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Showing 1,681 - 1,700 results of 2,280 for search '(( variable function coefficiency. ) OR ( variable function efficiency. ))*', query time: 0.14s Refine Results
  1. 1681

    Random Fuzzy Power Flow Analysis for Power System considering the Uncertainties of Renewable Energy and Load Demands by J. H. Zheng, Wenting Xiao, Zhigang Li, Q. H. Wu

    Published 2023-01-01
    “…Simulation studies conducted on the IEEE-33 system verifies the accuracy of the RFPF and the efficiency of the 3PE.…”
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    Article
  2. 1682

    Numerical Evaluation of Sound Attenuation Provided by Periodic Structures by Mario MARTINS, Luis GODINHO, Luis PICADO-SANTOS

    Published 2013-12-01
    “…The use of periodic structures as noise abatement devices has already been the object of considerable research seeking to understand its efficiency and see to what extent they can provide a functional solu- tion in mitigating noise from different sources. …”
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    Article
  3. 1683

    Cooperative Control of Interconnected Air Suspension Based on Energy Consumption Optimization by Guoqing Geng, Shuai Zeng, Liqin Sun, Zhongxing Li, Wenhao Yu

    Published 2022-01-01
    “…The optimal interval for suspension force is obtained through solving cost functions while satisfying a set of constraints on controlled variables and thereby reducing the coupling complexity of a multivariable control system. …”
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    Article
  4. 1684

    Translation and validation of Gujarati version of Indian HAQ in RA patients by Jaspreet Kaur Kang, Neeta J Vyas

    Published 2022-01-01
    “…Results: Internal consistency of each item was evaluated by Cronbach's alpha and the Construct validity was evaluated by determining Spearman's correlation between the Gujarati Indian HAQ score and disease activity variables. Reliability testing showed an intraclass coefficient for HAQ of 0. 848. …”
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    Article
  5. 1685

    Analysis of fuzzy TOPSIS Method in Determining Priority of Small Dams Construction by Desyta Ulfiana, Suharyanto Suharyanto

    Published 2019-10-01
    “…The first step was determining membership function and weighting each criteria. Then, TOPSIS method was applied to ranked eight alternatives. …”
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    Article
  6. 1686

    Hydrodynamic and sensitivity analysis of a polymeric calendering process for non-Newtonian fluids with temperature-dependent viscosity by Ali Fateh, Zahid Muhammad, Farmer M., Al Taisan Nada, Faqihi Abdullah A., Souayeh Basma, Raju S. Suresh Kumar, Alam Mir Waqas

    Published 2025-08-01
    “…Additionally, using the response surface method, Nusselt number (Nu)(\text{Nu}), sheet thickness HH0\left(\phantom{\rule[-0.75em]{}{0ex}},\frac{H}{{H}_{0}}\right), and shear stress (Sxy)({S}_{xy}), simulations were carried out to investigate the influence of variable viscoelastic parameters on the response functions (Nu\text{Nu}, HH0\frac{H}{{H}_{0}}, and Sxy{S}_{xy}). …”
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    Article
  7. 1687

    Optimization by RSM of reinforced concrete domes with meridian ribs, under static loading. by Logzit N., Raouache E., Bentoumi M., Bentoumi A., Khababa I.

    Published 2025-06-01
    “…Ultimately, a cost-oriented objective function is derived, incorporating a load-bearing capacity coefficient. …”
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    Article
  8. 1688

    Estimation of Above-Ground Biomass for <italic>Dendrocalamus Giganteus</italic> Utilizing Spaceborne LiDAR GEDI Data by Huanfen Yang, Zhen Qin, Qingtai Shu, Li Xu, Jinge Yu, Shaolong Luo, Zaikun Wu, Cuifen Xia, Zhengdao Yang

    Published 2025-01-01
    “…The outcomes reveal that 1) the results showed that the power function emerged as the most efficacious model, with coefficient of determination (<italic>R</italic><sup>2</sup>) &#x003D; 0.87 and root mean square error (RMSE) &#x003D; 0.00051 Mg, in estimating the AGB of <italic>Dendrocalamus giganteus</italic>. 2) Based on the feature importance ranking of Random Forest, five variables were selected from the 40 extracted from GEDI, achieving RMSE &#x003D; 8.21 Mg&#x002F;ha and mean absolute error (MAE) &#x003D; 6.12 Mg&#x002F;ha. …”
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    Article
  9. 1689

    New Approach of Blind Adaptive Equalizer Based on Genetic Algorithms by Caroline A. D. Silva, Marcelo A. C. Fernandes

    Published 2025-01-01
    “…Unlike traditional methods that rely on linear programming and suffer from local minima issues, this technique utilizes a stochastic linear programming cost function with GAs for robust optimization. The proposed method termed Blind Linear Equalizer based on genetic algorithm (BLE-GA) enhances performance by leveraging a GA’s ability to handle stochastic variables, offering rapid convergence and resilience against signal noise and inter-symbol interference. …”
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  10. 1690

