Search Results - (( mode selection method algorithm ) OR ( based information ((bat algorithm) OR (acs algorithm)) ))
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A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots
Published 2022“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents
Published 2022“…This work focuses on the FS problem by automatically detecting events through a novel wrapper FS method based on Adapted Binary Bat Algorithm (ABBA) and Adapted Markov Clustering Algorithm (AMCL), termed ABBA-AMCL. …”
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Bat Algorithm Based Hybrid Filter-Wrapper Approach
Published 2023“…This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI. …”
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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction
Published 2023“…In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”
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Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…Those methods are combined with the first part of the Hilbert–Huang transformation, namely, the empirical mode decomposition (EMD) algorithm. …”
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An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel
Published 2019“…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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An approach of filtering to select IMFs of EEMD in acoustic emission AE sensors for oxidized carbon steel
Published 2019“…Using four datasets, analysis parameters of the Ensemble Empirical Mode Decomposition (EEMD) algorithm has been conducted. …”
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Benchmarking of Bat-inspired Interaction Testing Strategy
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An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
Published 2019“…However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other signal processing methods especially in terms of accuracy. …”
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An enhance approach of filtering to select adaptive IMFs of EEMD in fiber optic sensor for oxidized carbon steel
Published 2019“…However, receiving desired and eliminating undesired information is yet a significant problem of these methods. Empirical Mode Decomposition (EMD) algorithm shows promising results in comparison to other signal processing methods especially in terms of accuracy. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
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Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…Also CS-RD show acceptable performance which is above 85% for compression ratio which that reflect the energy consumption. The Mode method effect negatively in performance all algorithms, the worst CS-RD with Mode in term of energy consumption closes to 2500uJ. …”
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Neural Networks based fault diagnosis of ac motors
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Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
Published 2018“…However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…For the overall performances which were based on the six data sets, the &-AMH algorithm recorded the highest mean accuracy scores of 0.93 as compared to the other algorithms: the ^-Population (0.91), the &-Modes-RVF (0.81), the New Fuzzy &-Modes (0.80), A:-Modes (0.76), &-Modes-HI (0.76), £-Modes- HII (0.75), Fuzzy £-Modes (0.74) and £-Modes-UAVM (0.70). …”
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