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  1. 781

    Early Yield Prediction of Oilseed Rape Using UAV-Based Hyperspectral Imaging Combined with Machine Learning Algorithms by Hongyan Zhu, Chengzhi Lin, Zhihao Dong, Jun-Li Xu, Yong He

    Published 2025-05-01
    “…The main results were as follows: (i) The yield prediction of oilseed rape using EWs showed better prediction and robustness compared to the full-spectral model. …”
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  2. 782
  3. 783
  4. 784

    Machine learning algorithms for maize yield prediction with multispectral imagery: Assessing robustness across varied growing environments by Bala Ram Sapkota, Gurjinder S. Baath, K. Colton Flynn, Kabindra Adhikari, Chad Hajda, Douglas R. Smith

    Published 2025-12-01
    “…The research utilizes multispectral imagery and maize yield data from diverse growing environments, comprising seven maize planting dates tested across three field locations over two years. Among five ML algorithms tested, the Extra Trees Regressor (ETR) showed superior performance at predicting maize yield across most maize growth phases. …”
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  5. 785
  6. 786

    Prediction of Electric Vehicle Mileage According to Optimal Energy Consumption Criterion by Oleksii Chkalov, Roman Dropa

    Published 2024-06-01
    “…Within this context, a novel model-based predictive approach is introduced for estimating electric vehicle energy consumption. …”
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  7. 787

    Sensor-validated simulations predict fracture healing outcomes in an ovine model by Alicia Feist, Carla Hetreau, Manuela Ernst, Peter Varga, Peter Schwarzenberg

    Published 2025-03-01
    “…The potential of the simulation to predict healing patterns and to be used as a tool for non-union risk assessment was illustrated. …”
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  8. 788

    Comparative Study on Prediction Models for Crack Opening Degree in Concrete Dam by HUANG Song, WU Jie, FANG Zhanchao, CHU Huaping, WU Yan'gang, XUE Zilong, HE Linbo

    Published 2025-03-01
    “…However, there are some deficiencies in the predictive power of the former and the theoretical explanation of the latter. …”
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    Article
  9. 789

    Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

    Published 2025-06-01
    “…This study presents a dynamic continuous error compensation model for direct-drive turntables, based on an analysis of positioning error mechanisms and the implementation of a “decomposition-modeling-integration-correction” strategy, which features high flexibility, adaptability, and online prediction-correction capabilities. Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
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  10. 790
  11. 791

    A Servo Control Algorithm Based on an Explicit Model Predictive Control and Extended State Observer with a Differential Compensator by Zhuobo Dong, Shuai Chen, Zheng Sun, Benyi Tang, Wenjun Wang

    Published 2025-06-01
    “…This paper introduces a novel two-degree-of-freedom (2-DOF) control algorithm that integrates explicit model predictive control (EMPC) with a differential-compensated extended state observer (DCESO). …”
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  12. 792

    Multi-layer perceptron-particle swarm optimization: A lightweight optimization algorithm for the model predictive control local planner by Xiaoqing Guan, Tao Hu, Ziang Zhang, Yixu Wang, Yifan Liu, You Wang, Jie Hao, Guang Li

    Published 2024-11-01
    “…This letter reports a lightweight and efficient two-stage solving algorithm for the model predictive control planner. …”
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  13. 793

    An Effective Approach to Promote Air Traveler Repurchasing Using the Random Forest Algorithm: Predictive Model Design and Utility Evaluation by Zhenyuan Zhang, Yanhong Chen, Luning Liu

    Published 2022-01-01
    “…The results show that the proposed model framework is better than the prediction results of the other algorithms. In addition, the proposed model framework was verified through a real case of an airline in China. …”
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    Article
  14. 794

    SPINEX-anomaly: similarity-based predictions with explainable neighbors exploration for anomaly and outlier detection by M. Z. Naser, Ahmad Z. Naser

    Published 2025-04-01
    “…Abstract This paper presents a novel anomaly and outlier detection algorithm from the SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) family. …”
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  15. 795
  16. 796

    Machine learning algorithms for predictive modeling of dyslipidemia-associated cardiovascular disease risk in pregnancy: a comparison of boosting, random forest, and decision tree regression by Idris Zubairu Sadiq, Fatima Sadiq Abubakar, Muhammad Auwal Saliu, Babangida Sanusi katsayal, Aliyu Salihu, Aliyu Muhammad

    Published 2025-01-01
    “…Methods In this study, we utilized three different machine learning algorithms (boosting, random forest, and decision tree regression) to predict dyslipidemia-associated cardiovascular disease using atherogenic index and lipid profile parameters based on a cross-sectional study datasets of 112 pregnant women aged between 15 and 49 conducted at Aminu Kano Teaching Hospital. …”
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  17. 797
  18. 798

    Medium- and Long-term Runoff Prediction Based on SMA-LSSVM by TIAN Jinghuan, LI Congxin, LI Ang

    Published 2022-01-01
    Subjects: “…slime mold algorithm (SMA)…”
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  19. 799

    Experimental Application of Predictive Controllers by C. H. F. Silva, H. M. Henrique, L. C. Oliveira-Lopes

    Published 2012-01-01
    “…The classical algorithms Infinite Horizon Model Predictive Control (IHMPC) and Model Predictive Control with Reference System (RSMPC) were used for the experimental application in the multivariable control of the pilot plant (level and pH). …”
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  20. 800

    Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction by Quésia Sá Pavão, Paula Godinho Ribeiro, Gutierre Pereira Maciel, Sérgio Henrique Godinho Silva, Suzana Romeiro Araújo, Antonio Rodrigues Fernandes, José Alexandre Melo Demattê, Pedro Walfir Martins e Souza Filho, Silvio Junio Ramos

    Published 2025-12-01
    “…The following objectives were set: i) to compare the efficacy of individual and combined Vis-NIR and pXRF data for the prediction of chemical attributes, using the Random Forest (RF) algorithm, and ii) to compare two methods (Boruta and Principal Component Analysis - PCA) for dimensionality reduction. …”
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