نتایج جستجو برای: support vector machine

تعداد نتایج: 1028308  

Journal: :تحقیقات مالی 0
سعید فلاح پور استادیار، مدیریت مالی، دانشگاه تهران، ایران غلامحسین گل ارضی استادیار، مدیریت مالی، دانشگاه سمنان، سمنان، ایران ناصر فتوره چیان کارشناس ارشد، mba گرایش مدیریت مالی، دانشگاه سمنان، سمنان، ایران

according to recent developments of predicting methodsin financial markets, and since the stock price is one of the mostimportant factors for investment decision-making, and its predictioncan play an important role in this field, the aim of this study is toprovide a model to predict the stock price movement with highaccuracy. accordingly, a hybrid model for predicting the stock pricemovement us...

Accurate simulation runoff process can have a significant role in water resources management and related issues. The inherent complexity of  this process makes difficult the use of physical and numerical models. In recent years, application of intelligent models is increased a powerful tool in hydrological modeling. The aim of this study was the application of the Gamma test to select the optim...

سید علی عظیمی محسن شفیعی نیک آبادی

Abstract—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models. In next step, the modeling step, an artificial neural network and support vector machine is presented. The structure of artificial neural network is selected based on previous researchers' results. For ...

Amir Hossein Hashemian, Daryoush Afshari, Nader Salari, Sara Manochehri, Soodeh Shahsavari, Zohreh Manochehri,

Background: Multiple sclerosis (MS) is a degenerative inflammatory disease which is most commonly diagnosed by magnetic resonance imaging (MRI). But, since the MRI device uses of a magnetic field, if there are metal objects in the patient's body, it can disrupt the health of the patient, the functioning of the MRI, and distortion in the images. Due to limitations of using MRI device, screening ...

ژورنال: علوم آب و خاک 2019

Land use/cover maps are the basic inputs for most of the environmental simulation models; hence, the accuracy of the maps derived from the classification of the satellite images reduces the uncertainty in modeling. The aim of this study was to assess the accuracy of the maps produced by machine learning based on classification methods (Random Forest and Support Vector Machine) and to compare th...

Journal: :amirkabir international journal of modeling, identification, simulation & control 2014
m.h. ranjbar jaferi s.m.a. mohammadi m. mohammadian

based on the problems caused by today conventional vehicles, much attention has been put on the fuel cell vehicles researches. however, using a fuel cell system is not adequate alone in transportation applications, because the load power profile includes transient that is not compatible with the fuel cell dynamic. to resolve this problem, hybridization of the fuel cell and energy storage device...

2011
Sascha Klemenjak Björn Waske

To segment a image with strongly varying object sizes results generally in under-segmentation of small structures or over-segmentation of big ones, which consequences poor classification accuracies. A strategy to produce multiple segmentations of one image and classification with support vector machines (SVM) of this segmentation stack afterwards is shown.

2001
Grace Wahba Yi Lin Yoonkyung Lee Hao Zhang

We rederive a form of Joachims’ ξα method for tuning Support Vector Machines by the same approach as was used to derive the GACV, and show how the two methods are related. We generalize the ξα method to the nonstandard case of nonrepresentative training set and unequal misclassification costs and compare the result to the GACV estimate for the standard and nonstandard cases.

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