neural network training set
A Predictive Model for Corrosion Inhibition of Mild Steel by Thiophene and Its Derivatives Using Artificial Neural Network
... the neural network can effectively generalize correct responses that only broadly resemble the data in the training ...The neural network can now be put to use with the actual data, ...
15
An Effective Intelligent Self Construction Multilayer Perceptron Neural Network
... artificial neural network with extracting most effective features, based on a priori knowledge from a set of training samples, assisted by Apriori algorithm for association rules and particle ...
6
Graph Neural Network for Minimum Dominating Set
... rate value used in the back propagation formula was 0.1. Momentum in these networks was considered as 0.1. The learning rate and parameter values were fixed by trial and error. The wrongly chosen values made the ...
5
Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning
... the 12 measurements of each eye of all five test subjects, were bundled into two groups: a group for central fixation (120 “eyes,” the “CF set”) and a group for paracentral fixation (480 “eyes,” the “para-CF ...
23
Current state and future prospects of artificial intelligence in ophthalmology: a review
... convolutional neural network (CNN) using two different datasets (ORIGA set 99 training images, 551 validation; SCES set used all 1676 images for validation as it was trained using the ...
29
Improving The Fault Prediction In Oo Systems Using ANN With Firefly Algorithm
... a neural network are adjusted through a process of stimulation by the environment in which network is ...embedded. Training rule is a prescribed set of well-defined rules for the ...
7
Training a Neural Network in a Low Resource Setting on Automatically Annotated Noisy Data
... We then label the whole training set using the method by Dembowski et al. (2017) in the ver- sion with heuristics. This approach of automati- cally labeling words allows to quickly obtain large amounts of ...
7
Knowledge Matters: Importance of Prior Information for Optimization
... a neural network to solve the task easily and ...two-tiered neural network, with supervised pre-training of the first part to recognize the category of sprites independently of their ...
32
BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... Grey neural network model is denoted by GNNM(h, n), wherein, h is the order of the differential equations, n is the number of sequences involved in the ...Grey neural network model lets a grey ...
5
Powdery Mildew Disease Identification in Pachaikodi Variety of Betel Vine Plants Using Histogram and Neural Network Based Digital Imaging Techniques
... propagation neural network based techniques were used to input and output data set of betel vine ...propagation neural network and evaluate its performance. Trained neural ...
8
USE OF GENETIC SVM FOR ECG ARRHYTHMIA CLASSIFICATION
... feedforward neural network has been hampered by the lack of training algorithm which reliably finds a nearly globally optimal set of ...a neural network classifier of PVC beats ...
9
The Computerized Simulation of the Neuro-fuzzy System for Recognizing the Parameters of the Geographically Distributed Systems Equipment
... of neural networks control over emergency and pre-emergency situations by predicting their development with the equipment of geographically distributed systems based on computer technology, which is operating ...
5
Application of artificial neural networks for understanding and diagnosing the state of mastitis in dairy cattle
... unsupervised neural network learning paradigms for the detection of minor infected and major infected quarters in the early stages of the ...the training data set on the correct classification ...
94
Recurrent Neural Network Training using ABC Algorithm For Traffic Volume Prediction
... the training phase, the Recurrent Neural Network is presented with a set of the training data from the dataset and the input weights are adjusted by using the ABC algorithm as a ...
10
Using Neural Networks for Corrosion Inhibition Efficiency Prediction during Corrosion of Steel in Chloride Solutions
... the neural network can effectively generalize correct responses that only broadly resemble the data in the training ...The neural network can now be put to use with the actual ...the ...
18
Artificial Intelligence Based Power Quality Disturbance Analysis for Power Quality Improvement
... Distribution network consist of three phase loads and one nonlinear load, various power quality disturbances like voltage sag, swell, transients, harmonics, momentary interruption, fault signals and normal voltage ...
9
Review of Face Recognition Technique Using PCA and BPNN
... because network structure is suitable for task as same as biological systems, such as ...in neural network is simultaneous optimization of network architecture & synaptic weights to obtain ...
5
New Approaches for Image Compression Using Neural Network
... cial neural network is a recent tool in image compression as it processes the data in parallel and hence requires less time and therefore, it is superior over any other ...artificial neural ...
10
3. Prediction of coronary artery plaque type based on Neural Network
... other neural network andLVQneural network can take advantage of the competitive layer neural network automatically learning mode of input vector classification, however, for the ...
7
Volume 2, Issue 7, July 2013 Page 416
... artificial neural network enhanced performance measurement of the filtering system especially on the ability of the system to learn more from any new spam messages that entered the ...
6