Machine Learning-Based Modelling and Predictive Maintenance of Turning Operation under Cooling/Lubrication for Manufacturing Systems by Gurpreet Singh, Jothi Prabha Appadurai, Varatharaju Perumal, K. Kavita, T. Ch Anil Kumar, DVSSSV Prasad, A. Azhagu Jaisudhan Pazhani, K. Umamaheswari

“…These three processes are developed to predict the machine learning force, cutting power, and cutting pressure by controlling primary factors (cutting speed, depth of cut, and feed rate). …”
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Assessing the predictive power of immune microenvironment-related genes and clinical immune-inflammatory parameters in breast cancer by Shangyi Lu, Shun Liang, Fucai Chen, Jianyuan Meng, Junwei Chen, Yi Lu, Gangjian Zhu

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Research on Feed Forward Adaptive-generalized Model Predictive Control for High-speed Train Automatic Operation by LUO Yuan, YI Jie, BAI Jinlei, ZHANG Zhengfang

“…Furthermore, a feed forward generalized prediction speed tracking control algorithm is designed based on the multi-object function, aiming to solve controller overshoot due to additional resistance changes and enhance control convergence rates. …”
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Improved Modulated Model Predictive Control: Reducing Total Harmonic Distortion, Computational Burden, and Parameter Sensitivity by Seyed Rasul Eftekhari, Ali Mosallanejad, Hamidreza Pairo, Jose Rodriguez

“…This paper presents an improved modulated model predictive control (M2PC) method, which is implemented on synchronous reluctance motor (SynRM) drives, significantly enhancing performance by streamlining the control algorithm. …”
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Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control by R. Nagai, Y. Bai, M. Ogura, M. Ogura, S. Kotsuki, S. Kotsuki, N. Wakamiya

“…This study evaluates CSE's efficacy against model predictive control (MPC), a well-established method in control engineering. …”
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Predictive modeling of Bifidobacterium animalis subsp. lactis Bb-12 growth in cow’s, goat’s and soy milk by Vedran Slačanac, Mirela Lučan, Jovica Hardi, Kristina Habschied, Vinko Krstanović, Goran Gagula

“…The aim of this study was to use a predictive model to analyse the growth of a probiotic strain Bifidobacterium animalis subsp. lactis Bb-12 in cow’s, goat’s and soy milk. …”
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Long-Horizon Direct Model Predictive Control for Medium-Voltage Converters Connected to a Distorted Grid by Andrei Tregubov, Petros Karamanakos, Ludovico Ortombina

“…Long-horizon finite control set model predictive control (FCS-MPC) is known for its superior performance, particularly when applied to complex, higher order systems, such as grid-connected converters with <inline-formula><tex-math notation="LaTeX">$LCL$</tex-math></inline-formula> filters. …”
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A reliable mixed-integer linear programming formulation for data-driven model predictive control in buildings by Peter Klanatsky, François Veynandt, Christian Heschl

“…Integrating renewable energy sources into buildings requires advanced control strategies to enhance demand-side flexibility. Data-driven Model Predictive Control (DMPC) has shown significant promise in this area. …”
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Hierarchical predictive optimal control for range extension of EV with ANN based torque control for IPMSM drives by Lekshmi S, Lal Priya P S

“…The approach involves a hierarchical control scheme that integrates a model predictive controller with a torque vectoring algorithm to optimize torque demand and accurately anticipate road-specific torque requirements. …”
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Extended State Observer-Based Robust Model Predictive Velocity Control for Permanent Magnet Synchronous Motor by Eunji Lee, Yonghao Gui, Sesun You, Jun Moon, Wonhee Kim

“…This article proposes an extended state observer based robust model predictive velocity control to decrease system prediction error under parameter uncertainties for permanent magnet synchronous motor (PMSM). …”
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Predictive analysis of solubility data with pressure and temperature in assessing nanomedicine preparation via supercritical carbon dioxide by Hashem O. Alsaab, Yusuf S. Althobaiti

