Showing 1,681 - 1,700 results of 2,280 for search '(variable OR variables) function ((coefficiency. OR efficiency.) OR efficient.)', query time: 0.24s Refine Results
  1. 1681

    Automated Geographic Information System Multi-Criteria Decision Tool to Assess Urban Road Suitability for Active Mobility by Bertha Santos, Sandro Ferreira, Pollyanna Lucena

    Published 2024-11-01
    “…The treatment, representation, and study of the variables considered in the analysis are carried out with the aid of geoprocessing, using the spatial and network analysis tools available in the GIS. …”
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  2. 1682
  3. 1683

    An Optimization Strategy for Generator Start-up Sequence After Blackouts Considering the Cyber System Fault by Mingming LI, Lei SUN, Yinghao MA

    Published 2022-09-01
    “…An optimal start-up sequence model of generators is proposed with the expectation of maximum power systems’ total generation as objective function, and taking into account the constraints including the start-up time constraint of generator units, the auxiliary variables constraint related to the cyber system fault, and the start-up power constraint of generator units. …”
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  4. 1684

    A Computational Approach to Increasing the Antenna System’s Sensitivity in a Doppler Radar Designed to Detect Human Vital Signs in the UHF-SHF Frequency Ranges by David Vatamanu, Simona Miclaus

    Published 2025-05-01
    “…In the context of Doppler radar, studies have examined the changes in the phase shift of the S<sub>21</sub> transmission coefficient related to minute movements of the human chest as a response to breathing or heartbeat. …”
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  5. 1685

    Analysis of factors influencing the increase of extracellular water ratio in tumor patients without edema signs by Heling Zhu, Panpan Gan, Hao Jiang, Liangliang Bao, Chengjiang Liu, Jiawen Yu, Jiawen Yu

    Published 2025-08-01
    “…PA was the most influential factor among all independent variables affecting ECW/TBW (B = −1.006, p &lt; 0.001). …”
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  6. 1686

    Torsional Vibration Suppression During Mode Transition Process in a Parallel Hybrid Electric Vehicle Based on Multiple Model Predictive Control by Cheng Huang, Changqing Du, Longjian Li, Xiangyu Gongye, Yifan Zhao

    Published 2024-01-01
    “…At the same time, the influence of the cost function, the weight coefficient, and the predictive time domain on the torsional vibration suppression effect during the mode transition process are explored in the mMPC strategy design, and the solution time is controlled within 10ms, which meet the real-time requirements. …”
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  7. 1687

    Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences by Alessandra Traini, Massimo Iorizzo, Harpartap Mann, James M. Bradeen, Domenico Carputo, Luigi Frusciante, Maria Luisa Chiusano

    Published 2013-01-01
    “…However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. …”
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  8. 1688

    Improved basal drag of the West Antarctic Ice Sheet from L-curve analysis of inverse models utilizing subglacial hydrology simulations by L.-S. Höyns, L.-S. Höyns, L.-S. Höyns, T. Kleiner, A. Rademacher, M. Rückamp, M. Wolovick, M. Wolovick, A. Humbert, A. Humbert

    Published 2025-06-01
    “…Since we cannot directly measure basal properties on a large scale, inverse models can be used to infer the basal drag coefficient by minimizing a cost function that depends on a velocity misfit and a regularization term.…”
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  9. 1689

    Correlation of the FIB-4 Liver Biomarker Score with the Severity of Heart Failure by Roxana Buzas, Paul Ciubotaru, Alexandra Corina Faur, Marius Preda, Melania Ardelean, Doina Georgescu, Patrick Dumitrescu, Daniel Florin Lighezan, Mihaela-Diana Popa

    Published 2024-11-01
    “…Statistical analysis was based on ANOVA one-way tests for continuous variables and Chi-square tests for categorical variables. …”
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  10. 1690

    Modeling and Regulation of Dynamic Temperature for Layer Houses Under Combined Positive- and Negative-Pressure Ventilation by Lihua Li, Min Li, Yao Yu, Yuchen Jia, Zhengkai Qian, Zongkui Xie

    Published 2024-10-01
    “…Additionally, a temperature control method for a layer house is designed using a variable universe fuzzy PID control algorithm (VFPID). …”
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  11. 1691

    Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach by Alireza Naeini, Alireza Jalali, Ehsan Houshfar

    Published 2025-09-01
    “…A neural network model is utilized to predict how the objective functions vary with six decision variables. The chosen optimization approach utilizes the genetic algorithm (GA) method. …”
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  12. 1692

    Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

    Published 2021-05-01
    “…BBO has demonstrated good performance on various unconstrained and constrained benchmark functions. It has also been applied to real world optimization problems of type linear or nonlinear, nominal or ordinal as well as mixed variables. …”
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  13. 1693

    Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China by Xuepeng Zhang, Taixia Wu, Qiqi Du, Ninglei Ouyang, Wei Nie, Yang Liu, Peng Gou, Guangchao Li

    Published 2025-01-01
    “…Based on this idea, a new framework for assessing EH is proposed. The efficient machine learning model (light gradient boosting machine model) and the variable explanation model (SHapley Additive exPlanation model) are combined to quantify the functional relationships between various driving factors and EH, thereby exploring the impacts of climatic factors, socioeconomic development (SED), and ecological restoration projects (ERP) on EH. …”
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  14. 1694

    Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

    Published 2024-07-01
    “…Taking these process parameters (<italic>x</italic>, <italic>y</italic>, <italic>z</italic>, <italic>d</italic>, <italic>h</italic>, <italic>n</italic>, <italic>a</italic><sub>p</sub>, <italic>a</italic><sub>e</sub>, <italic>f</italic><sub>z</sub>) as design variables, a multi-objective optimization model is constructed to balance machining efficiency and tool life. …”
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  15. 1695

    Application of a novel metaheuristic algorithm inspired by connected banking system in truss size and layout optimum design problems and optimization problems by Mehrdad Nemati, Yousef Zandi, Jamshid Sabouri

    Published 2024-11-01
    “…Abstract Optimum design of truss structures can be a challenging and difficult field of study specially if an optimum design problem is comprised of continuous and discrete decision variables such as in truss size and layout optimization problems. …”
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  16. 1696
  17. 1697

    Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer by Ashley M Henneghan, Emily W Paolillo, Kathleen M Van Dyk, Oscar Y Franco-Rocha, Soyeong Bang, Rebecca Tasker, Tara Kaufmann, Darren Haywood, Nicolas H Hart, Raeanne C Moore

    Published 2025-01-01
    “…Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. …”
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  18. 1698

    Effect of design and kinematic parameters on energy requirement in inclined screw mixer by V. F. Khlystunov, S. V. Braginets, A. S. Alferov, M. V. Chernutskiy

    Published 2018-12-01
    “…The establishment of functional dependences between parameters and modes enables to design power-efficient equipment for the on-farm feed production.Materials and Methods. …”
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  19. 1699

    Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

    Published 2025-04-01
    “…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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  20. 1700

    Forecasting Electricity Production in a Small Hydropower Plant (SHP) Using Artificial Intelligence (AI) by Dawid Maciejewski, Krzysztof Mudryk, Maciej Sporysz

    Published 2024-12-01
    “…Renewable Energy Sources (RESs) are difficult to predict due to weather variability. Electricity production by a run-of-river SHP is marked by the variability related to the access to instantaneous flow in the river and weather conditions. …”
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