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1
An improved algorithm for channel allocation on direct sequence spread spectrum
Published 2011“…Graph coloring is an assignment a color to each vertex, which each vertex that adjacent is given a different color. Graph coloring is a useful algorithm for channel allocation on Direct Sequence Spread Spectrum (DSSS).Through this algorithm,each access point (AP) that adjacent gives different channels based on colors available.Welsh Powell algorithm and Degree of saturation (Dsatur) are the popular algorithms being used for channel allocation in this domain. …”
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2
Schelkunoff array synthesis methods using adaptive-iterative algorithm
Published 2003“…The adaptive-iterative algorithm is an error-reduction algorithm that has been extensively studied in recent years. …”
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
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Distributed generation allocation to reduce losses and improve voltage profile genetic algorithm: article
Published 2010“…I used Newton Raphson for load flow algorithm and composed it with Genetic Algorithm. …”
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Optimal cost benefit of the EToU electricity tariff for a manufacturing operation by using optimization algorithm
Published 2021“…In regard to the issue, Tenaga Nasional Berhad (TNB) has introduced a more advanced tariff under Demand Side Management (DSM) programs namely Enhance Time of Use (EToU) tariff as an advanced version of the Time of Use (ToU) tariff for generation and demand side benefits. …”
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Problem restructuring in interger programming for reduct searching
Published 2003“…Standard Integer Programming / Decision Related Integer Programming (SIP/DRIP) is a reduct searching system that finds the reducts in an information system. …”
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9
Backward reduction application for minimizing wind power scenarios in stochastic programming
Published 2023“…In order to make informed decisions in the presence of uncertainties, risk management problems of power utilities may be modelled by multistage stochastic programs. These programs use a set of scenarios (or plausible realizations) and corresponding probabilities to model the multivariate random data process, e.g. electrical load, stream flows to hydro units, generation output of intermittent renewable sources as well as fuel and electricity prices. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Parallelization of speech compression based algorithm based on human auditory system on multicore system
Published 2012“…To achieve a scalable parallel speech coding algorithm, single program multiple data (SPMD) programming model was used, in which a single program was written for all cores. …”
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Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra...
Published 2025“…To address uncertainties in wind speed, solar irradiation, load demands, and energy prices, Monte Carlo Simulation (MCS) is employed. Scenario reduction through the Backward Reduction Algorithm (BRA) manages computational complexity. …”
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Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC)
Published 2019“…Satisfiable Integer Programming (SIP) has been used to quantify dataset in Rough Classification Modeling (RCM). …”
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ETOU electricity tariff for manufacturing load shifting strategy using ACO algorithm
Published 2019“…This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Empirical validation using benchmark dataset and real-world data from three logistics companies in China demonstrates significant improvements in supply chain efficiency and cost reduction. …”
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Fuzzy rules reduction using rough set approach
Published 2003“…Johnson reducer and Genetic Algorithm reducer are the methods used for computing reducts. …”
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An optimized test case generation technique for enhancing state-sensitivity partitioning
Published 2017“…The scope of this work is testing a module with memory where each module may consist of several programs. The essence of enSSP is to combine the features of Genetic Algorithm (GA) with a suite reduction technique to achieve optimization. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. The approach is based on optimization of selected test case from test suite T. …”
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