Power System Stabilizer based on Model Predictive Control by Manuel A Duarte-Mermoud, Freddy Milla

“…A model predictive power system stabilizer is proposed in this paper to damp power oscillations in an electric power system (EPS). …”
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APPLICATION OF MODEL PREDICTIVE CONTROL TO BATCH POLYMERIZATION REACTOR by N.M. Ghasem, M.A. Hussain, S. A. Sata

“…In this study, advanced control methodology is implemented for controlling the operation of a batch polymerization reactor for polystyrene production utilizingmodel predictive control. By utilizing a model of the polymerization process, the necessary operational conditions were determined for producing the polymer within the desired characteristics. …”
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Predictive potential of the bankruptcy global models in the tourism industry by Agustín Del Castillo García, Sergio Manuel Fernández Miguélez

“…As a consequence, previous research has provided bankruptcy prediction models both of a global nature for certain industries or regions of the world, and models focused on certain economic activities. …”
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Global distribution and predictive modeling of Vibrio vulnificus abundance by David J. Riedinger, Christiane Hassenrück, Daniel Herlemann, Matthias Labrenz

“…A poleward trend could accelerate due to climate change-induced modifications of phytoplankton dynamics and currents; factors that should be integrated into predictive modelling to estimate future risks.…”
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Model Predictive Control Used in Passenger Vehicles: An Overview by Meaghan Charest-Finn, Shabnam Pejhan

Subjects: “…Model Predictive Controls…”
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Informing Disaster Recovery Through Predictive Relocation Modeling by Chao He, Da Hu

“…These findings underscore the value of advanced predictive models in disaster recovery planning, particularly in geographically vulnerable regions like New Orleans where accurate relocation forecasting can guide more effective policy interventions.…”
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Data-driven predictive models for sustainable smart buildings by Prabhu Rajaram, Gnana Swathika O․V․

“…This analytical tool is instrumental in pinpointing the most influential attributes necessary for effective model training. By streamlining the feature selection process, ANOVA not only enhances the performance of the models but also conserves computational resources, making the approach more efficient overall. …”
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Predictive modeling of glioblastoma recurrence for therapeutic target identification by Hrvoje Miletic, Thomas Daubon

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Development of the predictive model for I stage breast cancer by A. Kh. Ismagilov, A. S. Vanesyan, D. R. Khuzina

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Risk Factors and Predictive Models for Sarcopenia in Older Adults by Shiyuan Zhang, Xue Yang, Nina An, Meng Lv, Lanyu Yang, Rui Liu, Song Hu, Weiguo Chen, Wenjing Feng, Yongjun Mao

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On modeling approaches for the predictive simulation of living systms dymamics by Ivan Mura

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Predictive modeling of biodegradation pathways using transformer architectures by Liam Brydon, Kunyang Zhang, Gillian Dobbie, Katerina Taškova, Jörg Simon Wicker

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Predictive Models for Educational Purposes: A Systematic Review by Ahlam Almalawi, Ben Soh, Alice Li, Halima Samra

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Toxic Workplace, Workstress, and Employee Performance: Predictive Model by Eko Agus Prasetyo, Ayya Maghfirah, Ali Ridho, Fathul Lubabin Nuqul, Muallifah Muallifah, Iin Tri Rahayu

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Predictive analysis of doubly Type-Ⅱ censored models by Young Eun Jeon, Yongku Kim, Jung-In Seo

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RETRACTED: Biomaterials and Artificial Intelligence: Predictive Modeling and Design by Rajitha Akula, Kansal Lavish, Raj Gowtham, Kalra Ravi, Dhamija Koushal, Abdul-Zahra Dalael Saad

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Transforming Drug Discovery with Miniaturized Predictive Tissue Models by Mohsen Akbari

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Predictive Model for Incipient Faults in Oil-Filled Transformers by Michael Osajeh, Linda Usiosefe, Efosa Igodan

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Indicators of Violence Levels: Questionnaires and Predictive Mathematical Model by E. Leal-Enríquez, A. R. Gutiérrez-Antúnez

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Predicting Financial Market Volatility with Modern Model and Traditional Model by R. G. Aldeki

“…There is evidence that the GARCH-SVR model performs best for predicting volatility time series, and classical volatility model techniques have an enormous predictive performance better than machine learning models.…”
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