backpropagation-trained neural network
Stock Market Prediction Model by Combining Numeric and News Textual Mining
... II. Backpropagation Algorithm in Neural Network [6] The study used three-layer (one hidden layer) multilayer feed- forward neural network model trained with ...
7
Weather prediction using Neural Network Backpropagation
... using Neural Network Backpropagation (BPP) for quantitative prediction of Rainfall ...of Neural Network backpropagation is built on N different attributes as input ...is ...
6
APPLICATION OF CELLULAR AUTOMATA FOR MODELING AND REVIEW OF METHODS OF MOVEMENT OF A GROUP OF PEOPLE
... for backpropagation network, then they used back propagation neural network, after that they trained and tested the network using optimal weights of the best fit chromosome, to ...
13
Machine learning in Dynamic Adaptive Streaming over HTTP (DASH)
... Artificial neural networks can be employed to solve a wide spectrum of problems in optimization, parallel computing, matrix algebra and signal processing ...the backpropagation algorithm (BA), the ...
8
Artificial Neural Networks A Review of Applications of Neural Networks in the Modeling of HIV Epidemic
... The authors concluded that the MLP network trained using backpropagation algorithm produced the best performance with 89.80% accuracy as compared to Levenberg-Marquardt and Bayesian rule[r] ...
9
The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks
... through neural networks is composed of three steps: gambling data analysis, neural network training with backpropagation, and knowledge extraction using ...Then, network training is ...
9
Performance Comparison of Featured Neural Network Trained with Backpropagation and Delta Rule Techniques for Movie Rating Prediction in Multi-criteria Recommender Systems
... the network models to work faster and more efficiently, the numerically trans- formed dataset was normalized to real numbers between 0 and 1 through dividing each of the modified ratings by 13 (since 13 is the ...
6
Neural Networks For Financial Time Series
... the network can learn to infer the relationship that binds ...the network is trained via an appropriate algorithm (usually backpropagation that is a supervised learning algorithm) that uses ...
6
Backpropagation Neural Network Experiment on Human Face Recognition
... Artificial Neural Network (ANN) experiments, the system of face recognition consists of image preprocessing, image segmentation, detection and feature extraction, localization and normalization and ...and ...
6
A subjective job scheduler based on a backpropagation neural network
... the neural network is an elementary information-processing ...artificial neural network, first it is to be decided how many neurons are to be used and how the neurons are to be connected to ...
15
Daily Network Traffic Prediction Based on Backpropagation Neural Network
... the network, there are 1 to 144 groups of data selected as the study samples, the 145 to 192 groups as the test samples and using the trained BPNN to ...
6
A PROFICIENT LOW COMPLEXITY ALGORITHM FOR PREEMINENT TASK SCHEDULING INTENDED FOR HETEROGENEOUS ENVIRONMENT
... prediction. Backpropagation Neural Network (BPNN) and correlation feature selection are applied in order to predict ERC which is trained and tested using 10-fold ...
5
Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning
... the neural network was created, trained, validated, and tested on the calibration data, in a further step, it was tested on our data set of clinical data (described in detail above under the “Data” ...
23
Backpropagation Neural Network Based on Local Search Strategy and Enhanced Multi-objective Evolutionary Algorithm for Breast Cancer Diagnosis
... In this study, the combination of a local search scheme and enhanced NSGA-II based on BP algorithm for the classification of the Breast Cancer diagnosis implemented and done successfully. The fundamental notion of the ...
7
Photonic Delay Systems as Machine Learning Implementations
... recurrent network with a fixed, specific con- nection matrix between the hidden states at different time ...that backpropagation can currently only leverage the recurrence of the system to a limited de- ...
17
Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World
... artificial neural networks that uses supervised learning that is popular and has advantages in its learning abilities ...The backpropagation algorithm is used for training. The backpropagation ...
6
Date Fruits Classification using MLP and RBF Neural Networks
... artificial neural networks ...of neural networks have been applied as classifiers: multi-layer perceptron (MLP) with backpropagation and radial basis function RBF ...the neural network ...
6
Intelligent Object and Pattern Recognition using Ensembles in Back Propagation Neural Network
... the Neural Network research community today. Neural networks are mostly preferred in predictive and classification problems because they are unstable classifier that is little change in input causes ...
8
Development of a Genetic based Neural Network System for Online Character Recognition
... Hence, a significant reduction in the time period was achieved for the weight adjustment of the hidden layer neurons. C3 is better than the other 2 classifiers (C1 & C2). This is because C3 has dual capabilities of ...
8
Intrusion Detection using Artificial Neural Network and Swarm Intelligence Algorithm
... LIMAM Selma et al. [22] proposed the integration and inflation of Three-Dimensional Periodic Phased Array Antenna using ANN Method. There frequent logical yields are not accessible for complex genuine frameworks, so that ...
9