Search Results - (( variables location modelling algorithm ) OR ( java simulation optimization 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
New Algorithm of Location Model based on Robust Estimators and Smoothing Approach
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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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9
A variable-capacity-based fuzzy random facility location problem with VaR objective
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10
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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11
Optimal timber transportation planning in tropical hill forest using bees algorithm
Published 2022“…The model uses grid cell-sized 10 m x 10 m characterised with timber locations, volume and fixed and variable costs to represent the study area. …”
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12
Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements
Published 2018“…The parameters investigated are apparent resistivity ( a ), horizontal location (x) and depth (z) as independent variable; while true resistivity ( t ) is dependent variable.…”
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14
The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…Specifically, a Great Value Priority binarization scheme is employed to transform the continuous location of the bat into a binary bit, representing a combination of the variable in binary string form. …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The simplex method is a conceptual model approach for analysing linear programming problems with any number of variables. …”
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16
Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi
Published 2018“…As the mixed integer nonlinear model of the problem was complicated to solve using exact methods, several meta-heuristic algorithms were employed in to optimize the models under investigation. …”
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17
Comparison on queuing performance measures on customer’s flow using Queuing Theory Model and DSW Algorithm / Muhammad Izuanudin Azmi ... [et al.]
Published 2023“…In a multi-server fuzzy queuing model, the approximate technique DSW algorithm is employed to describe a membership function regarding the performance measures (Thamotharan,2016). …”
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The Integration of Nature-Inspired Algorithms with Least Square Support Vector Regression Models: Application to Modeling River Dissolved Oxygen Concentration
Published 2018“…All the predictive models are found to perform best when all the four water quality variables are used as input, which indicates that it is possible to supply more information to the predictive model by way of incorporation of all the water quality variables.…”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2025“…Data compiled from 1985 to 2018 was utilized for training and testing the developed models. An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”
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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
Published 2020“…Secondly, the data collected from the main valve chamber controllers, which are located in the main pipes. The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. …”
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