“…Three models, namely Automatic Relevance Determination Regression (ARD), Gaussian process regression (GPR), and Linear Regression (LR) were designed and tuned to build predictive models. The ADABOOST ensemble technique was applied to strengthen the predictive capabilities of the models, while hyperparameter tuning was conducted using the Jellyfish Optimization (JO) algorithm. …”
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Enhanced Inverse Model Predictive Control for EV Chargers: Solution for DC&#x2013;DC Side by Abdullah Berkay Bayindir, Ali Sharida, Sertac Bayhan, Haitham Abu-Rub

“…To address this challenge, the proposed method employs an adaptive estimation strategy utilizing a recursive least square algorithm for online dynamic model estimation. This real-time estimated model enables IMPC to predict optimal switching states with improved reliability. …”
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Improving the Performance of Steering by Wire Using a Model Predictive Controller Enhanced with Particle Swarm Optimisation by Taher Alhassany, Ali Hussien Mary, Furat Ibrahim Hussein, Mohammed Ghufran Khidhir Abboosh, Muhammad Umar Fareed

“…The current study introduces an innovation of a model that integrates model predictive control (MPC) with particle swarm optimisation (PSO) to improve the performance of SBW systems. …”
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Learning-Based Model Predictive Control for Legged Robots with Battery–Supercapacitor Hybrid Energy Storage System by Boyu Shu, Zhiwu Huang, Wanwan Ren, Yue Wu, Heng Li

“…This article proposes a learning-based model predictive control (MPC) energy management strategy for legged robots with battery–supercapacitor hybrid energy storage systems containing a power prediction unit and an MPC with learning-based adaptive weights. …”
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Predictive modeling of graves’ orbitopathy activity based on meibomian glands analysis using in vivo confocal microscopy by Zixuan Su, Yayan You, Shengnan Cheng, Jiahui Huang, Xueqing Liang, Xinghua Wang, Fagang Jiang

“…Subsequently, a logistic regression model was constructed to predict GO disease activity. Results A total of 45 GO patients, corresponding to 90 eyes, were included in this study. …”
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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

“…This study examined the modeling and control of AVR in hydroelectric power plants using model predictive control (MPC), which utilizes an extensive mathematical model of the voltage regulation system to optimize the control actions over a defined prediction horizon. …”
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Intelligent predictive networks for MHD nanofluid with carbon nanotubes and thermal conductivity along a porous medium by Hafiz Muhammad Shahbaz, Iftikhar Ahmad

“…The reduced MSE reveals that predictions of model are less likely to deviate from the true values and are more accurate this validates the proposed approach.…”
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Integrated multi-omics analysis and predictive modeling of heart failure using sepsis-related gene signature. by Yiping Lang, Tianyu Liang, Fei Li

“…This study aimed to develop a predictive model for HF based on sepsis-related gene signatures.…”
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The predictive value of radiomics and deep learning for synchronous distant metastasis in clear cell renal cell carcinoma by Wan-Bin He, Chuan Zhou, Zhi-Jun Yang, Yun-Feng Zhang, Wen-Bo Zhang, Han He, Jia Wang, Feng-Hai Zhou

“…Abstract Objective The objective of this research was to devise and authenticate a predictive model that employs CT radiomics and deep learning methodologies for the accurate prediction of synchronous distant metastasis (SDM) in clear cell renal cell carcinoma (ccRCC). …”
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Predictive modeling for the adsorptive and photocatalytic removal of phenolic contaminants from water using artificial neural networks by Shahzar Hafeez, Ayesha Ishaq, Azeem Intisar, Tariq Mahmood, Muhammad Imran Din, Ejaz Ahmed, Muhammad Rizwan Tariq, Muhammad Amin Abid

“…The comparison of ANNs with other AI techniques revealed that ANNs have better predictability for mitigation of most of the phenolic contaminants. …”
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