Search Results - (( data optimization search algorithm ) OR ( parameter simulation based algorithm ))
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Cubic spline based particle swarm optimization for microstrip antennas
Published 2011“…The data for developing the CSPSO program is obtained from simulation software by varying different parameters of the antenna. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…This can overcome the existing memory-based algorithms such as random search (RS) and simulated annealing (SA) which currently produce less control accuracy due to the local minimum problem. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…This can overcome the existing memory-based algorithms such as random search (RS) and simulated annealing (SA) which currently produce less control accuracy due to the local minimum problem. …”
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Mobile data gathering algorithms for wireless sensor networks
Published 2014“…In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
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Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…FLC can automatically optimize HO parameters i.e. Handover Margin (HOM) and Time-ToTrigger (TTT) based on a set of criteria, this is in order to minimize unwanted HOs known as HO Ping Pong (HOPP) and HO failure (HOF). …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…This research focuses on improving Genetic Algorithms (GA) for SI, specifically addressing inefficiencies in common crossover operators that limit search space exploration and lead to premature convergence. …”
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Collaborative adaptive filtering approach for the identification of complex-valued improper signals
Published 2019“…This paper proposes a novel hybrid filter for data-adaptive optimal identification and modeling of complex-valued real-world signals based on the convex combination approach. It is equipped with different complex domain characteristics of subfilter algorithm. …”
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Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network
Published 2018“…However,the sink node position and size of data transmitted will not affect the performance of coverage area.This is because the coverage area value is fluctuated as the parameters value increases.Throughout the experiment conducted,sensor nodes deployed using Modified Harmony Search algorithm (MHS) gives better coverage area compared to other existing methods.The average coverage area percentage obtained by Modified Harmony Search is 63 %.The average coverage area percentage obtained by Modified Random is 48 % and the average coverage area percentage obtained by Harmony Search is 46 %.The highest coverage area recorded for Modified Harmony Search is 70 %.To enhance the energy efficiency,shortest path distance finder is added to each method.Throughout the research,Modified Harmony Search with shortest path distance finder gives optimum results.…”
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