Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

“…A Bland-Altman plot of the differences between the predicted values and the assessment values showed 95% of them within 0.21 WTE per patient. …”
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Predictive Control for an Ankle Rehabilitation Robot Using Differential Evolution Optimization Algorithm-Based Fuzzy NARX Model by Shenglong Xie, Haiming Zhong, Yuntang Li, Su'an Xu, Wenyuan Liu, Shiyuan Bian, Shiwu Zhang

“…In this paper, based on differential evolution (DE) optimization algorithm and fuzzy nonlinear auto regressive with exogenous inputs (NARX) model, an iterative learning model predictive controller is constructed to achieve accurate and robust trajectory tracking control of an ankle rehabilitation robot driven by pneumatic muscle. …”
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FOX-TSA hybrid algorithm: Advancing for superior predictive accuracy in tourism-driven multi-layer perceptron models by Sirwan A. Aula, Tarik A. Rashid

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Enhanced Robust Control of Induction Motor Using Combined Optimal Model Predictive Control With Super-Twisting Algorithm by REZGUI, S.-E., NEMOUCHI, B.

“…This paper presents a novel strategy for induction motor control that combines Optimal Model Predictive Control (OMPC) with the Super-Twisting Algorithm (STA) to enhance the performance of field-oriented control (IFOC) strategy under disturbances and uncertainties. …”
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Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm by Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun

“…To overcome these limitations, this paper proposes a novel energy scheduling framework that integrates the Model Predictive Control (MPC) with a Deep Reinforcement Learning algorithm, specifically the Deep Deterministic Policy Gradient (DDPG). …”
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Clean-Room Air Conditioning Control Based on Improved Min-Max Robust Model Predictive Control Algorithm by Qiang Luo, Ting Wang

“…Subsequently, an improved Min Max robust model predictive control algorithm was proposed to control the parameters of the model, and compared and analyzed with the original algorithm. …”
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Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms by Yuyang Chen, Jiansheng Zhong, Haixiang Li, Kunzhe Lin, Liangfeng Wei, Shousen Wang

“…Abstract This study aimed to predict arginine vasopressin deficiency (AVP-D) following transsphenoidal pituitary adenoma surgery using machine learning algorithms. …”
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Prediction of the Reaming Torque Using Artificial Neural Network and Random Forest Algorithm: Comparative Performance Analysis by M. C. Rakshith, Raghavendra C. Kamath, G. S. Vijay

“…The present study compares the use of ANN and Random Forest to analyze the data from reaming operations to predict the torque and compares it with those of the Random Forest method and the polynomial regression model. …”
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Real Power Loss Reduction by Enhanced RBS Algorithm by Kanagasabai L.

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Branch-and-Reduction Algorithm for Indefinite Quadratic Programming Problem by Yongjian Qiu, Yuming Zhu, Jingben Yin

“…This paper presents a rectangular branch-and-reduction algorithm for globally solving indefinite quadratic programming problem (IQPP), which has a wide application in engineering design and optimization. …”
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Data Reduction Method for Synthetic Transmit Aperture Algorithm by Piotr KARWAT, Ziemowit KLIMONDA, Michał SĘKLEWSKI, Marcin LEWANDOWSKI, Andrzej NOWICKI

“…Ultrasonic methods of human body internal structures imaging are being continuously enhanced. New algorithms are created to improve certain output parameters. …”
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Variance Reduction Optimization Algorithm Based on Random Sampling by GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang

“…To address the above challenge, a variance reduction optimization algorithm, DM-SRG (double mini-batch stochastic recursive gradient), based on mini-batch random sampling is proposed and applied to solving convex and non-convex optimization problems. …”
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Improved SLM algorithm for PAPR reduction in OFDM system by Ce JI, Wenjing ZHU, Ying WEI, Dianxia JIA

“…In order to reduce the peak to average power ratio (PAPR) of the conventional selective mapping (SLM) algorithm,decrease the transmission of side-band information,and improve the spectral efficiency in the orthogonal frequency division multiplexing (OFDM) system,the TL-SLM algorithm based on the conversion matrix and the chaotic sequence was proposed firstly.Although the TL-SLM algorithm could effectively decrease the transmission of side-band information,the reduction of PA P R was limited.To solve this problem,an improved TL-SLM algorithm based on the rotation vector was proposed,which was the TR-SLM algorithm.TR-SLM algorithm introduced the rotation vector to generate more time-domain alternative signals to further reducing the PA P R.The performance analysis shows that although the TL-SLM algorithm and the TR-SLM algorithm increase the complexity a little,the PA P R performance is effectively improved and the transmission of side-band information is greatly reduced.…”
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Predicting Insomnia Response to Acupuncture With the Development of Innovative Machine Learning by Qingyun Wan, Kai Liu, Yuyang Bo, Xiya Yuan, Mufeng Li, Xiaoqiu Wang, Chuang Chen, Lanying Liu, Wenzhong Wu

“…To address this, an innovative machine learning algorithm, Relief-NDPGWO-WSVM, is developed to predict insomnia response to acupuncture. …”
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Prediction of the Immune Phenotypes of Bladder Cancer Patients for Precision Oncology by Hyuna Cho, Feng Tong, Sungyong You, Sungyoung Jung, Won Hwa Kim, Jayoung Kim

“…Bladder cancer (BC) is the most common urinary malignancy; however accurate diagnosis and prediction of recurrence after therapies remain elusive. …”
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A new adaptive grey prediction model and its application by Jianming Jiang, Ming Zhang, Zhongyong Huang

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Transmission Error Prediction of RV Reducer based on SSA-BP by Houzhen Sun, Hongbing Yuan, Bin Yu

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Potential Biomarkers for Predicting the Risk of Developing Into Long COVID After COVID‐19 Infection by Zhiyong Hou, Yu Ming, Jun Liu, Zhong Wang

“…Among the 67 candidate genes were processed with machine learning algorithms and logistic regression, a subgroup consisting of CEP55, CDCA2, MELK, and DEPDC1B, was at last identified as potential biomarkers for predicting the risk of the progression into long COVID after COVID‐19 infections. …”
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PREDICTION OF THE POOR RATE K-MEANS AND GENERALIZED REGRESSION NEURAL NETWORK ALGORITHMS (CASE STUDY: NORTH SUMATRA PROVINCE) by Nita Suryani, Arnita Arnita, Rinjani Cyra Nabila, Amanda Fitria

“…In this study, poverty levels were mapped using the K-Means algorithm, and GRNN was then utilized for modeling and prediction. …”
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Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series by Vasilii A. Gromov, Philip S. Baranov

“…The resulting strategy demonstrates accurate results for both benchmark and real-world time series, with the number of predicted steps exceeding that of any other published algorithm.…”
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