A thermodynamic inspired AI based search algorithm for solving ordinary differential equations by V. Murugesh, M. Priyadharshini, T. R. Mahesh, Esmael Adem Esleman

“…In this paper, we introduce a new search algorithm called Thermodynamic Inspired Search Algorithm (TSA) for approximate solution to linear ODEs (LODEs), nonlinear ODEs (NLODEs) and systems of ODEs (SODEs). …”
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Traffic flow prediction based on improved deep extreme learning machine by Xiujuan Tian, Shuaihu Wu, Xue Xing, Huanying Liu, Heyao Gao, Chun Chen

“…Abstract A new hybrid prediction model is proposed for short-term traffic flow, which is based on Deep Extreme Learning Machine improved by Sparrow Search Algorithm (SSA-DELM). …”
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Algorithm for differential administration of combination antihypertensive therapy in patients with Type 2 diabetes mellitus by O. A. Koshelskaya, O. A. Zhuravleva, R. S. Karpov

“…These findings were used for the development of the algorithm for differential administration of combination AHT in patients with AH and DM-2. …”
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Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer by Ruowu Wu, Yandan Liang, Lianlei Lin, Zongwei Zhang

“…Finally, we demonstrated the excellent effect of STWPM in multivariate spatiotemporal field weather prediction by comprehensively evaluating the proposed algorithm with classical algorithms on the ERA5 dataset in a global region.…”
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Prediction of risk for acute kidney injury and its progression to mortality in obese patients admitted to ICU postoperatively by LI Qiang, LI Qiang, MU Guo, MU Guo, WANG Wenzhang

“…After data cleaning and preprocessing, Boruta feature selection was applied, followed by the construction of prediction models using 7 machine learning algorithms, that is, Gradient Boosting Machine (GBM), Generalized Linear Model (GLM), k-Nearest Neighbors (KNN), Naïve Bayes (NB), Neural Network (NNET), Support Vector Machine (SVM), and XGBoost. …”
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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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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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Fall prediction based on biomechanics equilibrium using Kinect by Xu Tao, Zhou Yun

“…We evaluate the model and algorithm on an open database. The performance indicates that the fall prediction algorithm by studying human biomechanics can predict a fall (91.7%) and provide a certain amount of time (333 ms) before the elder injuring (hitting the floor). …”
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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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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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