Results 31 to 40 of about 9,482,218 (334)

Evaluation of machine learning classifiers in keratoconus detection from orbscan II examinations

Clinics, 2010
PURPOSE: To evaluate the performance of support vector machine, multi-layer perceptron and radial basis function neural network as auxiliary tools to identify keratoconus from Orbscan II maps.
Murilo Barreto Souza, Fabricio Witzel Medeiros, Danilo Barreto Souza, Renato Garcia, Milton Ruiz Alves   +4 more
doaj   +1 more source

Earthquake Hazard Safety Assessment of Existing Buildings Using Optimized Multi-Layer Perceptron Neural Network

Energies, 2020
The latest earthquakes have proven that several existing buildings, particularly in developing countries, are not secured from damages of earthquake.
Ehsan Harirchian, T. Lahmer, Shahla Rasulzade   +2 more
semanticscholar   +1 more source

Fast Recognition of Table Eggs from Different Farming Systems Using Physical Traits and Multi-layer Perceptron [PDF]

Brazilian Journal of Poultry Science
Eggs are a widely consumed source of protein, with consumers often preferring free-range eggs due to their higher nutritive value and prices. However, dishonest traders sometimes mislabel cage eggs as free-range eggs for unjustified profits.
MC Huang, Q Lin, H Cai, H Ni
doaj   +1 more source

On various multi-layer perceptron and radial basis function based artificial neural networks in the process of a hot flow curve description

Journal of Materials Research and Technology, 2021
In recent years, the study of the hot deformation behavior of various materials is significantly marked by an increasing utilization of artificial neural networks, which are frequently employed for a hot flow curve description.
Petr Opěla, Ivo Schindler, Petr Kawulok, Rostislav Kawulok, Stanislav Rusz, Horymír Navrátil   +5 more
doaj   +1 more source

Results of Bias-variance Tests on Multi-layer Perceptron Neural Networks

Journal of Advanced Computational Intelligence and Intelligent Informatics, 2001
Training neural networks involves selection of a set of network parameters, or weights, on account of fitting a non-linear model to data. Due to the bias in the training data and small computational errors, the neural networks’ opinions are biased. Some improvement is possible when multiple networks are used to do the classification.
Wimpie D. Nortje, Johann E. W. Holm, Gerhard P. Hancke 0001, Imre J. Rudas, László Horváth   +4 more
openaire   +1 more source

Stock Price Forecast with Multi Layer Perceptron Artificial Neural Networks [PDF]

, 2021
This study maps and analyzes the academic literature regarding the stock price forecast with multi layer perceptron artificial neural networks, through bibliometric analysis and systematic review. The adoption of these methods requires the use of RStudio,
Fantin, Cristiane Orquisa, Eli Hadad Junior   +1 more
core   +1 more source

Rating prediction of peer-to-peer accommodation through attributes and topics from customer review

Journal of Big Data, 2021
This study aims to predict customers’ behavior in classifying their reviews as high rated or low rated using associated attributes and topics found in the review.
Athor Subroto, Marcel Christianis
doaj   +1 more source

Bacteria classification using Cyranose 320 electronic nose [PDF]

, 2002
Background An electronic nose (e-nose), the Cyrano Sciences' Cyranose 320, comprising an array of thirty-two polymer carbon black composite sensors has been used to identify six species of bacteria responsible for eye infections when present at a range ...
Ritaban Dutta, Gardner Julian W, Dutta, Ritaban, Gardner, J. W., Boilot Pascal, Evor L Hines, Hines, Evor, Hines Evor L, Julian W Gardner, Dutta Ritaban, Boilot, Pascal, Pascal Boilot   +11 more
core   +1 more source

Solving the linear interval tolerance problem for weight initialization of neural networks [PDF]

, 2014
Determining good initial conditions for an algorithm used to train a neural network is considered a parameter estimation problem dealing with uncertainty about the initial weights.
Adam, S.P., Karras, D.A., Vrahatis, M.N., Magoulas, George D.   +3 more
core   +1 more source

Prediction of Permanent Earthquake-Induced Deformation in Earth Dams and Embankments Using Artificial Neural Networks [PDF]

Civil Engineering Infrastructures Journal, 2015
This research intends to develop a method based on the Artificial Neural Network (ANN) to predict permanent earthquake-induced deformation of the earth dams and embankments. For this purpose, data sets of observations from 152 published case histories on
Kazem Barkhordari, Hosein Entezari Zarch
doaj   +1 more source