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Showing 981 - 1,000 results of 2,280 for search 'variables function (coefficient. OR efficient.)', query time: 0.17s Refine Results
  1. 981

    Prediction of Pile Bearing Capacity Using Opposition-Based Differential Flower Pollination-Optimized Least Squares Support Vector Regression (ODFP-LSSVR) by Nhat-Duc Hoang, Xuan-Linh Tran, Thanh-Canh Huynh

    Published 2022-01-01
    “…Based on such datasets, LSSVR is capable of generalizing a multivariate function that estimates values of pile bearing capacity based on a set of variables describing pile characteristics and ground conditions. …”
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    Article
  2. 982

    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
  3. 983
  4. 984

    Three-Dimensional Modified Cross-Section Hydrofoil Design and Performance Study by Hongpeng Cao, Yudong Xie, Zilei Ji

    Published 2025-04-01
    “…To improve the hydrodynamic performance of hydrofoils, this study combines the shape characteristics of flat and elliptical wings, uses parabolic function to fit the leading and trailing edges of hydrofoils, introduces the cross-section coefficient <i>λ</i> to characterize the cross-sectional size of hydrofoils along the spreading direction, and designs five hydrofoils with different cross-sections. …”
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    Article
  5. 985

    Analyzing Worn-Out Texture Regeneration from Urban Branding Perspective Using Structural Equation Modeling (SEM) (Case Study: Worn-Out Texture of Shahr-e-Kord) by Dvood Mahdavi, Ali Mohammadi Gojani, Waliullah Nazari

    Published 2024-06-01
    “…Furthermore, the findings demonstrated a strong, positive, and significant influence of the branding variable on the regeneration of the worn-out urban fabric with an impact coefficient of 0.833. …”
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    Article
  6. 986

    THE BONITATION METHOD FOR ASSESSING THE FERTILITY OF THE CHERNOZEM by Mariana BURCEA, Nicoleta OLTENACU

    Published 2019-01-01
    “…Statistical indicators have been determined using the functions from Excel Program, such as: average, standard deviation, coefficient of variability, annual growth rate. …”
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    Article
  7. 987

    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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    Article
  8. 988

    Impact of adopting improved Arabica varieties on the livelihood of organic coffee producers’ of Ethiopia: Continuous treatment approach by Negussie Zeray Gebru, Tasew Tadesse, Wajana Wae

    Published 2024-12-01
    “…The technique proved efficient in elucidating non-linear causal links between adoption intensities, dosages, and outcome variables. …”
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    Article
  9. 989

    Experimental Study and Damage Model Study of Rock Salt Subjected to Cyclic Loading and Cyclic Creep by Baoyun Zhao, Tianzhu Huang, Liu Dongyan, Dongsheng Liu, Yang Liu, Xiaoping Wang

    Published 2020-01-01
    “…The damage model is obtained by inverse functioning the s function, and then the correction coefficient is added to the model to obtain the modified damage model. …”
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    Article
  10. 990

    Experimental Studies of Heat and Moisture Exchange in the Process of Convective Drying of Thin Wet Materials by A. I. Ol’shanskii, S. V. Zhernosek, A. M. Gusarov

    Published 2018-12-01
    “…New ways of experimental data processing by generalized complex variables that are characteristic of the drying process are presented. …”
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    Article
  11. 991

    A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete by Nhat-Duc Hoang, Van-Duc Tran

    Published 2025-04-01
    “…Experimental results show that the L1 regularization helps achieve the most desired performance, with a coefficient of determination (R2) of roughly 0.96. Notably, an asymmetric loss function is used along with Nadam to decrease the percentage of overestimated cases from 50.83% to 27.08%. …”
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    Article
  12. 992

    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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    Article
  13. 993

    Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

    Published 2025-09-01
    “…The diffusion coefficient extracted from the moisture ratio function was used to assess the drying kinetics, while SEC was used to evaluate the energy efficiency of the EHD dehydrator under different parameter settings. …”
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    Article
  14. 994

    A 3D mixed frame element with multi-axial coupling for thin-walled structures with damage by D. Addessi, P. Di Re

    Published 2014-07-01
    “…The beam formulation is derived on the basis of the Hu-Washizu variational principle, expressed as function of four independent fields: the standard displacements, strains and stresses and the additional warping displacement. …”
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    Article
  15. 995

    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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    Article
  16. 996

    Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

    Published 2023-12-01
    “…The independent treatment variables were two climatic factors and five human activity factors affecting vegetation changes in East Africa. …”
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    Article
  17. 997

    Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

    Published 2024-01-01
    “…Results revealed that all NN models particularly PSO-NNs were efficient in prediction of Kfs. However, further evaluations may be recommended for other soil conditions and input variables to quantify their potential uncertainties and wider potential and versatility before they are used in other geographical locations/soil conditions.…”
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    Article
  18. 998

    A Fusion Method Based on Physical Modes and Satellite Remote Sensing for 3D Ocean State Reconstruction by Yingxiang Hong, Xuan Wang, Bin Wang, Wei Li, Guijun Han

    Published 2025-04-01
    “…This study developed an operational-oriented lightweight framework for three-dimensional ocean state reconstruction by integrating multi-source observations through a computationally efficient multivariate empirical orthogonal function (MEOF) method. …”
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  19. 999

    Research on optimization strategies of university ideological and political parenting models under the empowerment of digital intelligence by Fan Lv

    Published 2025-03-01
    “…It constructs the no-incentive, cost-sharing, and collaborative cooperation models, respectively, and obtains the optimal trajectories for the degree of effort, the subsidy coefficient, the optimal benefit function, and the digital and intelligent technology stock. …”
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    Article
  20. 1000

    Artificial Neural Network (ANN) Modeling of Plasma and Ultrasound-assisted Air Drying of Cumin Seeds by M. Namjoo, M. Moradi, M. A. Nematollahi, H. Golbakhshi

    Published 2025-03-01
    “…Therefore, the wavelet-based neural network (WNN), the multilayer perceptron neural network (MLPNN), and the radial-basis function neural network (RBFNN), as three well-known artificial neural networks models, were used to map the inputs and output data and the results were compared with the Multiple Quadratic Regression (MQR) analysis. …”
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