Artificial neural network models
Tourism demand modeling and forecasting with artificial neural network models: The Mozambique case study
... To select the best model it can be regarded as one that has a lower MAPE, which corresponds to the template whose sequence provided overnights is closer to the actual nights, or can select the model with the highest (r) ...
18
Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China
... an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN’s predictive ability with ...
7
Artificial neural network models: data selection and online adaptation
... designing neural network models [4], in terms of input selection, model structure determination and parameter ...driven models, the data used to design the models has a direct influence ...
257
Forecasting of a Non-Seasonal Tourism Time Series with ANN
... Abstract. The paper present and discusses several alternative architectures of Artificial Neural Network models used to predict the time series of tourism de- mand for Cape Verde. This time ...
11
Desempenho discriminatório de variáveis antropométricas na identificação de fragilidade em idosos
... No terceiro artigo, PERFORMANCE OF ANTHROPOMETRIC MEASURES IN PREDICTING FRAILTY IN ELDERLY: LOGISTIC REGRESSION AND ARTIFICIAL NEURAL NETWORK MODELS, buscou- se investigar a[r] ...
24
Use of Artificial Neural Network for Testing Effectiveness of Intelligent Computing Models for Predicting Shelf Life of Processed Cheese
... After setting up the data source for connecting to and importing data from a database we have used several standard functions of the Matlab Database Toolbox. We can retrieve BINARY or OTHER Java SQL data types. However, ...
45
SIMULATING POROSITY AND PERMEABILITY OF THE NUCLEAR MAGNETIC RESONANCE (NMR) LOG IN CARBONATE RESERVOIRS OF CAMPOS BASIN, SOUTHEASTERN BRAZIL, USING CONVENTIONAL LOGS AND ARTIFICIAL INTELLIGENCE APPROACHES
... backpropagation neural network (MATLAB, 2019) with five neurons in the hidden layer and one neuron in the output ...ANN models used, as transfer functions, a hyperbolic tangent function ...
13
An Artificial Neural Network for Data Forecasting Purposes
... of artificial neural networks (ANN) in solving the forecast task in the most general case, when the time series are ...feed-forward neural architecture: the nonlinear autoregressive network ...
12
Forecasting Inflation under Globalization with Artificial Neural Network-Based Thin and Thick Models
... traditional models that are “theory-rich” and “data-poor”, ANNs are “data-rich” and “theory-poor” in a way that little or no a priori knowledge of the problem is present ...(different network architectures) ...
6
Artificial neural network model applied to a PEM fuel cell
... ANN models were tested to predict the voltage using some experimental ...best ARTIFICIAL NEURAL NETWORK MODEL APPLIED TO A PEM FUEL ...
7
In silico prediction of human oral bioavailability : artificial neural networks and physiologically based models
... a network architecture of 2 hidden layers with 3 hidden neurons in the first layer and 2 hidden neurons in the second layer (n-3-2-1 ...same network architecture and including all the remaining molecular ...
229
Facial Expression Classification Based on Multi Artificial Neural Network and Two Dimensional Principal Component Analysis
... Facial expression classification is a kind of image classification and it has received much attention, in recent years. There are many approaches to solve these problems with aiming to increase efficient classification. ...
8
Evaluation of Artificial Immune System with Artificial Neural Network for Predicting Bombay Stock Exchange Trends
... Numerous soft computing approaches have been applied effectively in predicting the movement of stock trend and produced better performance. In this study, we have proposed an immune based computational strategy for ...
6
Prediction of Skin Penetration using Artificial Neural Network
... The artificial neural networks (ANN) technologies provide on-line capability to analyze many inputs and provide information to multiple outputs, and have the capability to learn or adapt to changing ...the ...
6
DESIGN AND ANALOG VLSI IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK
... proposed neural network. Back-propagation network (BPN) is the best example of a parametric method for training supervised multi-layer perception neural network for ...forward ...
14
Artificial Neural Network Analysis in Preclinical Breast Cancer
... of neural network methods are as follows: ease of optimization, cost-effective, lexible non-linear modeling of large data sets, accuracy for predictive inference, and with potential to support clinical de- ...
8
Short-Term Load Forecasting Using Artificial Neural Network
... methods, artificial neural networks, genetic algorithm, fuzzy logic ...average models [2] and spectral expansion technique [3], the regression method utilizes the tendency that the load pattern has a ...
6
An artificial neural network model for rainfall forecasting in Bangkok, Thailand
... only after the occurrence of the rainfall events. It means that these models can predict rainfall only when rain occurs, they can tell how long the rain will last but not whether it will rain or not. When using ...
36
Bol. Ciênc. Geod. vol.23 número1
... of Artificial Intelligence techniques in geodesy, this study developed, tested and compared a novel technique capable of improving the accuracy of ...this, artificial neural network technology ...
21
Functional Link Artificial Neural Network for Classification Task in Data Mining
... classification models have been proposed over the years, e.g. statistical models like linear/quadratic discriminates [2] , genetic models [3] , decision trees [4,5] and neural networks [6] ...
8