-
مقاله
1 - Classification of Brain Tumor Grades by MRI Images using Artificial Neural NetworkJournal of Computer & Robotics , شماره 18 , سال 12 , بهار 2019In recent years, the use of MRI images has been very much considered due to their high clarity and high quality in the diagnosis and determination of brain tumor and its features. In this study, to improve the performance of tumor detection, we investigated comparative چکیده کاملIn recent years, the use of MRI images has been very much considered due to their high clarity and high quality in the diagnosis and determination of brain tumor and its features. In this study, to improve the performance of tumor detection, we investigated comparative approach of the different classifiers to select the most appropriate classifier for identifying and extracting abnormal tissue and selected the best one by comparing their detection accuracies rate. In this research, GLCM and GLRM methods are used to extracting discriminating features. Thus results in they reduce the computational complexity. fuzzy entropy measurement method is used to determine the optimal properties and finally, we compared the four FFNN, MLP, BPNN, ANFIS neural networks to perform the decision making and classification process. The purpose of these four neural networks are to develop tools for discriminating the malignant tumors from benign ones assisting deciding in clinical diagnosis. Based on the results, we achieved high results among all classifiers. The proposed methodology results in accurate and speedy detection of tumor in brain along with identification of precise location of the tumor. In our opinion, the use of these classifiers can be very useful in the diagnosis of brain tumors in MRI images. Our other goal is to prove the suitability of the ANN method as a valuable method for statistical methods. The novelty of the paper lies in the implementation of the proposed method for discriminating the malignant tumors from benign which results in accurate and speedy detection of tumor in brain along with identification of precise location of the tumor. The efficiency of the method is proved through plenty of simulations and comparisons. پرونده مقاله -
مقاله
2 - Optimization of the DFIG Wind Turbine Controller Parameters by the Gray Wolf AlgorithmJournal of Computer & Robotics , شماره 22 , سال 14 , بهار 2021The increase in the power generated by the wind hashad effects on the performance of the power system incases such as power quality, safety, stability, andvoltage control. The wind turbines are used to generateelectrical energy from wind. They can work in fixedor variab چکیده کاملThe increase in the power generated by the wind hashad effects on the performance of the power system incases such as power quality, safety, stability, andvoltage control. The wind turbines are used to generateelectrical energy from wind. They can work in fixedor variable speeds. The asynchronous generator isdirectly connected to the grid for the fixed-speed windturbines. In order to connect the DFIG (Doubly-FedInduction Generator) to the grid, this machine must beable to integrate its generated power into the grid in aspecific voltage (the grid voltage level). The mainDFIG controlling method is the use of field-orientedvector control for regulating the rotor flux. The DFIGvector control consists of two main parts as grid sideconverter control and rotor side converter control. Therotor side converter is used to control the grid outputpower. This converter regulates the power factors inthe terminals, and actually restores the generatedpower deviation from the reference power through thePID controllers, besides guaranteeing the stability ofthe induction generator. In the current study, the powerwas controlled through the determination of the PIDoptimal coefficient of the rotor and grid sidescontrollers and the gray wolf algorithm in theMATLAB software. In addition, the stability of thesmall signal of the grid equipped with the doubly-fedwind generator in the wind speed turbulenceconditions was optimized to satisfy the requiredcriteria in output active and reactive power of a DFIG.From the simulation results it is observed that theproposed controller yields better results whencompared to other methods in literature in terms ofperformance index. پرونده مقاله -
مقاله
3 - پیش بینی بازار سهام با استفاده از مدل ترکیبی شبکه عصبی LSTMاقتصاد مالی , مقالات زودآیندپیش بینی قیمت و بازده سهام یکی از پیچیده ترین و بحث برانگیزترین موضوعات در بازارهای مالی است که همواره مورد توجه سرمایه گذاران و سهامداران میباشد. بازار سهام در برابر عوامل مختلفی آسیب پذیر است که بر نوسانات قیمت در بازار بورس تأثیر می گذارد. توسعه یک الگوریتم قوی بازا چکیده کاملپیش بینی قیمت و بازده سهام یکی از پیچیده ترین و بحث برانگیزترین موضوعات در بازارهای مالی است که همواره مورد توجه سرمایه گذاران و سهامداران میباشد. بازار سهام در برابر عوامل مختلفی آسیب پذیر است که بر نوسانات قیمت در بازار بورس تأثیر می گذارد. توسعه یک الگوریتم قوی بازار سهام که بتواند رفتار سهام را به دقت پیشبینی کند، برای به حداکثر رساندن سود و به حداقل رساندن ضرر سرمایهگذار، مورد نیاز است. با توجه به اینکه علاوه بر تاریخچه هر سهم، عوامل روانی بازار نیز بر ارزش هر سهم تاثیر می گذارد، در این تحقیق یک مدل ترکیبی هوش مصنوعی بر اساس LSTM و تعبیه متن پیشنهاد میشود که هم بر سابقه بازار سهام در قالب دادههای سری زمانی توجه دارد، و هم ویژگیهای روانی بازار را از سایتهای خبری استخراج میکند و آینده بازار سهام را پیش بینی میکند. نتایج ارزیابیها نشان میدهد مدل پیشنهادی میتواند به خوبی آینده بازار را پیشبینی نماید و نسبت به روشهای پروفت و آریما دارای میانگین مربعات خطای کمتری است. پرونده مقاله -
مقاله
4 - طراحی کنترل کننده و رویتگر مبتنی بر پسیویتی برای یک کلاس از سیستمهای غیرخطی با کاربرد در بیماری هپاتیت بیسیستم های پویای کاربردی و کنترل , شماره 1 , سال 7 , زمستان 1402In this paper, a strictly passive formulation has been developed to design a passive state-observer for both time-invariant and time-varying Lipschitz nonlinear systems. During this formulation, a convergence and strictly passive state-observer is provided to have passi چکیده کاملIn this paper, a strictly passive formulation has been developed to design a passive state-observer for both time-invariant and time-varying Lipschitz nonlinear systems. During this formulation, a convergence and strictly passive state-observer is provided to have passive closed-loop system. Some definitions and charts are defined here for time-invariant and time-varying systems in different scenarios. A new interconnection between passivity of subsystems and passivity/stability of the closed-loop system has been introduced from a different point of view. All definitions are organized based on the systematic method called “virtually Euler-Lagrange” form of passivation. Utilizing this form and theses definitions, make the design process simpler and straightforward, while, some conditions of design will be released due to using these definitions. The designed controller/observer has been applied to control the hepatitis B virus infection disease. The reliability of the proposed definitions are examined by using MATLAB/SIMULINK, while, the results demonstrate the ability and power of this novel approach. پرونده مقاله