Search Results - (( java implementation modified algorithm ) OR ( parameter object based algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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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. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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4
Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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7
Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…These values can be benchmarked in solving multi-objective GMS problems using the multi-objective PACS algorithm and its variants.…”
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…There are three objectives in this research. The first objective is to study the effects of varying the architecture designs and parameter values of the backpropagation neural network (BPNN) learning algorithm. …”
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Calibration of optical based silicone tactile sensor based on image deformation technique / Abdul Halim Esa
Published 2016“…Based on these three parameters, three different types of algorithm are developed in order to measure experimentally the forces and deformation based on optical information of the tactile sensor. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…A multi-objective PACS algorithm based on sequential strategy which considers unit commitment and GMS problem separately is proposed to obtain solution for a proposed GMS model. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Multi-objective optimization of friction stir welding process parameters of AA6061-T6 and AA7075-T6 using a biogeography based optimization algorithm
Published 2017“…In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. …”
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A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique
Published 2022“…Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D) is one of the algorithms that utilize the concepts of decomposition and neighbourhood to solve multi-objective problems. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…In the sizing of the SAPV system, the mutation adaptive DE (MADE) algorithm based multi-objective functions minimizes three constraint objective functions. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…The improved algorithm is based on hybridization of quasi opposition-based learning in enhanced scatter search (QOBLESS) method. …”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…The objective of the simulation is to understand the effect of the algorithm parameter on searching pattern strategy, as well as the possibility and the effectiveness of the proposed technique for the Swarm of mini Autonomous Surface Vehicles' (ASVs) application.…”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…Therefore, this paper aims to obtain optimum conditions of ethe nd milling process for three cutting inserts with multi-objective parameters using a combination of mathematical modelling and genetic algorithm. …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…The objective of this paper is to formulate an algorithm for tuning SVM parameters and feature subset selection.This can be achieved by simultaneously performing the selection of feature subset and tuning SVM parameters tasks. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…These fine-tuning techniques continue to be the object of ongoing research. Differential evolution (DE) is a simple yet powerful population-based metaheuristic. …”
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