[PDF] Top 20 Artificial neural networks (ANN): prediction of sensory measurements from instrumental data.
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Artificial neural networks (ANN): prediction of sensory measurements from instrumental data.
... field of Sensory Analysis of Foods, specifically with respect to the study of the relationship between sensory and instrumental measurements, it is observed that are few ... See full document
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Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee
... existence of multicollinearity and the dimensionality issue are limiting factors for the Bayesian models, since the once that data set used in this methodology needs to be defined and known priorly, ... See full document
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Data Fusion Using Different Activation Functions in Artificial Neural Networks for Vehicular Navigation
... the prediction mode of BPN-ANN and RBF-ANN were utilized ...presence of GPS signal, the proposed system relies on GPS position information to train the ...The data is processed as follows: ... See full document
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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 ... See full document
6
Uso de redes neurais artificiais para predição da evapotranspiração no cultivo protegido de pimentão
... applicability of artificial neural networks (ANNs) in the prediction of evapotranspiration of sweet pepper cultivated in a ...used data encompass the second crop ... See full document
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Combining Artificial Neural Networks and GIS Fundamentals for Coastal Erosion Prediction Modeling
... Artificial neural networks (ANN) or simply a neural network, is a set of independent neurons linked together in the same way as the synapses, neurons, and dendrites of ours ...a ... See full document
14
Egg Hatchability Prediction by Multiple Linear Regression and Artificial Neural Networks
... hatcher data). Hatchability and data electronically recorded by the sensors inside the incubators and the hatchers were randomly divided in two sets – training and ...consisted of data ... See full document
6
Comparison of mathematical models and artificial neural networks for prediction of drying kinetics of mushroom in microwave vacuum dryer
... Apart from mathematical modeling, the efficacy of artificial neural networks (ANN), as a novel ap- proach, has been successfully approved in resolving a wide variety of issues in ... See full document
11
An Artificial Neural Network for Data Forecasting Purposes
... market prediction is one of the most difficult tasks of time series ...potential of artificial neural networks (ANN) in solving the forecast task in the most general case, ... See full document
12
Prediction of Permanent Earthquake-Induced Deformation in Earth Dams and Embankments Using Artificial Neural Networks
... potential of artificial neural networks (ANN) for predicting earthquake-induced deformation of earth dams and ...propagation neural network models successfully learned ... See full document
13
Prediction of Operating Characteristics of Electrotechnical Devices using Artificial Neural Networks
... appropriate neural network, able to simulate the behavior of proximity sensor at different functioning conditions, we choose a high degree of parameterization for the application, with different kind ... See full document
6
Artificial neural networks for compression of gray scale images: a benchmark
... performance of an SMNN: How to deal with (downsize) the indices for the windows? Most vector quantization (VQ) compression approaches deal with the problem of managing a large number of pieces ... See full document
12
ARTIFICIAL NEURAL NETWORKS APPLIED FOR SOIL CLASS PREDICTION IN MOUNTAINOUS LANDSCAPE OF THE SERRA DO MAR
... aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from ... See full document
13
Masonry Compressive Strength Prediction Using Artificial Neural Networks
... production of the specimen and its actual measurement, the samples must be properly stored and cured, a process that demands plenty of space with speci fic ...homogeneity of samples that were created ... See full document
25
Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran
... comparison of classification in artificial and fuzzy neural networks technique has been conducted to separate classes of forest from non-forest using SPOT satellite neural ... See full document
6
Application of Artificial Neural Networks for Predicting Generated Wind Power
... source of energy available everywhere. The consumption of electricity is rapidly increasing in the world with growing ...capacity of hydro and coal prompts us to find other energy ...variability ... See full document
4
Prediction of Double Layer Grids' Maximum Deflection Using Neural Networks
... design of a neural network as a curve- fitting problem by finding a best fit to the training data in a multidimensional ...use of RBF in the design of neural networks was ... See full document
4
Design of Circular Microstrip Antenna Using Artificial Neural Networks
... design of a circular microstrip patch ...dimensions of microstrip patch antenna with high accuracy. The results of present study are quite ...promising. From the results, it is observed that ... See full document
4
Estimating soybean yields with artificial neural networks
... complexity of the statistical models used to estimate the productivity of many crops, including soybeans, restricts the use of this practice, but an alternative is the use of artificial ... See full document
9
Rules extraction from neural networks applied to the prediction and recognition of prokaryotic promoters
... input data in the se- quence-based ...servation of the consensus hexameric sequence of the pro- moters and the presence of several consensus promoter se- quences for each s factor (Lewin, ... See full document
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