Neuro fuzzy system for the classification of Endocrine Myopathy diseases at second level

نویسنده

  • Heena
چکیده

Intelligent systems for the diagnosis and classification of Endocrine Myopathy (EM) plays very significant role in the medical field. Neuro-fuzzy system is refers to combinations of artificial neural networks and fuzzy logic, in which fuzzy system works like human reasoning and the learning structure of neural networks. The plan of this paper is to present the Neuro-fuzzy system for the classification of Endocrine Myopathy diseases at second level. Neuro-fuzzy system has advantage to reduce the number of rules and decrease computational time, learns faster.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Adaptive Neuro-Fuzzy Inference System application for hydrothermal alteration mapping using ASTER data

The main problem associated with the traditional approach to image classification for the mapping of hydrothermal alteration is that materials not associated with hydrothermal alteration may be erroneously classified as hydrothermally altered due to the similar spectral properties of altered and unaltered minerals. The major objective of this paper is to investigate the potential of a neuro-fuz...

متن کامل

Coastal Water Level Prediction Model Using Adaptive Neuro-fuzzy Inference System

This paper employs Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict water level that leads to flood in coastal areas. ANFIS combines the verbal power of fuzzy logic and numerical power of neural network for its action. Meteorological and astronomical data of Santa Monica, a coastal area in California, U. S. A., were obtained. A portion of the data was used to train the ANFIS network, wh...

متن کامل

Adaptive Network-based Fuzzy Inference System-Genetic Algorithm Models for Prediction Groundwater Quality Indices: a GIS-based Analysis

The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...

متن کامل

Determination of water quality parameters and nutrient level with an Adaptive Neuro- Fuzzy Inference System

In this research, the physico-chemical water quality parameters and the effect of climate changes onwater quality is evaluated. During the observation period (5 months) physico-chemical parameterssuch as water temperature, turbidity, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity,conductivity, and concentration of total nitrogen (nutrient level) as main pollutant factor have be...

متن کامل

A New Structure for Direct Measurement of Temperature Based on Negative Temperature Coefficient Thermistor and Adaptive Neuro-fuzzy Inference System

Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating p...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014