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Showing 981 - 1,000 results of 2,280 for search '(( variable function coefficiency. ) OR ( variables function efficient. ))', query time: 0.23s Refine Results
  1. 981

    The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

    Published 2019-03-01
    “…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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  2. 982

    Response Surface Optimization of CuS Photocatalytic Process Using UV‐vis Irradiation for Wastewater Treatment by Caressa Munien, Emmanuel Kweinor Tetteh, Sudesh Rathilal

    Published 2025-06-01
    “…Thus, this study aimed to optimize the operating parameters of the photocatalytic degradation process using copper sulphide (CuS) and UV‐visible irradiation via response surface methodology (RSM) to determine the relationship that exists between the most significant factors and the water quality parameters. The efficiency of the CuS photocatalyst was evaluated as a function of three input variables viz. …”
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  3. 983

    Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

    Published 2025-07-01
    “…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
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  4. 984

    Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

    Published 2025-06-01
    “…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
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  5. 985

    Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases by Adel M. Hemeida, Mohammed S. Al-Blehed, Saad El-Din Desouky

    Published 1995-01-01
    “…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. …”
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  6. 986

    Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor by Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, Gustavo Scaglia

    Published 2017-01-01
    “…The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. …”
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  7. 987

    Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

    Published 2025-03-01
    “…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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  8. 988

    Flow-based cytometric analysis of cell cycle via simulated cell populations. by M Rowan Brown, Huw D Summers, Paul Rees, Paul J Smith, Sally C Chappell, Rachel J Errington

    Published 2010-04-01
    “…We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. …”
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  9. 989

    Parametric Survival Models of Hemodialysis Patients in Relation with Patient-Related Factors by Reem Yousif MEKKI, Mohamed Hassan MUDAWI, Manahil Saidahmed MUSTAFA, Altaiyb Omer Ahmed MOHMMED, Ahmed Bakheet Abd ALLA, Abdel Rahman AHMED

    Published 2020-12-01
    “…Based on the Cox-Snell Residuals and AIC, BIC, and Gompertz (PH) model is an efficient model than other when the values of (AIC=662.21), (BIC=703.83) and (R2=0.211) where maintained Study assessed that the variables dealing with univariate models were signifi cant but had a signifi cant effect on hemodialysis survival. …”
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  10. 990

    A theory and data-driven method for rapid bottom hole pressure calculation in UGS by Yang Li, Haiwei Guo, Xianfeng Gong, Naixin Lu, Kairui Zhang

    Published 2025-03-01
    “…To enhance the operational and maintenance efficiency of UGS, this paper innovatively proposes a new method for calculating bottom hole pressure. …”
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  11. 991

    A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

    Published 2025-07-01
    “…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
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  12. 992

    A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM by Sorin IONITESCU

    Published 2023-01-01
    “…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
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  13. 993

    FUNGSI GREEN UNTUK PERSAMAAN DIFUSI-ADVEKSI DENGAN SYARAT BATAS DIRICHLET by Josua Josua, Evi Noviani, Fransiskus Fran

    Published 2020-06-01
    “…Mathematically, diffusion-advection equation can be written as  where  is concentration of material in the fluid, stands for the advection velocity, and  for diffusion coefficient. In this paper, a solution  is sought by using the Green’s function concept. …”
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  14. 994

    The effects of IT capability and distribution competence on business performance of retailers in Omnichannel by Anh T.D. Nguyen

    Published 2025-03-01
    “…Results: Information technology capability and distribution competence have a direct impact on business performance, with beta coefficients of 0.198 and 0.271, respectively. Meanwhile, the regression coefficients of indirect relationships through mediating variables are 0.204 and 0.097, respectively. …”
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  15. 995

    Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks by Ehsan Kharati

    Published 2024-02-01
    “…For this purpose, we need to calculate the derivative of the Lagrangian function relative to its variables, in order to determine the condition as a multi-excited multi-equation device. …”
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  16. 996

    Nonparametric Test for Logistic Regression with Application to Italian Enterprises’ Propensity for Innovation by Stefano Bonnini, Michela Borghesi

    Published 2024-09-01
    “…In this work, a nonparametric method is proposed to jointly test the significance of the regression coefficient estimates in a logistic regression model and identify which explanatory variables are effective in predicting the binary response. …”
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  17. 997

    Comparative Study on the Treatment Effect of Stretching and High-frequency Diathermy in Subjects With Gastrocnemius Tightness by Beom-Seop Kim, Yixin Wang, Ye-Jin Kim, Min-Young Kim, Hye-Seon Jeon

    Published 2025-04-01
    “…Background: Ankle flexibility is important for maintaining proper biomechanical function. Static stretching is used to improve flexibility with minimal risk; however, its effects are often temporary. …”
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  18. 998

    Cultivares de trigo submetidas a déficit hídrico no início do florescimento, em casa de vegetação Wheat cultivars submitted to water deficit at the beginning of flowering in greenh... by Diego dos Santos, Vandeir F. Guimarães, Jeferson Klein, Samuel L. Fioreze, Eurides K. Macedo Júnior

    Published 2012-08-01
    “…Reduction was found in the gravimetric soil moisture, in the relative levels of water and in all biometric variables, in function of the water deficit. The grain production showed difference only among the water regimes, in which the cultivar CD 111 is more efficient in the maintenance of the productive potential in conditions of water deficit, through the quick recovery in the relative content of water in leaves.…”
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  19. 999

    Center of Largest Area Defuzzifier Vnit VLSI Architecture by Asim Majeed Murshid, Ahmed Chalak Shakir, Sarmed Nihad Mohammed

    Published 2023-02-01
    “…The functional analysis has revealed that the proposed architecture is implementing COLA based defuzzifier efficiently and accurately. …”
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  20. 1000

    Inference of Impulse Responses via Bayesian Graphical Structural VAR Models by Daniel Felix Ahelegbey

    Published 2025-04-01
    “…Impulse response functions (IRFs) are crucial for analyzing the dynamic interactions of macroeconomic variables in vector autoregressive (VAR) models. …”
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