Search Results - (( java implementation modified algorithm ) OR ( parameter reservation 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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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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Quality of service management algorithms in WiMAX networks
Published 2015“…Thirdly, an energy algorithm called the Efficient Battery Life-aware Power Saving (EBLAPS) algorithm is proposed to address the problems of minimizing energy at the expense of response due to how energy sleep parameters are adjusted based on the residual energy and the use of standard sleep mode algorithms consumes high energy because of frequent transition to listening mode in the case of light traffic. …”
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Research On Photovoltaic Mppt Control Method Based On Improved Bas Algorithm And Variable Step-Size Inc Method
Published 2024“…These methods differ greatly in terms of required parameters, algorithm complexity, tracking speed, tracking accuracy, hardware requirements, etc. …”
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A COMPARATIVE PERFORMANCE EVALUATION OF NEURAL NETWORK ALGORITHMS BASED STATE OF CHARGE ESTIMATION FOR LITHIUM-ION BATTERY
Published 2023“…Therefore, neural network algorithms based SOC estimation have received huge attention since they have the adaptively to adjust the network parameters automatically without battery model. …”
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ANALYSIS OF PERFORMANCE PARAMETERS FOR WIRELESS NETWORK USING SWITCHING MULTIPLE ACCESS CONTROL METHOD
Published 2023“…Three control access is processed; polling, token passing, and reservation algorithms for collision avoidance. The reservation stage reserves the data before sending, which includes two timeline intervals; a fixed-time reservation period, and variable data transmission interval. …”
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An efficient control implementation for inverter based harmony search algorithm
Published 2023“…The HS algorithm aims to handle the trial and error procedure used in finding the PI parameters and then apply the proposed control algorithm via the eZdsp TMS320F28355 board to link the inverter prototype with the Matlab Simulink. …”
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Metaheuristic Optimization of Perovskite Solar Cell Using Hybrid L32 Taguchi Doe-Based Genetic Algorithm
Published 2025“…This paper emphasizes the metaheuristic optimization approach in searching for the optimum input parameters of perovskite solar cell (PSC). The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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PREDICTIVE ANALYTICS OF JUNCTIONLESS DOUBLE GATE STRAINED MOSFET USING GENETIC ALGORITHM WITH DOE-BASED GREY RELATIONAL ANALYSIS
Published 2024“…This paper explores the application of Genetic Algorithm (GA) incorporated with design of experiment (DoE) based on Grey Relational Analysis (GRA) in predicting the optimal design parameters of n-type Junctionless Double Gate Strained MOSFET (JLDGSM). …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…All rights reserved.…”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Published 2021“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Published 2021“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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