlier with proper change in medication patients treatment can be improved. Artificial neural network (ANN) is used as classifier with wavelet transform as the feature extraction for reducing data set of ECG. Hidden markov model (HMM) is used as pred...

Journal: :desert 2011
m.t. dastorani h. afkhami

in recent decades artificial neural networks (anns) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. this paper presents the application of artificial neural networks to predict drought in yazd meteorological station. in this research, different archite...

ژورنال: اقتصاد مالی 2017

هدف پژوهش حاضر پیش‌بینی شاخص قیمت بورس اوراق بهادار تهران با استفاده از مدل شبکه عصبی هیبریدی مبتنی بر الگوریتم ژنتیک و جستجوی هارمونی است. مربوط‌ترین نماگرهای تکنیکی به عنوان متغیرهای ورودی و تعداد بهینه نرون در لایه پنهان شبکه عصبی مصنوعی با استفاده از الگوریتم‌های فراابتکاری ژنتیک و جستجوی هارمونی حاصل می‌گردد. مقادیر روزانه شاخص قیمت بورس اوراق بهادار تهران از تاریخ 1/10/91 الی 30/9/94 جهت ...

A Geranmayeh F Ghobadi H Rezaei M Bashiri

Most of existing researches for multi response optimization are based on regression analysis. However, the artificial neural network can be applied for the problem. In this paper, two approaches are proposed by consideration of both methods. In the first approach, regression model of the controllable factors and S/N ratio of each response has been achieved, then a fuzzy programming has been app...

In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...

ژورنال: سلامت و محیط زیست 2018

Background and Objective: Chromium is present in two oxidation forms of Cr(III) and Cr(VI). Cr(III) is less toxic than Cr(VI). The aim of this article was to optimize an artificial neural network structure in modeling the photocatalytic reduction of Cr(VI) by TiO2-P25 nanoparticles. Materials and Methods: In this work, an artificial neural network (ANN) for the modeling photocatalytic reductio...

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 Me...

2015
Jitesh R. Shinde Suresh Salankar

This paper proposes a novel approach for an optimal multi-objective optimization for VLSI implementation of Artificial Neural Network (ANN) which is area-power-speed efficient and has high degree of accuracy and dynamic range. A VLSI implementation of feed forward neural network in floating point arithmetic IEEE-754 single precision 32 bit format is presented that makes the use of digital weigh...

Journal: :journal of computer and robotics 0
mohammad talebi motlagh department of systems and control, industrial control center of excellence, k.n.toosi university of technology, tehran, iran hamid khaloozadeh department of systems and control, industrial control center of excellence, k.n.toosi university of technology, tehran, iran

modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید