Neural Network Identification-Based Model Predictive Heading Control for Wave Gliders by Peng Jin, Baolin Zhang, Yun Zhang

“…This paper deals with the neural network identification-based model predictive heading control problem in a wave glider. …”
Get full text

Research on Robust Adaptive Model Predictive Control Based on Vehicle State Uncertainty by Yinping Li, Li Liu

“…The results show that the improved algorithm achieves a 13% faster response time (5.2 s vs. 6 s control cycles), a 15% higher minimum speed during cornering (2.98 m/s vs. 2.51 m/s), a 32% narrower lateral velocity fluctuation range ([−0.11, 0.22] m/s vs. [−0.19, 0.22] m/s), and reduced yaw rate oscillations ([−1.8, 2.8] rad/s vs. [−2.8, 2.5] rad/s) compared with a traditional fixed-weight MPC algorithm. …”
Get full text

SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction by Bei Zhu, Yao Jin, Xuehua Guan, Yanni Dong

“…In the dimensionality reduction experiments, the overall accuracy of SSMM in any dimension is higher than that of other algorithms. …”
Get full text

Pumping up your predictive power for cognitive state detection with the proper GAINS by Victoria Ribeiro Rodrigues, Jeremy R. Prieto, Szilard L. Beres, Chad Stephens, Christopher Myers, Nicholas J. Napoli

Get full text

Model Predictive Control of Piecewise Affine System with Constrained Input and Time Delay by Zhilin Liu, Lutao Liu, Jun Zhang, Xin Yuan

“…A model predictive control (MPC) is proposed for the piecewise affine (PWA) systems with constrained input and time delay. …”
Get full text

Design and Application of Offset-Free Model Predictive Control Disturbance Observation Method by Xue Wang, Baocang Ding, Xin Yang, Zhaohong Ye

“…Model predictive control (MPC) with its lower request to the mathematical model, excellent control performance, and convenience online calculation has developed into a very important subdiscipline with rich theory foundation and practical application. …”
Get full text

K-Nearest Neighbors for Anomaly Detection and Predictive Maintenance in Water Pumping Systems by João Pablo Santos da Silva, André Laurindo Maitelli

“…The input parameters used for a model are the sensor parameters, and the model analyzes the correlation between the input parameters (sensors) and determines which parameters are the most important, deciding on the output of the model, and thereby building the simplest model, which requires the least input parameters and gives the most accurate prediction results. In this project, using on the input signal from the sensors, the k-nearest neighbors machine learning algorithm was used to correlate/predict whether the pump was shut down (broken) for a certain period of time.…”
Get full text

Multi-objective Predictive Control of Gas Turbine System Based on T-S Fuzzy Model by Guolian HOU, Xiaoyan DAI, Linjuan GONG, Haixin XU, Jianhua ZHANG

“…In this paper, a T-S fuzzy model-based multi-objective predictive controller is proposed to enhance both the tracking performance and economic performance together. …”
Get full text

Disturbance Rejection and Uncertainty Analysis in Wind Turbines Using Model Predictive Control by Alok Kumar, Atul Kelkar

“…We have tailored the algorithm to the practical parameters of the National Renewable Energy Laboratory’s (NREL) Controls Advanced Research Turbine (CART) model. …”
Get full text

Fractional-Order Predictive Functional Control of Industrial Processes with Partial Actuator Failures by Min-Ying Li, Kang-Di Lu, Yu-Xing Dai, Guo-Qiang Zeng

“…The comprehensive simulation results demonstrate the performance of the proposed control method by comparing with a recently developed predictive functional control, genetic algorithm, and particle swarm optimization-based versions in terms of four performance indices.…”
Get full text

Enhanced Inverse Model Predictive Control for EV Chargers: Solution for Rectifier-Side by Ali Sharida, Abdullah Berkay Bayindir, Sertac Bayhan, Haitham Abu-Rub

“…Then, an adaptive estimation strategy employing a recursive least square algorithm is proposed for online dynamic model estimation, which is then used by the IMPC for optimal switching states prediction. …”
Get full text

Beyond purchase patterns: harnessing predictive analytics to anticipate unarticulated consumer needs by Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Mansour

“…The results underscore the importance of integrating human-centered design with algorithmic precision to translate predictive insights into actionable business value.…”
Get full text

Optimizing public health management with predictive analytics: leveraging the power of random forest by Hongman Wang, Yifan Song, Yifan Song, Hua Bi

“…This study employs a Random Forest Algorithm (RFA) to address this limitation and enhance the predictive modeling of community health outcomes. …”
Get full text

Predictive density profile control with discrete pellets, applied to integrated simulations of ITER by C.A. Orrico, M. van Berkel, T.O.S.J. Bosman, L. Ceelen, W.P.M.H. Heemels, F. Koechl, D. Krishnamoorthy

“…The model predictive control (MPC) scheme we deploy combines the offset-free method to correct prediction model inaccuracies and our novel modified penalty term homotopy algorithm for real-time MPC (PTH-MPC). …”
Get full text

Sialyltransferase-related genes as predictive factors for therapeutic response and prognosis in cervical cancer by Jia Shao, Can Zhang, Yaonan Tang, Aiqin He, Xiangyan Cheng

“…“MCPcounter” R package, ESTIMATE algorithm and TIMER online tools were used to depict the tumor immune microenvironment in CC. …”
Get full text

Risk Factors and Predictive Model for Ischemic Complications in Endovascular Treatment of Intracranial Aneurysms: Insights From a Large Patient Cohort by Jianwen Jia, Zeping Jin, Mirzat Turhon, Yixin Lin, Xinjian Yang, Yang Wang, Yunpeng Liu

“…Our study aimed to identify the risk factors for ischemic complications after the interventional treatment of IAs and to make an individualized prediction of the occurrence of ischemic complications, providing important reference guidance for clinicians. …”
Get full text

Improving T2D machine learning-based prediction accuracy with SNPs and younger age by Cynthia AL Hageh, Andreas Henschel, Hao Zhou, Jorge Zubelli, Moni Nader, Stephanie Chacar, Nantia Iakovidou, Haralampos Hatzikirou, Antoine Abchee, Siobhán O’Sullivan, Pierre A. Zalloua

“…Integration of a polygenic risk score (PRS) further supported risk prediction, particularly in younger individuals, though incremental gains were modest. …”
Get full text

EFFICIENT ALGORITHM FOR NUMERICAL INTEGRATION OF MOTION EQUATIONS OF LARGE PARTICLES in Microwave Devices by A. O. Rak

“…The algorithm is presented in three forms: explicit, prediction-correction and a modified, designed to simulate the motion of large relativistic particle in an electromagnetic field. …”
Get full text

Comparison of Geostatistical Kriging Algorithms for Intertidal Surface Sediment Facies Mapping with Grain Size Data by No-Wook Park, Dong-Ho Jang

“…This paper compares the predictive performance of different geostatistical kriging algorithms for intertidal surface sediment facies mapping using grain size data. …”
Get full text

Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model by Ting Wang

“…The results showed that compared with financial time series prediction algorithms, the fusion algorithm improved the prediction accuracy by 4.8% and the computation speed by 6.5 bps. …”
Get full text