نتایج جستجو برای: کنترل ANFIS
تعداد نتایج: 89192 فیلتر نتایج به سال:
در این مقاله استراتژی کنترل بهینه ساختمانهای مجهز به میراگر mr با استفاده از شبکه عصبی فازی anfis ارائه گشته است. ابتدا یک تابعک هدف (j) پیشنهاد گشته و از معادلات دینامیکی سازه به همراه میراگر mr به عنوان قیود آن استفاده گردیده است. با حداقل کردن این تابعک هدف، تاریخچه زمانی بهینه ولتاژهای اعمالی به میراگرها بدست آورده شده است. از این ولتاژها و پاسخهای سازه¬ای متناظر، برای آموزش anfis استفاده ش...
This paper presents novel GA-ANFIS expert system prototype for dermatological disease detection by using dermatological features and diagnoses collected in real conditions. Nine dermatological features are used as inputs to classifiers that are based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for the first level of fuzzy model optimization. After that, they are used as inputs in Genetic ...
در این مقاله ابتدا مدل خطی سیستم تعلیق خودرو انتخاب و شبیهسازی و دادههای لازم جهت آموزش از آن استخراج میگردد. در راستای تحقق هدف سیستم تعلیق، با استفاده از روشهای مرسوم یک کنترلکننده pid برای سیستم تعلیق طراحی و از آن جهت آموزش کنترلکننده تطبیقی عصبی - فازی (anfis) استفاده شود. این سیستم anfis با استفاده از خطای خروجی کنترلکننده pid به صورت بر خط آموزش میبیند و پس از آموزش، کنترلکننده...
This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electroencephalogram (EEG) signals. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of EEG signals were us...
Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensib...
In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes. The ANFIS uses a hybrid learning algorithm. The ANFIS is a class of adaptive networks that is functionally equivalent to fuzzy inference systems (FIS). The ANFIS is based on neuro-fuzzy model, trained wit...
This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering (ANFIS-FCM) and M5 model tree (M5Tree), for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer...
Prediction of student’s performance is potentially important for educational institutions to assist the students in improving their academic performance, and deliver high quality education. Developing an accurate student’s performance prediction model is challenging task. This paper employs the Adaptive NeuroFuzzy Inference system (ANFIS) for student academic performance prediction to help stud...
In this study, a new approach based on adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of internal carotid artery stenosis and occlusion. The internal carotid arterial Doppler signals were recorded from 130 subjects that 45 of them suffered from internal carotid artery stenosis, 44 of them suffered from internal carotid artery occlusion and the rest of them were health...
In this paper a pose invariant face recognition using neuro-fuzzy approach is proposed. Here adaptive neuro fuzzy interface system (ANFIS) classifier is used as neuro-fuzzy approach for pose invariant face recognition. In the proposed approach the preprocessing of image is done by using adaptive median filter. It removes the salt pepper noise from the original images. From these denoised images...
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