    THE STRUCTURE OF HAPPINESS REPRESENTATION FOR RUSSIAN AND AMERICAN REPRESENTATIVES by S. Yu. Zhdanova, A. V. Pecherkina, A. A. Strokanov

    Published 2017-09-01
    “…Statistical analysis of the data was based on the use of the coefficient of φ-angular Fisher transform, correlation coefficient φ, and cluster analysis.Results and scientific novelty. …”
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    Article
  11. 1691

    Shell and tube heat exchanger optimization: A critical literature assessment and fairness-based comparative performance analysis of meta-heuristic algorithms by Samet Gürgen

    Published 2025-08-01
    “…In order to make comparisons, the objective function, decision variables and their boundary values were taken as the same. …”
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  12. 1692

    Binary composite crossover genetic algorithm for locating critical slip surface by Wei Qin, Jiancheng Zhao

    Published 2024-12-01
    “…A reasonable combination of parameters for the binary composite crossover (BCC) operator in the RGA-BCC is determined through six benchmark function experiments. On this basis, the stability of five soil slopes from the literature was analysed using the RGA-BCC in combination with the Morgenstern and Price method, and the results obtained were compared with those in the published literature to demonstrate that the RGA-BCC is able to efficiently determine the CSSs of slopes and their minimum factors of safety. …”
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  13. 1693

    Phenotypic screen of early-developing larvae of the blood fluke, schistosoma mansoni, using RNA interference. by M M Mourão, Nathalie Dinguirard, Glória R Franco, Timothy P Yoshino

    Published 2009-08-01
    “…Although RNAi holds great promise as a functional genomics tool for larval schistosomes, our finding of potential off-target or nonspecific effects of some dsRNA treatments and variable efficiencies in specific gene knockdown indicate a critical need for gene-specific testing and optimization as an essential part of experimental design, execution and data interpretation.…”
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  14. 1694

    Effects of two types of repetitive transcranial magnetic stimulation on brain network in Parkinson’s disease by Shuo Liu, Shuo Yang, Chen Wang, Jiarui Li, Lei Wang

    Published 2025-07-01
    “…The iTBS group showed post-treatment changes involving more brain regions in spatiotemporal variability. This study demonstrates that compared to 10Hz-rTMS, iTBS can reduce treatment time while providing superior improvement in functional brain connectivity for PD patients.…”
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  15. 1695

    Optimally controlled heating of solid particles in a fluidised bed with a dispersive flow of the solid by Poświata Artur, Szwast Zbigniew

    Published 2016-03-01
    “…The mixing rate was described by the axial dispersion coefficient. As any economic values of variables describing analysing process are subject to local and time fluctuations, the accepted objective function describes the total cost of the process expressed in exergy units. …”
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  16. 1696

    Time-varying MVAR algorithms for directed connectivity analysis: Critical comparison in simulations and benchmark EEG data. by Mattia F Pagnotta, Gijs Plomp

    Published 2018-01-01
    “…Results from numerical simulations and from benchmark EEG recordings showed that: i) across a broad range of model orders all algorithms correctly reproduced patterns of interactions; ii) signal downsampling degraded connectivity estimation accuracy for most algorithms, although in some cases downsampling was shown to reduce variability in the estimates by lowering the number of parameters in the model; iii) single-trial modeling followed by averaging showed optimal performance with larger adaptation coefficients than previously suggested, and showed slower adaptation speeds than multi-trial modeling. …”
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  17. 1697
  18. 1698

    Multiobjective Optimization of Stress-Release Boot of Solid Rocket Motor under Vertical Storage Based on RBF Model by Qiuwen Miao, Huihui Zhang, Zhibin Shen, Weiyong Zhou

    Published 2022-01-01
    “…Stress-release boot can effectively improve the structural integrity of SRM (solid rocket motor), but it will also influence the loading fraction and interior ballistic performance, so the purpose of this paper is to propose a multiobjective optimization method for stress-release boot. The design variables are the front and rear depth of the stress-release boot, and four optimization variables were determined according to the analysis of SRM performance. …”
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  19. 1699

    Comparative Analysis of ANFIS and State-ANFIS for Forecasting Cooking Oil Prices Based on Processed Palm Oil Yield (Crude Palm Oil) by Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Mochammad Reza Habibi, null Makkulau

    Published 2024-01-01
    “…Our analysis underscores S-ANFIS’s superiority over ANFIS, particularly with Gaussian membership functions, as it reduces RMSE and MAPE values by half while requiring fewer nodes, thereby improving computational efficiency. …”
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  20. 1700

    Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

    Published 2024-12-01
    “…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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