Search Results - (( java application bee algorithm ) OR ( network implementation learning algorithm ))

Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Implementation of machine learning algorithm in preventing network congestion by Noorazimah binti Ali Sabri

Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

“…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Multi-Backpropagation network by Wan Ishak, Wan Hussain, Siraj, Fadzilah, Othman, Abu Talib

“…The learning mechanism for Neural Network is its learning algorithm. …”
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Computationally efficient sequential learning algorithms for direct link resource-allocating networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

“…Computationally efficient sequential learning algorithms are developed for direct-link resource-allocating networks (DRANs). …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

“…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…By removing these irrelevant and redundant features accuracy of the learning algorithms can be increased. In this paper implementation of different feature selection techniques have been reviewed. …”
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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks by Sadiq, A., Yahya, N.

“…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS by TEH, CHOON KEONG

“…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

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A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

“…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

“…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. …”
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Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.

“…Backpropagation algorithms; Computation theory; Deep learning; Face recognition; Iterative methods; Knowledge acquisition; Machine learning; Neural networks; Biological learning; Convolutional neural network; DeepID; Extreme learning machine; Face Verification; Fast implementation; Feature mapping; Labeled faces in the wilds (LFW); Learning algorithms…”

Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman by Seman, Noraini

“…However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques.…”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…The total work is completed by the selection, assessment, and implementation of the Machine Learning (ML) model, and finally, proposed the crime prediction. …”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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