Model based multi-loop predictive control scheme for multivariable processes by Arun Ramaveerapathiran, Muniraj Rathinam, Karuppiah Natarajan, Muthiah Athi, Patil Mounica

“…Abstract Industry applications of multi loop controller approaches are common because of their robustness, minimal tuning parameter, and straightforward design. A model based multi-loop predictive control method is presented. …”
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Monitoring land-use changes and predicting their spatio-temporal trends in Hamedan City by Naser Shafiei Sabet, Faranak Feyzbabaei cheshmeh sefidi

“…This land conversion has negative consequences for the region's future.Conclusion: In this study, it was found that the automatic cell model and Markov chain have a high ability to predict future land-use changes. …”
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Predicting Young’s Modulus of Aggregated Carbon Nanotube Reinforced Polymer by Roham Rafiee, Vahid Firouzbakht

“…Prediction of mechanical properties of carbon nanotube-based composite is one of the important issues which should be addressed reasonably. …”
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RESEARCH ON MODELING METHOD OF EQUIVALENT TURNING FORCE MODEL (MT) by WU MingZhou, ZHANG GuangPeng, GOU JianFeng, ZHANG Peng

“…A turning force prediction model based on the equivalent model is established. …”
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Prediction of Chlorophyll a in Kurtboğazı and Çamlıdere Reservoirs by Handan Çamdeviren, Sıddık Keskin, Nilsun Demır, &ccedil -

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A Fused Multi-Channel Prediction Model of Pressure Injury for Adult Hospitalized Patients—The “EADB” Model by Eba’a Dasan Barghouthi, Amani Yousef Owda, Majdi Owda, Mohammad Asia

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Heuristic modeling of the process of milling aviation parts with opposed end mills by synthesis of a predictive model by E. A. Shestakova, V. O. Ievlev, R. M. Yanbaev

“…The resulting model allows predicting the results of machining by the proposed method with an error of 10…15%.…”
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Two novel deep-learning models to predict spontaneous ureteral calculi passage: Model development and validation by Zhiying Xiao, Hui Bai, Yumeng Zhang

“…The aim of this study was to develop and evaluate two deep-learning (DL) models for predicting spontaneous ureteral stone passage (SSP). …”
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Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application by Eko Abdul Goffar, Rosa Eliviani, Lili Ayu Wulandhari

“…The literature review section discusses the factors that influence stunting, and these factors are used as features to build a stunting prediction model. Then the features were used to build a model with three machine learning algorithms Extreme Gradient Boosting (XGBoost), Random Forest, and K-Nearest Neighbor (KNN) to build and evaluate models that predict stunting. …”
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Development of a comprehensive model to predict stock prices in the stock market with an interpretive structural modeling approach by Shiva Rezaeyan, Mohammad Taleghani, Azita Sherej Sharifi

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Modeling and control of automatic voltage regulation for a hydropower plant using advanced model predictive control by Ebunle Akupan Rene, Willy Stephen Tounsi Fokui

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Morphological Model for Erosion Prediction of India’s Largest Braided River Using MIKE 21C Model by Kuldeep Pareta

“…The approach leverages predictive models to predict morphological changes over a 2–3 years timeframe, contributing to improved river management.…”
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Large language models' knowledge of children's memory and suggestibility: Evaluating model predictions of prior experimental results by Pekka Santtila, Yongjie Sun, Kristjan Kask, Liisa Järvilehto, Jiaxing Xiu

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To What Extent Does Discounting ‘Hot’ Climate Models Improve the Predictive Skill of Climate Model Ensembles? by Abigail McDonnell, Adam Michael Bauer, Cristian Proistosescu

“…The Intergovernmental Panel on Climate Change's (IPCC) Assessment Report Six (AR6) took a step toward ending so‐called ‘model democracy’ by discounting climate models that are too warm over the historical period (i.e., models that ‘run hot’) when making projections of global temperature change. …”
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Temporal trends and predictive modeling of air pollutants in Delhi: a comparative study of artificial intelligence models by Omer A. Alawi, Haslinda Mohamed Kamar, Ali Alsuwaiyan, Zaher Mundher Yaseen

“…The modelling results revealed that Bi-LSTM model had the best predictability performance for forecasting CO with (R2 = 0.979), NO with (R2 = 0.961), NO2 with (R2 = 0.956), SO2 with (R2 = 0.955), PM10 with (R2 = 0.9751) and NH3 with (R2 = 0.971). …”
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A robust multi-model framework for groundwater level prediction: The BFSA-MVMD-GRU-RVM model by Akram Seifi, Sharareh Pourebrahim, Mohammad Ehteram, Hanieh Shabanian

“…Finally, the extracted data is fed into the RVM model to predict groundwater levels one month ahead in Iran's Bastam Plain. …”
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Generalization of a fast, predictive model for tokamak scenario design in ASTRA and comparison to a RAPTOR model by Raphael Schramm, Alexander Bock, Emiliano Fable, Jörg Stober, Simon van Mulders, Marc Maraschek, Rainer Fischer, Andreas Burckhart, Philip Schneider, Olivier Sauter, Hartmut Zohm, the ASDEX Upgrade Team, JET Contributors

“…We have previously presented an analytical predictive model to aid in the AT scenario design, optimized for a single scenario (Schramm et al 2024 Nucl. …”
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A hybrid workflow connecting a network and an agent-based model for predictive pedestrian movement modelling by Anita Ullrich, Franziska Hunger, Ioanna Stavroulaki, Adam Bilock, Klas Jareteg, Yury Tarakanov, Alexander Gösta, Alexander Gösta, Johannes Quist, Meta Berghauser Pont, Fredrik Edelvik

“…This study outlines a comprehensive workflow tailored for urban planners. It proposes a hybrid model that integrates an agent-based model, which simulates the micro-scale movement of pedestrians in outdoor urban environments, with a network model, which predicts the aggregated pedestrian flows on a macro-scale. …”
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Joint Decision-Making Model Based on Consensus Modeling Technology for the Prediction of Drug-Induced Liver Injury by Yukun Wang, Xuebo Chen

“…Compared with the main published studies, our method exhibits certain advantage in data size, transparency, and standardization of the modeling process and accuracy and credibility of prediction results. …”
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Construction and application of optimized model for mine water inflow prediction based on neural network and ARIMA model by Xiaoyu Gong, Bo Li, Yu Yang, MengHua Li, Tao Li, Beibei Zhang, Lulin Zheng, Hongfei Duan, Pu Liu, Xin Hu, Xin Xiang, Xinju Zhou

Subjects: “…Mine influx prediction…”
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