A Symbol Conditional Entropy-Based Method for Incipient Cavitation Prediction in Hydraulic Turbines by Mengge Lv, Feng Li, Yi Wang, Tianzhen Wang, Demba Diallo, Xiaohang Wang

“…The comparison results with different prediction algorithms show that the proposed SCE has excellent trend prediction performance and high precision.…”
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Unveiling users’ algorithm trust: The role of task objectivity, time pressure, and cognitive load by Ruoxin Yang, Sisheng Li, Yawei Qi, Jiali Liu, Qinghua He, Haichao Zhao

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An Improved Binary Spider Wasp Optimization Algorithm for Intrusion Detection for Industrial Internet of Things by Mousa'b Mohammad Shtayat, Mohammad Kamrul Hasan, Anil Kumar Budhati, Rossliawati Solaiman, Shayla Islam, Bishwajeet Pandey, Huda Saleh Abbas, Mamoon Mohammed Ali Saeed

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An Improved KNN-Based Slope Stability Prediction Model by Shuai Huang, Mingming Huang, Yuejun Lyu

“…In our study, the k-nearest neighbor (KNN) algorithm is improved to reduce its sample dependence and improve the robustness of the algorithm, and then the prediction model of the slope stability is proposed based on the improved k-nearest neighbor (KNN) algorithm. …”
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Fast full conformal prediction for multiple test points by Ilsang Ohn, Jisu Park

“…This paper attempts to fill this gap by developing a scalable conformal prediction algorithm for multiple test points. We find that when we use kernel ridge regression for the underlying prediction method, it is possible to reuse some computation in constructing prediction intervals across multiple test points, which enables us to avoid repeating the heavy computation of a matrix inverse for each test point. …”
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Research on ionospheric parameters prediction based on deep learning by Yuntian FENG, Xia WU, Xiong XU, Rongqing ZHANG

“…For ionospheric parameter prediction, the short-term and daily mean value prediction of ionospheric parameters was established by long short-term memory (LSTM) predictive neural network modeling.Two methods of point-by-point prediction and sequence prediction were utilized.Furthermore, in order to predict the hourly and daily changes of ionospheric parameters, the proposed scheme was optimized by multidimensional prediction and empirical mode decomposition (EMD) algorithm.Finally, the feasibility of the proposed optimization algorithm in improving the prediction accuracy of ionospheric parameters is verified.…”
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Prediction of protein interactions with function in protein (de-)phosphorylation. by Aimilia-Christina Vagiona, Sofia Notopoulou, Zbyněk Zdráhal, Mariane Gonçalves-Kulik, Spyros Petrakis, Miguel A Andrade-Navarro

“…To evaluate the efficacy of our algorithm, we predicted PTM-related PPIs of ataxin-1, a protein which is responsible for Spinocerebellar Ataxia type 1 (SCA1). …”
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Interactive trajectory prediction for autonomous driving based on Transformer by R. Xu, J. Li, S. Zhang, L. Li, H. Li, G. Ren, X. Tang

“…In this paper, we propose a novel trajectory prediction algorithm based on Transformer networks, a data-driven method that ingeniously harnesses dual-input channels. …”
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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Machine learning methods open up great opportunities in predicting the rheological parameters of polymers. Previously, studies were conducted on the construction of predictive models using artificial neural networks and the CatBoost algorithm. …”
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Predictive Variable Gain Iterative Learning Control for PMSM by Huimin Xu, Xuedong Zhang, Xiangjie Liu

“…Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.…”
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Dynamic Prediction of Financial Distress Based on Kalman Filtering by Qian Zhuang, Lianghua Chen

“…The operation of the dynamic prediction is achieved by Kalman filtering algorithm. …”
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Driving behavior recognition and prediction based on Bayesian model by Xinsheng WANG, Zhen BIAN

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Developing decision support algorithm for hypertension medications for use in a digital therapeutic system by Jeannie K. Lee, J. Skye Nicholas, Amani Albadawi, Kathleen C. Insel

“…Case scenarios were used to code the algorithm into the app.ResultsA total of 117 hypertension medications and combination products were included in the formulary of the Medication Education, Decision Support, Reminding, and Monitoring (MEDSReM©) system, a mobile digital therapeutic. …”
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Movie Box Office Prediction Based on IFOA-GRNN by Wei Lu, Xiaoqiao Zhang, Xinchen Zhan

“…This study improves the fruit fly algorithm to optimize the generalized regression neural network (IFOA-GRNN) model to predict whether a movie can become a high-grossing movie. …”
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Synchrophasor-Based Out-of-Step Prediction in Large Grids by Zainab Alnassar, S. T. Nagarajan

“…In this paper, synchrophasor-based bus voltage angle measurement has been used for early prediction of OOS condition in power systems. A new algorithm has been formulated for both generator and tie lines based on the trajectory of first and second derivatives of the bus voltage phase angle for early detection of OOS condition. …”
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Predicting the risk of malignisation of endometrial hyperplasia in reproductive age by I. M. Ordiyants, A. A. Kuular, A. A. Yamurzina, D. S. Novginov

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Machine Learning‐Assisted Prediction and Generation of Antimicrobial Peptides by Sukhvir Kaur Bhangu, Nicholas Welch, Morgan Lewis, Fanyi Li, Brint Gardner, Helmut Thissen, Wioleta Kowalczyk

“…Herein, to accelerate the discovery process of new AMPs, a predictive and generative algorithm is build, which constructs new peptide sequences, scores their antimicrobial activity using a machine learning (ML) model, identifies amino acid motifs, and assembles high‐ranking motifs into new peptide sequences. …”
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A MACHINE LEARNING DISTRACTED DRIVING PREDICTION MODEL by Samira AHANGARI, Mansoureh JEIHANI, Abdollah DEHZANGI

“…Here we investigated different optimization models to build the best BN in which a Genetic Search Algorithm obtained the best performance. As a result, we achieved a 67.8% prediction accuracy using our model to predict driver distraction. …”
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RACH Traffic Prediction in Massive Machine Type Communications by Hossein Mehri, Hani Mehrpouyan, Hao Chen

“…Furthermore, we develop a new low-complexity online prediction algorithm that updates the states of the LSTM network by leveraging frequently collected data from the mMTC network. …”
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Machine Learning Techniques and Recommender Systems for Large Educational Data by Ammar Mohammed, Murtadha Hamad

“…This study utilized the educational dataset from Coursera’s online courses. …”
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