Search Results - (( java implementation 5s algorithm ) OR ( program quality optimization algorithm ))
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System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)
Published 2022“…This project present a system program algorithm based on Moth Flame Optimization (MFO) algorithm to assign an optimal set of system program to meet the satisfaction of quality of service requirements of cloud computing in such a way that the total execution time of tasks is minimized. …”
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Academic Exercise -
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Performance evaluation of real-time multiprocessor scheduling algorithms
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…Furthermore, Optimized Parametric Topology Control Routing algorithm performs significantly better than Triangular Routing Method and Change Foreign Agent Algorithm. …”
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Thesis -
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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Thesis -
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Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.]
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Conference or Workshop Item -
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A hybrid MEP and AIS Algorithm for energy dispatch in power system
Published 2017“…Based on original Meta Heuristic Evolutionary Programming (Meta-EP) method with a consideration on cloning process as in Artificial Immune System (AIS) algorithm together thus identified as New Meta Heuristic Evolutionary Programming algorithm (NMEP). …”
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An efficacious multi-objective fuzzy linear programming approach for optimal power flow considering distributed generation
Published 2016“…An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. …”
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Optimization of milling parameters using ant colony optimization
Published 2008“…In process planning of conventional milling, selecting reasonable milling parameters is necessary to satisfy requirements involving machining economics, quality and safety. This study is to develop optimization procedures based on the Ant Colony Optimization (ACO). …”
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Undergraduates Project Papers -
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A Hybrid Multi-objective Integrated JAYA-Evolutionary Programming (MOIJEP) Algorithm for Under Voltage Load Shedding (UVLS) Scheme in Bulk Power System
Published 2025Subjects:Conference paper -
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…To evaluate the hybrid algorithm, optimization of hydro-power energy of Karun dams were considered. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. …”
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Video colorization using canny optimization technique / Irwin Kevin Mueson
Published 2016“…In future, it is recommended that this program prototype can improve the image quality and smoothen the colour distribution.…”
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Thesis -
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An optimal mesh algorithm for remote protein homology detection
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Genetic Mutation of Cowpea as a Constrained Stochastic Optimization Problem in Sustainability
Published 2023“…Our experiments with genetic algorithm as a stochastic optimizer, confirmed that the evolution from the initial random string (initial cowpea species) to the target string (optimal cowpea solution) was smeared by uncertainties in the optimization-for-sustainability effort. …”
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