Search Results - (( using adaptive using algorithm ) OR ( simulation optimization based algorithm ))
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1
Active power optimization based on non adaptive immune algorithm: article
Published 2010“…This paper presents a study of active power optimization based on non adaptive immune algorithm (NAIA) in power systems. …”
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2
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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4
Adaptive DNA computing algorithm by using PCR and restriction enzyme
Published 2004“…In this paper, we introduce a new adaptive DNA coinpitting algorithm by using Poiymcruse Chain Rearlion (PCR). …”
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5
A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…A thematic analysis of 40 peer-reviewed articles was conducted using ATLAS.ti, revealing three dominant research themes: intelligent algorithms, building performance simulation techniques, and adaptive design for climate change. …”
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Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…The predictive part determines the feasible schedule to be used for a flow shop which is generated using a combination of rule-based simulation and optimization: first, using the optimization algorithm to compute a rough plan, followed by using a rule based simulation system to locally fine tune the plan to obtain the final schedule. …”
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Exponentially adaptive sine-cosine algorithm for global optimization
Published 2019“…Sine-Cosine algorithm (SCA) is an optimization algorithm formulated based on mathematical Sine and Cosine terms. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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BBO algorithm-based tuning of PID controller for speed control of synchronous machine
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An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization
Published 2019“…In addition, the ADAPSO position update equation is modified to anticipate position adjustment to ensure communication connectivity. To adaptively switches between the two algorithms, an adaptive switching algorithm based on a Generalized Likelihood Ratio Test (GLRT) is proposed. …”
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11
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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12
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz
Published 2017“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm
Published 2023“…The algorithm works by finding the minimum transmitter power with the help of Distributed Parallel Genetic Algorithm (DPGA) employed on an offload microcontroller system to form optimal beam coverage to reduce power usage of adaptive antenna at WCDMA base station. …”
Conference paper -
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
Published 2018“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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Estimation-based Metaheuristics: A New Branch of Computational Intelligence
Published 2016“…Each agent in SKF acts as a Kalman Filter. By adapting the standard Kalman Filter framework, each individual agent finds an optimization solution by using a simulated measurement process that is guided by a best-so-far solution as a reference. …”
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Enhanced utility accrual scheduling algorithms for adaptive real time system.
Published 2009“…We compared the performances of these algorithms by using discrete event simulation. Results: The proposed PUAS algorithm achieved the highest accrued utility for the entire load range. …”
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FPGA implementation of metaheuristic optimization algorithm
Published 2023“…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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