راحیل حسینی

[ 1 ] - به‎‎کارگیری تکنیک‎های دسته‎بندی ترکیبی رأی‎گیری با توافق سطح بالا برای تفکیک بیماری التهاب روده

به‎دلیل پیچیدگی تصمیمات پزشکی، کاربرد سیستم‎های هوشمند برای پشتیبانی از این تصمیمات افزایش یافته است. در این پژوهش از قابلیت پنج الگوریتم مختلف ماشین بردار پشتیبان، درخت تصمیم‎گیری، نایو بیزین، نزدیک‎ترین همسایه و جنگل تصادفی، یک دسته‎بند ترکیبی ساخته شده که برای به‎دست آوردن نتیجۀ آرای این دسته‎بند، از رویکرد رأی‎گیری با توافق سطح بالا به‎منظور ارزیابی و پیش‎بینی استفاده می‎شود. با توجه به اهم...

[ 2 ] - A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children

Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to e...

[ 3 ] - A Survey of Concurrency Control Algorithms in the Operating Systems

Concurrency control is one of the important problems in operation systems. Various studies have been reported to present different algorithms to address this problem, although a few attempts have been made to represent an overall view of the characteristics of these algorithms and comparison of their capabilities to each other. This paper presents a survey of the current methods for controlling...

[ 4 ] - A Fuzzy-GA Approach for Parameter Optimization of A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children

Hybrid fuzzy expert systems are one of the most practical intelligent paradigm of soft computing techniques with the high potential for managing uncertainty associated to the medical diagnosis. The potential of genetic algorithm (GA) by inspiring from natural evolution as a learning and optimization technique has been vastly concentrated for improving fuzzy expert systems. In this paper, the GA...

[ 5 ] - Novel Hybrid Fuzzy-Evolutionary Algorithms for Optimization of a Fuzzy Expert System Applied to Dust Phenomenon Forecasting Problem

Nowadays, dust phenomenon is one of the important challenges in warm and dry areas. Forecasting the phenomenon before its occurrence helps to take precautionary steps to prevent its consequences. Fuzzy expert systems capabilities have been taken into account to assist and cope with the uncertainty associated to complex environments such as dust forecasting problem. This paper presents novel hyb...

[ 6 ] - A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children

Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to e...

[ 7 ] - A Survey of Concurrency Control Algorithms in the Operating Systems

Concurrency control is one of the important problems in operation systems. Various studies have been reported to present different algorithms to address this problem, although a few attempts have been made to represent an overall view of the characteristics of these algorithms and comparison of their capabilities to each other. This paper presents a survey of the current methods for controlling...

[ 8 ] - A Fuzzy Rule-based Expert System for the Prognosis of the Risk of Development of the Breast Cancer

Soft Computing techniques play an important role for decision in applications with imprecise and uncertain knowledge. The application of soft computing disciplines is rapidly emerging for the diagnosis and prognosis in medical applications. Between various soft computing techniques, fuzzy expert system takes advantage of fuzzy set theory to provide computing with uncertain words. In a fuzzy exp...

[ 9 ] - Soft Computing Methods based on Fuzzy, Evolutionary and Swarm Intelligence for Analysis of Digital Mammography Images for Diagnosis of Breast Tumors

Soft computing models based on intelligent fuzzy systems have the capability of managing uncertainty in the image based practices of disease. Analysis of the breast tumors and their classification is critical for early diagnosis of breast cancer as a common cancer with a high mortality rate between women all around the world. Soft computing models based on fuzzy and evolutionary algorithms play...

[ 10 ] - Novel Hybrid Fuzzy-Evolutionary Algorithms for Optimization of a Fuzzy Expert System Applied to Dust Phenomenon Forecasting Problem

Nowadays, dust phenomenon is one of the important challenges in warm and dry areas. Forecasting the phenomenon before its occurrence helps to take precautionary steps to prevent its consequences. Fuzzy expert systems capabilities have been taken into account to assist and cope with the uncertainty associated to complex environments such as dust forecasting problem. This paper presents novel hyb...

[ 11 ] - A Novel Fuzzy-Genetic Differential Evolutionary Algorithm for Optimization of A Fuzzy Expert Systems Applied to Heart Disease Prediction

This study presents a novel intelligent Fuzzy Genetic Differential Evolutionary model for the optimization of a fuzzy expert system applied to heart disease prediction in order to reduce the risk of heart disease. To this end, a fuzzy expert system has been proposed for the prediction of heart disease. The proposed model can be used as a tool to assist physicians. In order to: (1) tune the para...