نتایج جستجو برای: artificial neural network asphaltene

تعداد نتایج: 1026901  

Journal: :advances in mathematical finance and applications 0
maryam saberi tarbiat modarres university, tehran, iran mohammad reza rostami tarbiat modarres university, tehran, iran mohsen hamidian tarbiat modarres university, tehran, iran nafiseh aghami tarbiat modarres university, tehran, iran

profitability as the most important factor in decision-making, has always been considered by stake­holders in the company's profitability. also can be a basis for evaluating the performance of the managers. the ability to predict the profitability can be very useful to help decision-makers. that's why one of the most important issues is the expected profitability. the importance of th...

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

با توجه به طول دوره آماری کم اطلاعات، سعی شده است تا حد امکان از مدلهایی با پیچیدگی کمتر استفاده شود. بدین منظور از روش تحلیل مولفه های اصلی برای بررسی تغییرات اطلاعات انتقالی با تعداد سیگنال های درنظر گرفته شده، استفاده شده است. سپس به منظور تعیین ورودی های مدل پیش بینی بارش حوضه، از روش همبستگی و روش نوین تست گاما استفاده شده است. مقایسه نتایج مدلسازی با استفاده از معیارهای ارزیابی نشان دهنده...

Journal: :iranian chemical communication 2014
sharmin esmaeilpoor zahra shirzadi hadi noorizadeh

the quantitative structure-retention relationship (qsrr) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. the genetic algorithm (ga) was employed to select the variables that resulted in the best-fitted models. after the variables were selected, the linear multi...

Journal: :iranian journal of health sciences 0
mohammad rafiee department of environmental health engineering, school of public health, shahid beheshti universityof medical sciences, tehran, iran mahsa jahangiri-rad young researchers and elites club, science and research branch, islamic azad university, tehran, iran

abstract background and purpose: eutrophication is one of the major environmental problems in waterways causing substantial adverse impact on domestic, livestock and recreational use of water resources. aras dam, iran which provides arasful city with drinking water, has chronic algal blooms since 1990. levels of up to 900,000 cells/ml of toxic cyanobacteria (mainly anabaena and microcystis) hav...

Journal: :international journal of nanoscience and nanotechnology 2015
a. azari s. marhemati

in this study, a model for estimating the nfs thermal conductivity by using a gmdh-pnn has been investigated. nfs thermal conductivity was modeled as a function of the nanoparticle size, temperature, nanoparticle volume fraction and the thermal conductivity of the base fluid and nanoparticles. for this purpose, the developed network contains 8 layers with 2 inputs in each layer and also trainin...

Journal: :international journal of advanced biological and biomedical research 2013
manish dubey a.k wadhwani s. wadhwani

the aim of this work is to use self organizing map (som) for clustering of locomotion kinetic characteristics in normal and parkinson’s disease. the classification and analysis of the kinematic characteristics of human locomotion has been greatly increased by the use of artificial neural networks in recent years. the proposed methodology aims at overcoming the constraints of traditional analysi...

Journal: :international journal of iron and steel society of iran 0
m. rakhshkhorshid department of mechanical and materials engineering, birjand university of technology, south khorasan, iran h. rastegari department of mechanical and materials engineering, birjand university of technology, south khorasan, iran

many efforts have been made to model the the hot deformation (dynamic recrystallization) flow curves of different materials. phenomenological constitutive models, physical-based constitutive models and artificial neural network (ann) models are the main methods used for this purpose. however, there is no report on the modeling of warm deformation (dynamic spheroidization) flow curves of any kin...

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...

Journal: :civil engineering infrastructures journal 0
mahmoud hassanlourad assistant professor, faculty of engineering, imam khomeini international university, qazvin, iran. maryam vosoughi m.sc. student, faculty of engineering, imam khomeini international university, qazvin, iran. arash sarrafi m.sc. student, faculty of engineering, imam khomeini international university, qazvin, iran.

in this paper, the grouting ability of sandy soils is investigated by artificial neural networks based on the results of chemical grout injection tests. in order to evaluate the soil grouting potential, experimental samples were prepared and then injected. the sand samples with three different particle sizes (medium, fine, and silty) and three relative densities (%30, %50, and %90) were injecte...

Journal: :journal of ai and data mining 2014
mohaddeseh dashti vali derhami esfandiar ekhtiyari

yarn tenacity is one of the most important properties in yarn production. this paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. the artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 ne. as the first step for modeling, the empirical data is col...

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