artificial neural network


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artificial neural network

(ar-ti-fish'ăl nū'răl net'wŏrk),
a computer-based decision-making system for complex data sets comprising processor nodes interconnected in a weighted fashion, simulating a biologic nervous system.
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Estimation of wrist angle from sonomyography using support vector machine and artificial neural network models.
On the basis of the analysis and results of the selected paper, we may imply that artificial neural network analysis is effectively used for determination of the impact of macroeconomic variables on working capital.
The porosity logs are predicted at well locations using the Artificial Neural Network (ANN), then through Probabilistic Neural Network (PNN) these porosity logs are extrapolated over the whole impedance volume (Liu and Liu, 1998).
Detection and classification of brain tumor using Artificial Neural Network from EEG Images", International Journal of Science Engineering and Advance Technology, IJSEAT, 1: 7.
Two models were proposed using Principal Component Analysis (PCA) and trained by an artificial neural network (ANN) using Levenberg-Marquardt (LM) algorithm to recognize rubber seed.
Figure 6 shows an industrial process screen in the supervisory system (SCADA), according to the coagulant dosage control and a button with a caption "ANN", wherein the operator is able to turn on the artificial neural network technique (Figure 7).
An efficient improved photovoltaic irrigation system with artificial neural network based modeling of soil moisture distribution - A case study in Turkey, Computers and Electronics in Agriculture 102: 120-126.
2013) Comparison of prediction model for cardiovascular autonomic dysfunction using artificial neural network and logistic regression analysis.
He also programmed the artificial neural network to produce images that emulate the styles of Ang Kiukok and Pieter Bruegel.
Through artificial neural network, it was proposed the formation of three, seven and nine groups for allocating the genotypes; 86 % of the genotypes were classified correctly in the group defined, this classification was consistent with the measured variables and plant phenotypes observed in field experiments (Table 03 and 04).
Back propagation artificial neural network (BPANN) which was presented by Remelhart in 1986 is one of the most widely used neural network models at present.
Constaints of artificial neural network for rainfall-runoff modeling: trade-offs in hydrological state representation model evaluation.

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