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[PDF] Top 20 Date Fruits Classification using MLP and RBF Neural Networks

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Date Fruits Classification using MLP and RBF Neural Networks

Date Fruits Classification using MLP and RBF Neural Networks

... a neural prototypical computer vision system to speed up the process of date grading and sorting as well as maintain the consistency and ...automatic classification process of date, all ... See full document

6

Usage Surface Deflection Data for Performance Prediction in Flexible Pavement

Usage Surface Deflection Data for Performance Prediction in Flexible Pavement

... analyzed using multi layers perceptron (MLP) and radial basis function (RBF) neural ...These neural networks were optimized by levenberg-marquardt (MLP-LM), scaled ... See full document

22

Artificial Intelligence Tools Aided decision for Power Transformer Fault Diagnosis

Artificial Intelligence Tools Aided decision for Power Transformer Fault Diagnosis

... faults classification using the dissolved gas analysis for power ...functions), neural networks (MLP and RBF) and Support Vector Machine (with polynomial and Gaussian kernel ... See full document

8

FRICTION MODELING OF Al-Mg ALLOY SHEETS BASED ON MULTIPLE REGRESSION ANALYSIS AND NEURAL NETWORKS

FRICTION MODELING OF Al-Mg ALLOY SHEETS BASED ON MULTIPLE REGRESSION ANALYSIS AND NEURAL NETWORKS

... ficial neural networks (ANNs) which allows us to overcome the difficulty arising in the assess- ment of the complex relationships that is estab- lished based on empirical analytical models and is based on ... See full document

10

NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM

NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM

... (MLP) neural networks, although other tools such as radial basis function (RBF) networks can be ...the classification module we use sup- port vector machines (SVMs)—here also ... See full document

32

Reducing Error Signal in Multilayer Perceptron Neural Networks using MLP for Label Ranking

Reducing Error Signal in Multilayer Perceptron Neural Networks using MLP for Label Ranking

... Abstract: - This paper describes a simple tactile probe for identifying error signal in Multilayer. In multilayer having the number of hidden layers error signal can be process as irrespective manner so difficult to find ... See full document

15

A Novel Compressed Deep Stacking Neural Network Based Classifier for the Monitoring and Classification of Multiple Power Quality Disturbances

A Novel Compressed Deep Stacking Neural Network Based Classifier for the Monitoring and Classification of Multiple Power Quality Disturbances

... Detection and classification of single and combined power quality disturbances using neural 566. networks[r] ... See full document

26

Soft Computing Techniques for Mishaps Prediction

Soft Computing Techniques for Mishaps Prediction

... for classification of the given set of data and it is the same set of data used for ...(MLP) neural network topology is used in the analysis of behaviour of ...a classification point of view ... See full document

7

Classification of Diospyros Lotus Seeds Based on MLP Neural Network

Classification of Diospyros Lotus Seeds Based on MLP Neural Network

... Therefore, in this paper we propose a system for diospyros lotus seeds identification. We focus on analyzing visual features such as color features and shape features for efficient representation of seed images. Then we ... See full document

6

Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling

Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling

... artificial neural network (ANN) is determined by the number of layers in the hidden network, the number of the neurons in each layer, and the nature of the transfer ...different networks were created and ... See full document

11

Image Segmentation and Edge Detection Using a Neural Networks RBF Approach

Image Segmentation and Edge Detection Using a Neural Networks RBF Approach

... 2. Hidden layer – This layer has a variable number of neurons (the optimal number is determined by the training process). Each neuron consists of a radial basis function centered on a point with as many dimensions as ... See full document

6

Optimal Portfolio Allocation based on two Novel Risk Measures and Genetic Algorithm

Optimal Portfolio Allocation based on two Novel Risk Measures and Genetic Algorithm

... modes using the genetic ...obtained using the subtraction of price predicted by the neural network for each share for the next 5 days and the current ... See full document

19

Image classification using Hybrid MLP method

Image classification using Hybrid MLP method

... of neural network and support vector machine. For the classification of the images we use support vector machines as a classifier and after applying this classification process for the features ... See full document

8

Motor Learning Based on the Cooperation of Cerebellum and Basal Ganglia for a Self Balancing Two Wheeled Robot

Motor Learning Based on the Cooperation of Cerebellum and Basal Ganglia for a Self Balancing Two Wheeled Robot

... A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning ... See full document

12

Data Mining using Neural Networks

Data Mining using Neural Networks

... the neural networks can be used for maintaining and exploring new data sciences in order to provide encouraging frameworks in managing infinite volumes of data we have at our ...and neural ... See full document

6

Recognizing Handwritten Alphabets using Neural Networks

Recognizing Handwritten Alphabets using Neural Networks

... The second step of the recognition system is to process the image file acquired in the first step. This process is crucial to the whole system as it affects the accuracy as well as efficiency of the system. In this ... See full document

5

Adaptive Control OF Nonlinear Multivariable Dynamical Systems Using MRAN-RBF Neural Networks

Adaptive Control OF Nonlinear Multivariable Dynamical Systems Using MRAN-RBF Neural Networks

... many total training observations will be presented. A significant contribution to sequential learning was made by Platt [5] by proposing RAN in which hidden neurons were added sequentially based on the novelty of the new ... See full document

9

THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED 
ONSIDERATION

THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION

... any classification model. For effective classification, the extracted features should give valuable information about the categories, and it should be inexpensive in terms of computation [4, ...page ... See full document

7

Performance Evaluation of Data Mining based Classifier for Classification of Spam E Mail

Performance Evaluation of Data Mining based Classifier for Classification of Spam E Mail

... Abstract: E-mail is one of the important and economical communication media to transfer the information from one person to others. Due to increase number of E-mails resulted drastic increases spam E-mail. In this ... See full document

6

Speech emotion classification using SVM and MLP on prosodic and voice quality features

Speech emotion classification using SVM and MLP on prosodic and voice quality features

... 53.22%. Using the same database, [9] compared there proposed classifier, the Gausian Mixture Autoregressive Model, with HMM, KNN and ...a classification accuracy of 76%, versus 71% for the Hidden Markov ... See full document

7

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