نتایج جستجو برای: neural fuzzyinterface
تعداد نتایج: 302530 فیلتر نتایج به سال:
Multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE), are chronic inflammatory demyelinating disorders of central nervous system (CNS). While the cause is unclear, the fundamental mechanism is thought to be destruction of myelin sheaths of neurons through immune system. One of the approaches being proposed in EAE therapy is neural stem cells (NSCs) trans...
Introduction: Acute appendicitis is one of the most common causes of emergency surgery especially in children. Proper and on-time diagnosis may decrease the unwanted complications. In despite of diagnostic methods, a significant number of patients yet and up with negative laparotomies. The aim of this study was to assess the role of artificial neural networks in diagnosis of acute appendicitis ...
This paper presents a feed forward back-propagation neural network model to predict the retained tensile strength and design chart in order to estimation of the strength reduction factors of nonwoven geotextiles due to installation process. A database of 34 full-scale field tests were utilized to train, validate and test the developed neural network and regression model. The results show that t...
Introduction: cardiovascular diseases are becoming the main cause of mortality and morbidity in most countries. This research goal was to predict the types of heart diseases for more accurate diagnosis by data mining and neural network technics. Method: This research was an applied-survey study and after data preprocessing, three approaches of neural network, decision making tree and Bayes simp...
The accurate determination of river flow in watersheds without sufficient data is one of the major challenges in hydrology. In this regard, given the diversity of existing hydrological models, selection of an appropriate model requires evaluation of the performance of the hydrological models in each region. The objective of this study was to compare the performance of artificial neural network ...
A new iterative learning controller is proposed for a general unknown discrete time-varying nonlinear non-affine system represented by NARMAX (Nonlinear Autoregressive Moving Average with eXogenous inputs) model. The proposed controller is composed of an iterative learning neural identifier and an iterative learning controller. Iterative learning control and iterative learning identification ar...
when a vehicle travels on a road, different parts of vehicle vibrate because of road roughness. this paper proposes a method to predict road roughness based on vertical acceleration using neural networks. to this end, first, the suspension system and road roughness are expressed mathematically. then, the suspension system model will identified using neural networks. the results of this step sho...
abstract biometric access control is an automatic system that intelligently provides the access of special actions to predefined individuals. it may use one or more unique features of humans, like fingerprint, iris, gesture, 2d and 3d face images. 2d face image is one of the important features with useful and reliable information for recognition of individuals and systems based on this ...
abstract forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. this paper studies load consumption modeling in hamedan city province distribution network by applying esn neural network. weather forecasting data such as minimum day temperature, average day temp...
a two-variable integrate and fire model is presented to study the role of transient outward potassium currents in producing temporal aspects of dorsal cochlear nucleus (dcn) pyramidal cells with different profiles namely the chopper, the pauser and the buildup. this conductance based model is a reduced version of km-lif model (meng & rinzel, 2010) which captures qualitative firing features of a...
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