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density

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تکرار جستجوی کلیدواژه density در نشریات گروه فنی و مهندسی
تکرار جستجوی کلیدواژه density در مقالات مجلات علمی
  • Ali Kashani, Behrooz Shirgir *, Shervin Sayyar
    In order to compute level of service and density in weaving segments, the Highway Capacity Manual (HCM) defined for the first time in 2010 a relationship based on a lane change rate to assess the density of the weaving segment. It is critical to accurately estimate lane changing rate in these situations, but field observations in weaving segments shorter than 250 meters in Tehran, Iran revealed a significant difference between the HCM2016 model estimate and field data. The traffic and geometric data collected at 87 (15-minute) intervals from six weaving segments in Tehran were used to develop models for estimating lane changing rate in weaving segments. These 87 intervals were then divided into 69 (terrain data) for equations and 18 (test data) for model comparisons. Weaving volume and weaving segment area are introduced as two independent variables in the optional lane changing rate model of weaving vehicles in this study, with R2=0.74. Furthermore, for a lane-changing model of non-weaving vehicles with R2=0.95, two new variables of non-weaving volume and traffic solidity were defined. Finally, based on the 18 intervals used to test the results, it showed the improvement of the developed models results compared to HCM2016 models.
    Keywords: Weaving Segment, Density, Lane-Changing Rate, Regression Model, Weaving Vehicles, Non-Weaving Vehicles, Highway Capacity Manual
  • S. Asleshirin, H. Mazaheri *, M. R. Omidkhah Nasrin, A. Hassani Joshaghani
    Ionic Liquid(IL)now refers to fluids that are liquid at temperatures above 100°C, they are called "Green"solvents.One of their applications is in heat transfer and solar collectors.Thermophysical properties can be improved by adding nanoparticles to the IL.For this reason,spherical and rod-shaped alumina nanoparticles were added to 1-Hexyl-3-methyl imidazolium hexafluorophosphate IL with different weight percentages. The effect of adding nanoparticles on thermophysical properties of IL such as density,viscosity,thermal conductivity, and heat capacity in 0.05,0.1 and 0.5 %wt of nanoparticles at temperatures of 20, 30, and 50 °C is investigated. Increasing the concentration of nanoparticle set out an increase in density, viscosity, and thermal conductivity and a decrease in the thermal capacity of the ionic nanofluid (INF) compared to the base IL.Also, the viscosity, density, and thermal conductivity in INF with rod-shaped alumina nanoparticles are improved more than spherical alumina nanoparticles. Also the experimental viscosity and thermal conductivity data were fitted with the existing theoretical models. the viscosity of spherical alumina-IL and rod-shape alumina-IL was in unison with particles aggregation effect (Krieger-Dougherty model) and the both INF effective thermal conductivity are prognosticated by interfacial layer approach with sufficient accuracy.Eventually nonlinear equations have also been proposed for changes in the thermophysical properties of viscosity.
    Keywords: Alumina Nanoparticles, Thermal Conductivity Coefficient, Density, Heat Capacity, Ionic Liquids
  • بهزاد زمانی دهکردی *، زهره نکویی شهرکی
    ترکیب طبقه بندها، یک روش موثر در یادگیری ماشینی است که در آن با ترکیب نتایج چند طبقه بند سعی می گردد تقریب بهتری از یک طبقه بند بهینه فراهم شود. برای آنکه ترکیب نتایج طبقه بندها مفید واقع شود باید طبقه بندهای پایه ضمن برخورداری از کارایی قابل قبول، دارای خطاهای متفاوتی باشند. همچنین بایستی قاعده مناسبی برای ترکیب خروجی طبقه بندهای پایه به کار گرفته شود. روش های متعدد ترکیب طبقه بندها ارائه شده است که می توان به روش های کیسه کردن، رای گیری و روش تقویتی اشاره نمود. در این مقاله یک روش برای ترکیب نتایج طبقه بندها پیشنهاد شده است که در مرحله ترکیب طبقه بندهای پایه از جمع وزن دار خروجی طبقه بندها استفاده شده است. وزن ها با استفاده از الگوریتم ژنتیک چندهدفه با بهینه سازی هم زمان چهار معیارهای خطای طبقه بندی، پراکندگی، گوناگونی و تراکم تخمین زده می شوند. نتایج آزمایش ها روی مجموعه دادگان UCI نشان داد که روش پیشنهادی باعث افزایش دقت سیستم طبقه بندی ترکیبی نسبت به دیگر روش های متداول ترکیب می شود.
    کلید واژگان: ترکیب طبقه بندها، الگوریتم ژنتیک چندهدفه، خطای طبقه بندی، پراکندگی، گوناگونی، تراکم
    B. Zamani Dehkordi *, Z. Nekouei
    Ensemble classifier is an effective method in machine learning that attempted to provide a better approximation of an optimal classifier with combination of some classifiers results. To achieve better performance, the base classifiers should have acceptable efficiency and different classification error, also a suitable method used to combine their results. Various ensemble classification methods such as bagging, voting and strengthening methods have been presented. In this paper, we proposed the ensemble classifier based on weighted mean of the base classifiers output. The weights were estimated using a multi-objective genetic algorithm with taking classification error, sparsity, diversity and density criterion. The results of implementations on UCI datasets show that the proposed method causes more increasing classification accuracy related to other traditional ensemble classifiers.
    Keywords: Ensemble classifier, Multi, objective genetic algorithm, classification error, sparsity, diversity, Density
  • Mohammad A. Feizi Chekab, Parviz Ghadimi *
    The use of ferrofluids as shapeable external appendage to a submerged body and as a mean of vortex flow induction is studied in this paper. Ansys-CFX numerical results are validated against analytical problems and used to analyze the ferrofluid free surface shape affected by gravity, different magnets and different densities of the surrounding non-magnetic fluids. It is demonstrated that the height, width, and curvature of ferrofluid can be controlled by magnet size and strength. It is also observed that ferrofluid mass loss may occur due to gravity which should be addressed in designing a fluid appendage. Subsequently, vortex production inside the ferrofluid is investigated via a shear flow on the magnet. It is shown that ferrofluid can contain complex vortices while being shaped by the magnetic field, gravity, and the vortices. It is also observed that vortices inside the ferrofluid affect the flow of the surrounding fluid. Additionally, the effects of surface tension and viscosity are briefly analyzed to roughly show the importance of these parameters for further works. Overall, it is concluded that using ferrofluids as appendages for shaping and controlling fluid flow around submerged bodies seem to be practical and needs further attention.
    Keywords: Ferrofluid, Density, Shape, Vortex, numerical simulation
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