Search Results - (( java simulation optimization algorithm ) OR ( _ aggregate method algorithm ))
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1
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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2
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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3
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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4
Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…The results of the aggregation algorithms of NNs ensemble are also compared with the Simple Averaging method. …”
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5
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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7
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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8
Examining performance of aggregation algorithms for neural network-based electricity demand forecasting
Published 2015“…The outputs from NN models are combined by three different aggregation algorithms. These aggregation algorithms comprise of a simple average, trimmed mean, and a Bayesian model averaging. …”
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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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10
Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…In this project three different data aggregation algorithms coding schemes based relative difference (CS-RD), an adaptive method of data aggregation that exploits the spatial correlation between the sensor nodes (ADAM) and coding schemes based the factor of precision (CS-FP) are evaluated. …”
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11
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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12
A Novel Aggregate Classification Technique Using Moment Invariants and Cascaded Multilayered Perceptron Network
Published 2009“…This article discusses a novel method for automatic classification of aggregate shapes using moment invariants and artificial neural networks. …”
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Backpropagation neural network training algorithm analysis / Shahrul Azmi Rosli
Published 2010“…There is several training algorithm that can be used to compute a neural network problem. …”
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14
Data redundancy reduction scheme for data aggregation in wireless sensor network
Published 2020“…The aim to design MC and SAN algorithms is to increase data aggregation efficiency in terms of energy consumption, End-to-end delay, whereas the aim to design AD algorithm is to conserve aggregated data accuracy. …”
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15
Stereo matching algorithm for autonomous vehicle navigation using integrated matching cost and non-local aggregation
Published 2023“…In this paper, a new framework of stereo matching algorithm that used the integration of census transform (CT) and sum of absolute difference (SAD) at the matching cost computation step, non-local cost aggregation at the second step, winner take all strategy at the third step, and a median filter at the final step to minimize disparity map error. …”
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A decomposition/aggregation method for solving electrical power dispatch problems
Published 2023Subjects:Conference paper -
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Development of a novel component carrier selection algorithm in long term evolution-advanced (LTE-A) with carrier aggregation
Published 2017“…Carrier Aggregation (CA), which is a method that aggregates multiple Component Carriers (CCs) of the same or different frequency bands, is one of the Long Term Evolution-Advanced (LTE-Advanced) key features. …”
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Proceeding Paper -
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Hybrid group decision making method based on multi-granular information using fusion algorithms and consistent fuzzy preference relation / Siti Amnah Mohd Ridzuan
Published 2017“…Both algorithm been illustrated in textbook selection. The proposed methods can be utilized as another option to solve a decision making problem.…”
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19
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
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20
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…Multi-objective Genetic Algorithms (MOGA) are an extension of Genetic Algorithms (GA) that does not require multiple objectives to be aggregated to one value. …”
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Proceeding Paper
