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Chaos search in fourire amplitude sensitivity test
Published 2012“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Chaos Search in Fourier Amplitude Sensitivity Test
Published 2012“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Optimization of Grading Ring Design for Metal Oxide Arrester Using Gravitational Search Algorithm
Published 2023Conference Paper -
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A modified weight optimisation for higher-order neural network in time series prediction
Published 2020“…In line with this, the Cuckoo Search (CS) learning algorithm, a kind of metaheuristics techniques employs high-level techniques for exploration and exploitation of the search space in which its step length is much longer in the long run. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…In one-side incomplete information problem, comparison between MGT algorithm and smart random trade-offs (SRT) algorithm indicates that MGT outperforms SRT. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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Operating a reservoir system based on the shark machine learning algorithm
Published 2018“…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach
Published 2024“…Drawing on a diverse dataset from a commercial building, encompassing vital input parameters such as Chilled Water Rate, Building Load, Cooling Water Temperature, Humidity, and Dew Point, the study conducts a comprehensive comparison of metaheuristic algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Barnacles Mating Optimizer (BMO), Harmony Search Algorithm (HSA), Differential Evolution (DE), Ant Colony Optimization (ACO), and the latest RIME algorithm). …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…On the other hand, the offline phase is evoked when the user requests to view the overall clustering results. The DBSCAN algorithm is used to perform the macro clustering task by replacing the distance between trajectories segments with the distance between the temporal micro-clusters. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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Pseudo Randomized Search Strategy (PRSS*) of the ambiguity function mapping
Published 1998“…A technique has been developed for reliably resolving the GPS carrier phase ambiguity over a medium length baseline. A combination between three methods of optimization, global random search and ambiguity function mapping produced an efficient search algorithm what the author called the Pseudo Randomized Search Strategy (PRSS). …”
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Hyperparameter tuning in deep learning using NSGA-III: a Multi-Objective perspective
Published 2025“…The proposed Multi-Objective NSGAIII-DL framework is benchmarked against six baseline optimization strategies—manual search, grid search, random search, Bayesian optimization, particle swarm optimization, and standard genetic algorithms using MNIST and CIFAR-10 datasets. …”
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
Published 2024“…Recursive Feature Elimination (RFE) was employed for feature selection, and we trained seven supervised classifiers. Grid Search was used to optimize the hyperparameters of each algorithm. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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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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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…However, BA needs to be coupled with appropriate learning scheme in determining the tradeoff between global explorative search with local exploitative search. …”
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