Search Results - (( development factors function 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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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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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Effort Estimation Model for Function Point Measurement
Published 2007“…This research work has generated an algorithmic effort estimation model for function points measurement. …”
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Performance comparison of LFXLMS, MOVFXLMS and THF-NLFXLMS algorithms for Hammerstein NANC
Published 2016“…In previous works, Tangential Hyperbolic Function NLFXLMS (THF-NLFXLMS) algorithm has been developed whereby the degree of nonlinearity is estimated using tangential hyperbolic function (THF). …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…In computational grid, job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Monograph -
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…As for multi-objective functions associated with the optimisation problem, a weight-sum method is typically used to determine each objective function's coefficient factors (CF). …”
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Uninterruptible power supply topology using single phase matrix converter with active power filter functionality / Muhammad Shawwal Mohamad Rawi
Published 2022“…It possesses low harmonic contents with a low Total Harmonics Distortion (THD) level, thus, improving the high-power factor. A step response function investigates the transition between the proposed switching algorithms for rectifier and inverter operations. …”
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Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm
Published 2001“…These factors include the choice of initial weights, the choice of activation function and target values, and the two backpropagation parameters, the learning rate and the momentum factor.…”
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Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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A holistic review on artificial intelligence techniques for well placement optimization problem
Published 2020“…Newly developed optimization algorithms are very efficient and favorable when compared to other established optimization algorithms and in all cases, it has been noticed that hybridization of two or more algorithms works better than stand-alone algorithms. …”
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