Search Results - (( parallel prediction learning algorithm ) OR ( java simulation optimization algorithm ))
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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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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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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Leveraging data lake architecture for predicting academic student performance
Published 2024“…With its parallel processing capabilities, this centralized data repository facilitates the training and evaluation of various machine learning models for prediction. …”
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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Protein secondary structure prediction from amino acid sequences using a neural network classifier based on the Dempster-Shafer theory
Published 2003“…As a result, this research extends the initial work by examining its potential improvements and applicability in a new real world task such as the protein secondary structure prediction. In order to reduce the computational demand when training with large data of proteins, an interface was developed using the data parallel approach to parallelize the training phase of the classifier and other accompanying methods such as data clustering algorithms. …”
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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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Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia
Published 2024“…Even though the lowest reported performance was reported by the XGBoost, it is the faster of the three algorithms due to its advanced parallel processing capabilities and distributed computing architecture. …”
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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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Monograph -
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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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Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…Our results indicate that gene expression profiles combined with carefully chosen learning algorithms can predict patient survival for certain diseases.…”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Undergraduates Project Papers -
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Extreme Learning Machines: A new approach for prediction of reference evapotranspiration
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An integrated priority-based cell attenuation model for dynamic cell sizing
Published 2012“…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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