نتایج جستجو برای: bayesian network

تعداد نتایج: 731163  

‎The most challenging task in dealing with Bayesian networks is learning their structure‎. ‎Two classical approaches are often used for learning Bayesian network structure;‎ ‎Constraint-Based method and Score-and-Search-Based one‎. ‎But neither the first nor the second one are completely satisfactory‎. ‎Therefore the heuristic search such as Genetic Alg...

Background: The stress is one of main factors effects on production system. Several factors (both genetic and environmental elements) regulate immune response to stress. Objectives: In order to determine the major immune system regulatory genes underlying stress responses, a learning Bayesian network approach for those regulatory genes was applied to RNA-...

خرمیان طوسی, دکتر سمیه, زینلی, بهنام,

 Introduction: Dentists have to choose a precise treatment plan based on the prevailing sign symptoms gathered from patients. However; in most of cases, the symptoms are complicate which makes the lack of confidence for the dentist to find an accurate treatment plan. This study introduces a new diagnosis system that helps the dentists and students to choose an accurate course of treatment ...

The future of development and design is impossible without study of Power Flow(PF), exigency the system outcomes load growth, necessity add generators, transformers and power lines in  power system. The urgency for Optimal Power Flow (OPF) studies, in addition to the items listed for the PF and in order to achieve the objective functions. In this paper has been used cost of generator fuel, acti...

Introduction: The identification of asthma risk factors plays an important role in the prevention of the asthma as well as reducing the severity of symptoms. Nowadays, the identification process can be performed using modern techniques. Data mining is one of the techniques which has many applications in the fields of diagnosis, prediction, and treatment. This study aimed to identify the effecti...

Journal: :Theoretical Computer Science 2020

2014
Roy Levy

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2014
Tanja Käser Severin Klingler Alexander G. Schwing Markus H. Gross

Modeling and predicting student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for student modeling is Bayesian Knowledge Tracing (BKT). BKT models, however, lack the ability to describe the hierarchy and relationships between the different skills of a learning domain. In this work, we therefore aim at increasing the representational power of the student m...

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