Search Results - (( developing evaluating gaps algorithm ) OR ( java simulation optimization algorithm ))
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To address this issue, the main objective of this research is to improve the existing Priority Rules (PR) cloud schedulers by developing a new dynamic scheduling algorithm by manipulating the gaps in the cloud job schedule. …”
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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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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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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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10
Energy band gap modeling of doped bismuth ferrite multifunctional material using gravitational search algorithm optimized support vector regression
Published 2021“…The energy band gap of doped bismuth ferrite is modeled in this contribution through the fusion of a support vector regression (SVR) algorithm with a gravitational search algorithm (GSA) using crystal lattice distortion as a predictor. …”
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Evaluating critical success factors in AI-driven drug discovery using AHP: a strategic framework for optimization
Published 2025“…This study presents a novel framework using the Analytic Hierarchy Process (AHP) to systematically evaluate and rank these factors, addressing a crucial gap in strategic planning for AI adoption in pharmaceutical research. …”
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Midblock signalled pedestrian crossing : alternative controller algorithms
Published 2000“…The measures of performance of all algorithms are evaluated using a fully calibrated and validated simulation program. …”
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A new priority rule cloud scheduling technique that utilizes gaps to increase the efficiency of jobs distribution
Published 2023“…To address this issue, the main objective of this research is to improve the existing PR cloud schedulers by developing a new dynamic scheduling algorithm by manipulating the gaps in the cloud job schedule. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
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Virtual Models for Real-World Learning: The Development and Evaluation of a Patient Simulator for Eye Disability Diagnosis
Published 2024thesis::master thesis -
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802.11 MAC layer sniffer using spoof detection algorithm / Azwan Abdul Satar
Published 2007“…The result of these tests showed that the wireless sniffer was able to identify all normal gap, spoofing, high gap between successive frames, out of order and retransmit frames. …”
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Evaluate the performance of university timetabling problem with various artificial intelligence techniques
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Final Year Project / Dissertation / Thesis -
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Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
Published 2023“…Objectives involve studying, developing, and evaluating the accuracy of a Bayesian model for predicting winning rates. …”
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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