نتایج جستجو برای: layer perceptron algorithm of artificial neural network next
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Construction and training principles have been proposed and tested for an artificial neural network based on metal-oxide thin-film nanostructures possessing bipolar resistive switching (memristive) effect. Experimental electronic circuit of neural network is implemented as a double-layer perceptron with a weight matrix composed of 32 memristive devices. The network training algorithm takes into...
During the past 20 years, artificial neural networks was successfully applied for solving signal processing problems. Researchers proposed many different models of artificial neural networks. A challenge is to identify the most appropriate neural network model which can work reliably for solving realistic problem. This chapter provides some basic neural network model and efficiently applying th...
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 ...
This paper investigates the effect of boehmite nano-particles surface adsorbed byboric acid (BNBA) along with other input welding parameters such as welding current, arc voltage, welding speed, nozzle-to-plate distance on weld penetration. Weld penetration modeling was carried out using multi-layer perceptron artificial neural network (MPANN) technique. For the sake of training the network, 70%...
Atmosphere–ocean coupled global climate models (GCMs) are the main source to simulate the climate of the earth climate. The computational grid of the GCMs is coarse and so, they are unable to provide reliable information for hydrological modelling. To eliminate such limitations, the downscaling methods are used. The present study is focused on simulating the impact of climate change on the beha...
Classrooms, as one of the most important educational environments, play a major role in the learning and academic progress of students. reverberation time, as one of the most important acoustic parameters inside rooms, has a significant effect on sound quality. The inefficiency of classical formulas such as Sabin, caused this article to examine the use of machine learning methods as an alternat...
This paper investigates the effect of boehmite nano-particles surface adsorbed byboric acid (BNBA) along with other input welding parameters such as welding current, arc voltage, welding speed, nozzle-to-plate distance on weld penetration. Weld penetration modeling was carried out using multi-layer perceptron artificial neural network (MPANN) technique. For the sake of training the network, 70%...
In this paper, the application of neural networks to study the maximum and minimum relative humidity for Chandigarh city is explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model forecasting system is used and Back Propagation algorithm is used to train the network. The proposed network is trained with actual data of the past 10 years (2000-2010) and...
This article presents the role of artificial neural networks in use of hydroabrassive suspensive jet cut process in laminate treatment. Three-ply layer perceptron type network with an error backpropagation learning algorithm was applied to describe this process. The article provides detailed description of neural network. This neural network simulates the treatment process and predicts its effi...
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...
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