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.
Farlex Partner Medical Dictionary © Farlex 2012
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Due to its nonlinear structure, artificial neural networks can capture more complex characteristics, controlled for several genes, of the data, which is not always possible with traditional statistical techniques, like traditional analysis of variance.
Ahmed, "Prediction of dissolved oxygen in Surma River by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks (ANNs)," Journal of King Saud University-Engineering Sciences, 2014.
Linear discriminant analyses, artificial neural networks and logistic regression are applied in mandate to predict the probability of a specic categorical outcome based upon several independent variables.
Artificial neural networks (ANN) can be an efficient way of modeling the water level fluctuations process in situations where explicit knowledge of the internal hydrologic processes is not available.
There are many types of artificial neural networks, and the most popular one is a Multilayer Perceptron or MLP.
He applied this tweak to artificial neural networks with more layers, so-called deep neural networks.
Then a joint analysis of the stability experiments and analyses was carried out using the traditional method (CRUZ et al., 2012), PLAISTED & PETERSON (1959), WRICKE (1965), EBERHART & RUSSELL (1966), and based on artificial neural networks (NASCIMENTO et al., 2013).
Thus, this study aimed to estimate the Pol of sugarcane juice through modeling by artificial neural networks, using values of [degrees]Brix and WCW as input variables, besides indicating whether the network architecture complexity interferes with its accuracy.
Although optical artificial neural networks were recently demonstrated experimentally, the training step was performed using a model on a traditional digital computer and the final settings were then imported into the optical circuit.
The estimation of rock mass deformation modulus using regression and artificial neural networks analysis.
A team based at the Centre for Robotics and Neural Systems at Plymouth University presented on April 4 their study that involves using artificial neural networks (ANNs) to classify planets into categories based on how they could possibly sustain life.

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