Search Results - (( developing function a algorithm ) OR ( learning application optimized algorithm ))

Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications by Faisal M., Hannan M.A., Ker P.J., Uddin M.N.

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

“…Shark Smell Optimization (SSO) algorithm has been proven to have high efficiency in many optimization applications. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Optimized processing of satellite signal via evolutionary search algorithm by Hassan, Azmi, Othman, Rusli, Tang, Kieh Ming

“…The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…This algorithm comes with some corollaries that form a learning approach in one-side incomplete problem. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…Particularly, GA is utilized to determine the optimal number of hidden layers, number of neurons in each hidden layer, type of training algorithm, type of activation function of hidden and output neurons, initial weight, learning rate, momentum term, and epoch size of a multilayer feed-forward ANN. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…On the other hand, an adaptive model predictive controller (WNMPC) based on LWN-OSELM modelling method is proposed for nonlinear system control applications. The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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A Stepper Motor Design Optimization Using by Wong, Chin Wei

“…The production process, including material processing and winding, would take up too much time and expense. There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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Chaos search in fourire amplitude sensitivity test by Koda, Masato

“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Chaos Search in Fourier Amplitude Sensitivity Test by Koda, Masato

“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Quasi oppositional—Manta ray foraging optimization and its application to pid control of a pendulum system by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nurul Amira, Mhd Rizal, Nor Maniha, Abd Ghani, Mohd Falfazli, Mat Jusof, Mohd Ashraf, Ahmad

“…From the study, MRFO is a relatively new developed algorithm and has low convergence rate. …”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

“…We develop an efficient iterative algorithm to optimize it since the objective function of the proposed method is non-smooth and difficult to solve. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod