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fully connected multilayer perceptron

An Effective Intelligent Self Construction Multilayer Perceptron Neural Network

An Effective Intelligent Self Construction Multilayer Perceptron Neural Network

... Back-propagation algorithm is the most familiar, powerful, and effective algorithm used to train the multilayer perception (MLP) networks. It consists of an input layer, an output layer, and at least one hidden ...

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Heart Disease Prediction System Using Multilayer Perceptron

Heart Disease Prediction System Using Multilayer Perceptron

... consists ofmultiple layers of nodes in a directed graph, with each layer fully connected to the next one. Except for the input nodes, each node is a neuron with a nonlinear activation function. MLP utilizes ...

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A Deep And Wide Analysis For Speech-Emotion Recognition Using Multilayer Perceptron

A Deep And Wide Analysis For Speech-Emotion Recognition Using Multilayer Perceptron

... MLP is a class of artificial neural network and it consists of a set of process units (simple perceptron’s) arranged in layers. In the MLP, the nodes are fully connected between layers without connections ...

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Improving performance of a hyper heuristic using a multilayer perceptron for vehicle routing

Improving performance of a hyper heuristic using a multilayer perceptron for vehicle routing

... Apprenticeship learning is mostly applied in the field of robotics [1]. In a previous work [5], a machine learning approach based on apprenticeship learning with the C4.5 clas- sifier was implemented to build a ...

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Performance Evaluation of Lazy, Decision Tree Classifier and Multilayer Perceptron on Traffic Accident Analysis

Performance Evaluation of Lazy, Decision Tree Classifier and Multilayer Perceptron on Traffic Accident Analysis

... and Multilayer perceptron classifier to classify dataset based on casualty class as well as clustering techniques which are k-means and Hierarchical clustering techniques to cluster ...

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Clustering of heterogeneous precipitation fields for the  assessment and possible improvement of lumped neural network models for  streamflow forecasts

Clustering of heterogeneous precipitation fields for the assessment and possible improvement of lumped neural network models for streamflow forecasts

... The structure of a Kohonen neural network is designed so as to identify patterns in data and as such can be used as a clustering technique. This network is a descriptive tool that is used increasingly in hydrology and ...

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Self-organizing map and multilayer perceptron for malay speech recognition

Self-organizing map and multilayer perceptron for malay speech recognition

... necessitates more data for training. Perceptron as well as Multilayer Perceptron (MLP) usually needs input pattern of fixed length (Lippman, 1989). This is the reason why the MLP has difficulties ...

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Modified Ant Colony Optimization With Modified Adaptive Network Based Fuzzy Inference System For Thyroid Nodule Classification

Modified Ant Colony Optimization With Modified Adaptive Network Based Fuzzy Inference System For Thyroid Nodule Classification

... step, multilayer perceptron was utilized for classifying the internal features when support vector machine was utilized for the classification of external ...

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Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment

Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment

... Fourier-lapped multilayer per- ceptron (FLMLP) method here proposed assembles the best features of MOQV (objective measure for speech quality) [8] and MOQV-KSOM (MOQV using Kohonen self-organizing maps) [9, 10] ...

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Web Page Categorization using Multilayer Perceptron with Reduced Features

Web Page Categorization using Multilayer Perceptron with Reduced Features

... layer. Multilayer Perceptron with back propagation algorithm are the standard algorithm for any supervised learning pattern recognition process and the subject of ongoing research in computational ...

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ariational Analysis In Neural Networks – A Research Study

ariational Analysis In Neural Networks – A Research Study

... presents various novel issues. Initial, a conceptual hypothesis for neural systems from a variational perspective is composed. Specifically, we present the possibility of the capacity space traversed by a ...

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An innovative method to forecasting the load with the help of 
		Multilayer Perceptron Neural Network

An innovative method to forecasting the load with the help of Multilayer Perceptron Neural Network

... addition, multilayer feed forward neural network with 11 input neurons in the input layer, 10 hidden neurons in the hidden layer & 1 output has been significantly used for conducting the research ...box ...

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Stock Credibility Prediction Using Multilayer Perceptron and Statistical Computational Methodologies

Stock Credibility Prediction Using Multilayer Perceptron and Statistical Computational Methodologies

... Stock Market Prediction deals with the various approaches that are used to forecast the value of a company’s stock. Although, the Efficient Market Hypothesis considers stock prices to be unpredictable as they are a ...

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Efficiency of Multilayer Perceptron Neural Networks Powered by Multi Verse Optimizer

Efficiency of Multilayer Perceptron Neural Networks Powered by Multi Verse Optimizer

... In this work, multi-layer feedforward perceptron network was trained by a promising metaheuristic approach, MVO. The framework is examined by five datasets and two trigonometric functions. The framework is tested ...

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Multilayer Perceptron based Model of Large Scale Gene Regulatory Network

Multilayer Perceptron based Model of Large Scale Gene Regulatory Network

... therefore uses the biological prior information to reduce the large search space created from the complex units of Multi- layer perceptron due to the complex nature of the input data. It was noted that ranking of ...

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On  the  Performance  of  Multilayer  Perceptron  in  Profiling  Side-channel  Analysis

On the Performance of Multilayer Perceptron in Profiling Side-channel Analysis

... In this paper, we experimentally investigate the performance of MLP when applied to real-world implementations protected with countermeasures and ex- plore the sensitivity of the hyperparameter tuning of a successful MLP ...

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Adaptive multilayer perceptron model for hourly steamflow Hydrograph

Adaptive multilayer perceptron model for hourly steamflow Hydrograph

... Model Pcrfomrncc Criterir Tho MLP model is designed to simuble tho ninfrll-runoff procosccs of wausheds systans, Bccause there was no d€finitive tost to evaluale tb€ succcs ofeach model,[r] ...

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A hybrid BP and HSA for enhancing a multilayer perceptron learning

A hybrid BP and HSA for enhancing a multilayer perceptron learning

... Traditionally training process of MLP NNs is divided into two phases. The first phase involves with determining the structure of hidden layers, hidden neurons and connection scheme. While the second phase, is involved ...

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Poly co: a multilayer perceptron approach for coreference detection

Poly co: a multilayer perceptron approach for coreference detection

... This paper presents the coreference resolution system Poly-co submitted to the closed track of the CoNLL-2011 Shared Task. Our sys- tem integrates a multilayer perceptron classi- fier in a pipeline ...

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Eigen Vector Descent and Line Search for Multilayer Perceptron

Eigen Vector Descent and Line Search for Multilayer Perceptron

... Abstract—As learning methods of a multilayer perceptron (MLP), we have the BP algorithm, Newton’s method, quasi- Newton method, and so on. However, since the MLP search space is full of crevasse-like forms ...

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