Search Results - (( java implementation modified algorithm ) OR ( using demand using algorithm ))
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1
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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Thesis -
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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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Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search
Published 2014“…The second problem is the use of a single algorithm that failed to solve local optima. …”
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7
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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8
Improving performance of mobile ad hoc networks using efficient Tactical On Demand Distance Vector (TAODV) routing algorithm
Published 2012“…It also describes the design of a novel on-demand routing algorithm. Most of the proposed algorithms use a blind ooding technique during the route discovery process. …”
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Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan
Published 2025“…The aim of this study is to optimize the demand response of solar energy generation using Genetic Algorithm (GA) to minimize the daily yield loss caused by load shedding. …”
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10
Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation
Published 2019“…The current operation of AHD using the existing optimization rules resulted in a mismatch between the water supply and water demand. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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Hybrid Real-Value-Genetic-Algorithm and Extended-Nelder- Mead Algorithm for Short Term Energy Demand Prediction
Published 2024“…It is essential to accurately predict the amount of short-term power required by an area using a highly effective prediction technique. The real-value-genetics-algorithm (RVGA) is the most effective technique that is currently used. …”
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Festive season balancing groceries optimization / Fairuz Mohamed Razi
Published 2012“…This research uses Genetic Algorithms concept and technique to solve an optimization problem in shortage in supply-demand during festive season which is during Hari Raya Aidilfitri. …”
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Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim
Published 2019“…A new MILP for DSIRPB is formulated and used within the algorithm. The DSIRPB is modeled as stochastic dynamic programming and solved using hybrid rollout algorithm. …”
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DYNAMIC PRICING ALGORITHM IN PARKING SYSTEMS
Published 2020“…This algorithm will be used to change the parking rate in any parking lots that maybe overutilised or underutilised. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi
Published 2015“…The results indicate that the applied algorithms can generate the useful results. Therefore, iv MA, M-SA and TS are found suitable for solving TTRPSDTW as well. …”
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Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty
Published 2017“…Results are compared with the classic form of BDA and the weighted sum method for demand uncertainty and deterministic demands. To do this, Monte Carlo method with uniform function is used, then the stability of the proposed method towards demand uncertainty is shown. …”
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