Search Results - (( developing multilayer selection algorithm ) OR ( java simulation optimization algorithm ))
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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A new intelligent multilayer framework for insider threat detection
Published 2021“…The selection procedure has been developed based on the integration of the entropy-VIKOR methods. …”
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Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Prior to developing the whole multilayered ensemble framework, two separate experiments were performed to evaluate and study the different methods of feature extraction and selection. …”
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Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method
Published 2017“…The Differential Evolution Algorithm (DE) is used in this work to select the optimum color and texture information to achieve the optimum response. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Cardiac abnormality prediction using tansig based multilayer perceptron
Published 2021“…This study has used a Multilayer Perceptron (MLP) network as ANN structure by being trained using three different training algorithms namely Backpropagation (BP), Lavenberg Marquardt (LM) and Bayesian Regularization (BR). …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…A systematic method for selecting the ANN's input variables was developed using Matlab Programming language.…”
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Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
Published 2018“…The prediction performance of the proposed fully tuned RBF was compared with Multilayer Perceptron (MLP), Hybrid Multilayer Perceptron (HMLP) and RBF networks trained with CT algorithm. …”
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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah
Published 2020“…Existing researches on air pollution forecasting used a variety of machine learning algorithm. One of the popular algorithms used to forecast the air pollution is Artificial Neural Network (ANN). …”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…Hidden node size, initial weights and feature selection of the MLP that play significant role in the classification performance are selected to be automatically optimized by the improved GA. …”
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Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column
Published 2003“…The algorithm utilizes process simulator to develop plant model in order to conduct sensitivity analysis and provide dynamic data on selected fault. …”
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Conference or Workshop Item -
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Improvement of Neural Network performance by data selection using Radial Basis Function and Hybrid Multilayered Perceptron network / Ahmad Puad Ismail, Nazirah Mohamat Kasim and S...
Published 2008“…This thesis presents the implementation of Radial Basis Function (RBF) and Hybrid Multilayered Perceptron(HMLP) Neural Network for a classical controller modeling. …”
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