Showing 321 - 340 results of 4,946 for search 'different (evolution OR evaluation) algorithm', query time: 0.17s Refine Results
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    Seismic Sedimentologic Study on Sequence-Sediment Evolution in Fault Basin Regions by Wang Tianyun, Tian Jingchun, Liu Wei, Han Xiaofeng, Li Yuan, Li Tao, Sun Xiaoping

    Published 2023-01-01
    “…Considering the scarcity of wells in Aitegle Sag, we have systematically carried out the research on the sequence structure and sedimentary system evolution of the Lower Cretaceous based on seismic, core, and logging data, guided by the Vail classic sequence stratigraphy, and innovatively introduced the self-organizing mapping neural network (SOM) learning algorithm to assist in seismic geological analysis. …”
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  4. 324

    Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. by Niels Röckendorf, Markus Borschbach, Andreas Frey

    Published 2012-01-01
    “…The influence of different evolutional parameters and mechanisms such as mutation rate, crossover probability, gaussian variation and fitness value scaling on the course of this artificial evolutional process was investigated. …”
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  5. 325

    Data Validation Algorithm for Wireless Sensor Networks by Jaichandran Ravichandran, Anthony Irudhayaraj Arulappan

    Published 2013-12-01
    “…Performance of the algorithms is evaluated using real data samples of WSNs prototype for environment monitoring injected with different types of data faults such as out-of-range faults, struck-at faults, and outliers and spike faults. …”
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  6. 326

    Difference in Quality and Volatile Flavor Compounds of Zingiber officinale Roscoe with Different Drying Methods by Jiani Chen, Jinhua Wang, Yonghui Ge, Hongrui Ping, Wenxuan Liu

    Published 2023-01-01
    “…Ester and aldehyde compounds were identified as the main flavor components in dried ginger, with variations observed among the different drying methods. Principal component analysis (PCA) and the nearest neighbor algorithm successfully distinguished the ginger samples treated with different drying methods. …”
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    The Impact of Void-finding Algorithms on Galaxy Classification by Fatima Zaidouni, Dahlia Veyrat, Kelly A. Douglass, Segev BenZvi

    Published 2024-01-01
    “…We explore how the definition of a void influences the conclusions drawn about the impact of the void environment on galactic properties using two void-finding algorithms in the Void Analysis Software Toolkit: Voronoi Voids ( V ^2 ), a Python implementation of ZOnes Bordering On Voidness ( ZOBOV ); and VoidFinder , an algorithm that grows and merges spherical void regions. …”
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  9. 329

    Benchmarking network algorithms for contextualizing genes of interest. by Abby Hill, Scott Gleim, Florian Kiefer, Frederic Sigoillot, Joseph Loureiro, Jeremy Jenkins, Melody K Morris

    Published 2019-12-01
    “…Our work highlights strengths and weaknesses of each algorithm and results in a recommendation of algorithms best suited for performing different tasks.…”
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  10. 330

    Five-Year Evaluation of Sentinel-2 Cloud-Free Mosaic Generation Under Varied Cloud Cover Conditions in Hawai’i by Francisco Rodríguez-Puerta, Ryan L. Perroy, Carlos Barrera, Jonathan P. Price, Borja García-Pascual

    Published 2024-12-01
    “…We conducted a comparative analysis of three cloud-masking methods: two Google Earth Engine algorithms (CloudScore+ and s2cloudless) and a new proprietary deep learning-based algorithm (L3) applied to Sentinel-2 imagery. …”
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    Current-to-Best Crossover for Modified Jaya Algorithm by Sandeep Kumar Mogha, Sonal Deshwal, Pravesh Kumar

    Published 2025-08-01
    “…The newly designed crossover operation manages the population diversity, while the second approach helps to amplify the convergence rapidity of the algorithm. The proposed MCrJaya is verified on 54 benchmark problems from different test suits and three real-life applications of IEEE CEC 2011. …”
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  13. 333

    Stability of feature selection algorithm: A review by Utkarsh Mahadeo Khaire, R. Dhanalakshmi

    Published 2022-04-01
    “…High stability of the feature selection algorithm is equally important as the high classification accuracy when evaluating feature selection performance. …”
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  14. 334

    QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

    Published 2013-01-01
    “…Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. …”
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  15. 335

    On the Effectiveness of Optimisation Algorithms for Hydrodynamic Lubrication Problems by František Kocman, Pavel Novotný

    Published 2025-05-01
    “…This study evaluates the most commonly used algorithms, including the genetic (GA), particle swarm (PSWM), pattern search (PSCH) and surrogate (SURG) algorithms. …”
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  16. 336

    Digital Watermarking using Dragonfly Optimization Algorithm by Satender Sharma, Usha Chauhan, Ruqaiya Khanam, Krishna Kant Singh

    Published 2020-12-01
    “…The proposed method is applied on different images to evaluate the performance. The results obtained are compared with other state of the art methods.…”
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    On Decision-Making Algorithms in Discrete Optimization Problems by Yulia Terentyeva

    Published 2023-10-01
    “…The article provides a comparative analysis of the efficiency of using several predictor functions, i.e. special auxiliary functions a priori evaluating the feasibility of choosing a separating element for a certain iterative algorithm. …”
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    Numerical Investigation of Large Wood Evolution Characteristics Transported by Flash Floods by SONG Siyuan, FEI Gaogao, WANG Xiekang

    Published 2024-01-01
    “…The two-way coupling algorithm can reflect the influence of large wood on water flow, thereby allowing the analysis of backwater rise problems caused by logjams. …”
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    Valuation and compensation selection algorithm of simulation interferences by S. V. Kozlov

    Published 2019-06-01
    “…Using estimated-compensation method the selection it's motivated the algorithm simulation of interference evaluating the time of arrival and complex amplitude of the output signal consistent with the true signal of the filter, the weight subtracting the copy of the true signal from the input implementation, the formation of sufficient statistics for the two alternatives are «slow» and «fast» differences false signal from the true and comparing them with the threshold. …”
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