Search Results - (( development strategy selection 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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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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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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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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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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10
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For floor localisation, the strategy is based on developing the algorithm to determine the floor by utilising fingerprint clustering technique. …”
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Channel selection strategies for co-existence between wimax and wifi
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Development of intelligent evaluation system for product end-of-life selection strategy
Published 2011“…This problem can be best resolved by promoting end-of-life (EOL) selection strategies. The main objective of this research is to develop an evaluation system for selecting EOL strategy specifically for remanufacturing. …”
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Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani
Published 2016“…The findings of the study show that, there is a strong relationship between the summary writing proficiency of students and the summarizing strategies that they used. We then develop a new algorithm to address the summarizing strategies identification problem. …”
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14
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Various experiments were carried out to assess and test components of IFS algorithm. The first test was designed to evaluate the formulated IFS Selection Criterion Strategy (MI estimator) by comparing it with six different MI estimator benchmarks. …”
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CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm
Published 2019“…Thus, IOR combinatorial testing is selected to be studied in this research. To overcome the combinatorial optimization problem, Jaya algorithm is proposed to apply in this project since metaheuristic algorithm is fast in optimization and this strategy is named as CTJ. …”
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Undergraduates Project Papers -
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The algorithm is developed by integrating the SURE model with the Autometrics search strategy; hence, it is named as SURE-Autometrics. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation
Published 2017“…This paper describes our experience with four hyper-heuristic selection and acceptance mechanisms namely Exponential Monte Carlo with counter (EMCQ), Choice Function (CF), Improvement Selection Rules (ISR), and newly developed Fuzzy Inference Selection (FIS), using the t-way test generation problem as a case study. …”
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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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