###### neural network

- This course helps you understand and apply two popular artificial neural network algorithms, multi-layer perceptrons and radial basis functions. (sas.com)
- Constrained multi-variable generalized predictive control using a dual neural network. (rwth-aachen.de)
- Syllable duration was modelled using a three-layer neural network that was trained and tested on different portions of the database. (assta.org)
- This paper is organized as follows: a brief overview of Artificial Neural Network,Multilayer perceptron, Back-propagation algorithm, Time Series Analysis and MATLAB are discussed in section II, the data groups and data variables are described in section III, Experimental results obtained using the proposed network and generalisation capacity of model are listed in section IV, and finally we conclude this paper in section V. II. (docplayer.net)
- A performance comparison have been done between Support vector regression and multilayer feed-forward neural network models with respect to their forecasting capabilities. (docplayer.net)
- These network models are: the multilayer perceptron neural network (MLPNN), the radial basis function neural network (RBFNN) and the simple neural network (SNN).The result of the study showed that performances of all three combination methods are better than that of the best individual rainfall-runoff model . (docplayer.net)
- To answer these questions, we can explore a simpler example that reads some inputs and print it to the Understand how to implement a neural network in Python with this code example-filled tutorial.Any layers in between are known as hidden layers because they dont directly see the feature inputs within the data you feed in or the outputs. (gucquebec.ml)
- Recently, I spent sometime writing out the code for a neural network in python from scratchFor example, heres what a neural network with two hidden layers would look like algorithm that calculates the gradients that we need to update our weights from the outputs of our feed forward step. (gucquebec.ml)

###### neuron

- Each hidden or output neuron has weighted input connections from each of the units in the preceding layer. (slideplayer.com)

###### algorithm

- Controlling the parallel layer perceptron complexity using a multiobjective learning algorithm. (rwth-aachen.de)
- Proposed model used Multilayer perceptron (MLP) network with back propagation algorithm for training. (docplayer.net)

###### algorithms

- The p -recursive piecewise polynomial sigmoid generators and first-order algorithms for multilayer tanh-like neurons. (rwth-aachen.de)

###### fuzzy

- Fuzzy perceptron neural networks for classifiers with numerical data and linguistic rules as inputs. (springer.com)
- Fuzzy kernel perceptron. (springer.com)
- Uncertainty of data, fuzzy membership functions, and multilayer perceptrons. (springer.com)

###### model

- One such network with supervised learning rule is the Multi-Layer Perceptron (MLP) model. (codeproject.com)
- A Multi Layer Perceptron model showed the best performance and was therefore selected over the other networks. (beds.ac.uk)
- The results based on mean square error function (MSE) confirm, this model which is based on multilayer perceptron has the potential to successful application to weather forecasting. (docplayer.net)

###### polynomial

- The problem could be thought of as finding the coefficients for a multi-variable polynomial equation in the form: f(x,y,...) = a n x n + a n-1 x n a 1 x + a 0 + b n y n +... where x, y and so forth represent inputs such as price or technical indicators. (docplayer.net)

###### parallel

- Interconnected processing nodes are organized in two or more layers and work in parallel to process input data. (docplayer.net)

###### vector

- 12 6.2.3 Single-layer mapping networks The functionality of a single put node generalizes directly to networks with several put nodes to represent vector functions. (docplayer.net)
- The procedure is developed using Computational Intelligence (CI) Techniques, and in particular Artificial Neural Networks (ANN) and Support Vector Machines (SVM), on a data set consisting of over 2000 deflection profiles calculated for a large number of three layer pavement structures using the BISAR PC software. (docplayer.net)

###### nodes

- A multi layer perceptron network composed by 1 hidden layer with 7 nodes was chosen. (beds.ac.uk)

###### linear

- Using these values, the stiffness of the various layers is back calculated using a back analysis program based on multilayer linear elastic theory. (docplayer.net)

###### networks

- This section considers methods for learning the structure of multi layer perceptrons (MLPs), Bayesian belief networks (BNNs) and Markov random fields (MRFs) and considers methods of feature selection. (biomedcentral.com)
- Different topologies of Neural Networks were created with change in hidden layer, number of processing element and activation function. (docplayer.net)

###### simple

- Implementation of a simple MLP network with one hidden layer. (gucquebec.ml)

###### Learning

- The deep learning techniques are basically composed of multiple hidden layers, and each hidden layer consists of multiple neurons, which compute the suitable weights for the deep network. (mdpi.com)

###### Results

- The results of layer-wise-trained DCNN are favorable in comparison with those achieved by a shallow technique of handcrafted features and standard DCNN. (mdpi.com)
- On the basis of these evaluation parameter results, it is found that multilayer perceptron (MLP) network predict more accurate than other traditional models. (docplayer.net)

###### input

- The standard structure of an MLP contains an input layer, one or more hidden layers and an output layer. (biomedcentral.com)

###### done

- All example code is done in Python, and theres a chapter on multilayer perceptrons. (gucquebec.ml)

###### Weight

- Removal of hidden neurons in multilayer perceptrons by orthogonal projection and weight crosswise propagation. (rwth-aachen.de)

###### evaluation

- There are also options to choose the best solution with multi-modal evaluation. (bigopendata.eu)