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A Decision System for Predicting Diabetes using Neural Networks
... veins in retinal photos. They have used the thought of composed station for disclosure of signs and symptoms to recognize piecewise direct parts of veins in retinal images and created 12 one in all a type preparations to ... See full document
10
An Intelligent Control Technique for Dynamic Optimization of Temperature during Fruit Storage Process
... troducing neural networks and genetic ...control system mimicking a simple thinking process of a skilled grower, which is applied for realizing the optimization control of the rate of water loss ...a ... See full document
10
Predicting Diabetes Mellitus Using Artificial Neural Network Through a Simulation Study
... in diabetes and of designing glucose regulators based on model predictive control for the artificial ...patients using data from sensors monitoring blood glucose concentration as well as data from in silico ... See full document
6
Predicting the Collapsibility Potential of Unsaturated Soils Using Adaptive Neural Fuzzy Inference System and Particle Swarm Optimization
... strength using articial neural network modeling [10]; Zorlu and Gokceoglu (2008) dealt with predicting the collapsibility index using a double input fuzzy inference system in the ... See full document
17
Optimal Decision Support System Using Multilayer Neural Networks for Incinerator Control
... Data points of modified Claus plant tail gas incinerator are collected using a simulator. These data points where graphically represented to understand the data. The relationship between the adiabatic stack ... See full document
6
Predicting potential of controlled blasting-induced liquefaction using neural networks and neuro -fuzzy system
... In this study, the ANFIS model was created in three methods of Grid Partitioning (GP), subtrac- tive clustering (SCM), and Fuzzy c-Means cluster- ing (FCM). In GP, every part of premise variables is suggested ... See full document
15
Development of a Neural-Networks Tool-Wear Monitoring System for a Turning Process
... (FF-BP) neural network, a fuzzy-decision support system (FDSS) and an artificial-neural-network-based fuzzy-inference system ...back-propagation neural networks for ... See full document
14
An Efficient Identification of Malnutrition with Unsupervised Classification Using Logical Decision Tree Algorithm
... Techniques—Artificial Neural Networks And Decision Trees [5]: This article demonstrates how a coding system at the meal level might be analyzed by using data mining ...coding ... See full document
5
Applying Advanced NN based Decision Support Scheme for Heart Diseases Diagnosis
... proposed system, which is based on Artificial Neural Networks (ANNs), provides a decision support system to classify the heart diseases: mitral stenosis, aortic stenosis and ventricular ... See full document
5
Learning And Predicting Individual Preferences In Multicriteria Decision Making With Neural Networks Vs. Utility Functions
... ulti-criteria decision making (MCDM) involves making choices on a set of alternatives, taking into consideration many conflicting qualitative and/or quantitative criteria ...individual decision patterns, ... See full document
6
Predicting And Simulating Level Of Diabetes Over The Region Using Complex Networks
... virtual system for the patients suffering from diabetes which analyze all the factor of blood ...this system declare the patient under risk and provide nearby hospital according to geographical ... See full document
5
Classification Techniques for Predicting Graduate Employability
... algorithms, Decision Tree, Support Vector Machines and Artificial Neural Networks are used and being compared for the best ...show decision tree J48 produces higher accuracy compared to other ... See full document
9
Predicting race results using artificial neural networks
... First let us explain why there is need for such a regularization function. For this we need to look at overfitting and overtraining. We will start with a quote, which points out the problem; ”The Nobel prizewinning ... See full document
82
Effective Analysis and Predictive Model of Stroke Disease using Classification Methods
... like Decision tree, Naïve bayes and neural networks is used for predicting stroke diseases and principle component analysis algorithm for reducing the ... See full document
6
DECISION SUPPORT SYSTEM BASED ON SIGNS AND SYMPTOMS USING NEURAL NETWORKS FOR CONGENITAL HEART DISEASE DIAGNOSIS
... diagnostic system for cardiovascular ...neuro-fuzzy system is superior to the INS system using a training data set where the accuracy of each system is 100% and ...However, using ... See full document
6
Data Mining Algorithms in Healthcare
... Prediction System (IHDPS) using data mining techniques, namely, Decision Trees, Naive Bayes and Neural Networks ...expandable system which is implemented on the ... See full document
6
A Framework for Software Defect Prediction Using Neural Networks
... of neural networks is their capability to learn from ...A neural network learns patterns by adjusting its weights. When the neural network is properly trained, it can give correct, or nearly ... See full document
11
Model development of the external friction of granular vegetable materials on the basis of artificial neural networks
... A modified error back-propagation method was used for teaching the network (a method called momentum and an adaptive learning rate have been applied). The number of inputs and outputs was determined by the task the ANN ... See full document
6
Predicting the required duration for construction activities using Artificial Neural Networks
... for predicting of construction activities, aiming to develop a model that can be used to predict the construction duration of major structural elements in the concrete skeleton buildings, scoping the project for ... See full document
28
CHANNEL ESTIMATION OF OFDM BASED SYSTEM USING PILOT ASSISTED NEURAL NETWORKS
... fig, neural network with 5 inputs and 3 neurons in hidden layer and 2 ...forward networks as learning algorithm to update weights and biases of the network when inputs are applied to the ... See full document
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