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  1. 1761

    Two-Layer Predictive Control of a Continuous Biodiesel Transesterification Reactor by Hongyan Shi, Dingding Wang, Decheng Yuan, Tianran Wang

    Published 2013-01-01
    “…A novel two-layer predictive control scheme for a continuous biodiesel transesterification reactor is presented. …”
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    Article
  2. 1762

    Water Supply Network System Control Based on Model Predictive Control by Adel Abdulrahman, Nagib Nasher

    Published 2010-07-01
    “…This paper considers the application of a controller that is approved to be robust to improve the behavior of the water network supply system, to maintain stable operation of the water flow rate, and reduce the operational cost by manipulating the pump speed. The model predictive control (MPC) algorithm is one of the most common automatic control system that has got a wide spread application in process industry. …”
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  3. 1763
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    Predictive Beamforming With Active Inference Under Continuous Time-Varying Channels by Naoki Nishio, Tatsuya Otoshi, Masayuki Murata

    Published 2025-01-01
    “…To address this issue, we propose a method that combines hierarchical codebooks with active inference to predict the optimal beam rather than search for it. …”
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  5. 1765

    Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

    Published 2025-01-01
    “…Given the diverse needs of these pilgrims and the continuous efforts to enhance their experience, we propose an advanced social media classification system based on predictive deep learning. The primary objective of this system is to efficiently classify and analyze social media content related to Hajj and Umrah services. …”
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  6. 1766

    Design and Practical Evaluation of Robust Model Predictive Wind Turbine Control by Andreas Klein, Thorben Wintermeyer‐Kallen, János Zierath, Kevin Kluge, Dirk Abel, Heike Vallery, Maximilian Basler

    Published 2025-05-01
    “…Due to ever more and ever larger wind turbines (WT), the requirements for WT operation become more complex. Model predictive control (MPC) for WTs shows the potential to handle these requirements and conflicting control objectives in a single optimization‐based controller. …”
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    Article
  7. 1767

    An Integrated Framework for Cryptocurrency Price Forecasting and Anomaly Detection Using Machine Learning by Hani Alnami, Muhammad Mohzary, Basem Assiri, Hussein Zangoti

    Published 2025-02-01
    “…The accurate prediction of cryptocurrency prices is crucial due to the volatility and complexity of digital asset markets, which pose significant challenges to traders, investors, and researchers. …”
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  8. 1768

    Development and external validation of a nomogram prediction model based on quantitative coronary angiography for predicting ischemic lesions: a multi-centre study by Shuai Yang, Shuai Yang, Shuang Leng, Shuang Leng, Zhouchi Wang, Jiang Ming Fam, Jiang Ming Fam, Adrian Fatt Hoe Low, Adrian Fatt Hoe Low, Ru-San Tan, Ru-San Tan, Ping Chai, Ping Chai, Lynette Teo, Lynette Teo, Chee Yang Chin, Chee Yang Chin, John C. Allen, Mark Yan-Yee Chan, Mark Yan-Yee Chan, Khung Keong Yeo, Khung Keong Yeo, Aaron Sung Lung Wong, Aaron Sung Lung Wong, Soo Teik Lim, Soo Teik Lim, Qinghua Wu, Liang Zhong, Liang Zhong, Liang Zhong

    Published 2025-06-01
    “…For per-patient analysis, the corresponding values were 85.8%, 85.7%, 86.0% in the development cohort and 82.2%, 83.3%, 81.1% in the validation cohort.ConclusionThe nomogram may be useful for predicting ischemic lesions using QCA measurements and the LASSO regression algorithm, with external validation indicating potential predictive value in cardiology care settings.…”
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  9. 1769
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    A Novel Grey Prediction Model: A Hybrid Approach Based on Extension of the Fractional Order Discrete Grey Power Model with the Polynomial-Driven and PSO-GWO Algorithm by Baohua Yang, Xiangyu Zeng, Jinshuai Zhao

    Published 2025-02-01
    “…Background: This study addresses the challenge of predicting data sequences characterized by a mix of partial linearity and partial nonlinearity. …”
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  11. 1771

    Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer by Kaimin Hu, Yinan Wu, Yajing Huang, Meiqi Zhou, Yanyan Wang, Xingru Huang

    Published 2025-01-01
    “…Our classifier achieved a predicting accuracy of 81.25%, and 88.7% slides labeled as endocrine resistant were predicted as the mesenchymal-phenotype, while 75.6% slides labeled as sensitive were predicted as the epithelial-phenotype. …”
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    Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

    Published 2025-02-01
    “…Optimization using GTO resulted in a 6.71% improvement in kerf deviation prediction accuracy compared to experimental values, while ZOA achieved a 2.37% improvement. …”
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  15. 1775

    Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated with genetic algorithm by J.M. Zikri, M.S.M. Sani, M.F.F.A. Rashid, J. Muriban, G.S. Prayogo

    Published 2025-03-01
    “…This research examines the predictive performance of two modeling techniques—Response Surface Methodology (RSM) and an Artificial Neural Network enhanced by a Genetic Algorithm (ANN-GA)—in relation to noise emission levels from a single-cylinder diesel engine running on palm oil methyl ester (POME). …”
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  16. 1776

    Interpretable Reinforcement Learning for Sequential Strategy Prediction in Language-Based Games by Jun Zhao, Jintian Ji, Robail Yasrab, Shuxin Wang, Liang Yu, Lingzhen Zhao

    Published 2025-07-01
    “…However, existing models often struggle with poor adaptability and limited interpretability when applied to dynamic language prediction tasks such as <b>Wordle</b>. To address these challenges, this study proposes an interpretable reinforcement learning framework based on an Enhanced Deep Deterministic Policy Gradient (Enhanced-DDPG) algorithm. …”
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