Exploration of Predictive Models for Lean Services in Government Lean Banking Industry by Fazel Saydi, Morteza Musa Khani, Sedigheh Tootian, Shahrazad Tayaran

“…The present study aims to identify and validate a predictive model of lean services in the context of lean government in the banking industry. …”
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Role of artificial intelligence in enhancing mechanical ventilation – A peek into the future by Neeraj Pal Singh, Masood Ali Mujawar, Akash Golani

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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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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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Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms by Tuxiang Lin, Rongliang Lin

“…This study presents a novel framework that integrates the Spatiotemporal Graph Convolutional Network-Long Short-Term Memory (STGCN-LSTM) model for traffic flow prediction with the Proximal Policy Optimization (PPO) algorithm for dynamic traffic signal control. …”
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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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Domain Adaptation for Pedestrian Detection Based on Prediction Consistency by Yu Li-ping, Tang Huan-ling, An Zhi-yong

“…Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. …”
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Prediction and evaluation of residual life of casing with corrosion defects by JIA Aoyin, QIAN Liqin, WANG Jie, YANG Jingwei, WU Yaokun, WEI Mingji

“…The particle swarm optimization-gaussian process regression （PSO-GPR) algorithm was employed to construct a predictive model for casing corrosion rates.ResultsIntegration of the two models, the evaluation of the residual life of casings with corrosion defects was completed, it has theoretical guidance significance for the prevention and management of corroded casings in oil field operations.…”
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Residual Lifetime Prediction with Multistage Stochastic Degradation for Equipment by Zhan Gao, Qi-guo Hu, Xiang-yang Xu

“…Residual useful lifetime (RUL) prediction plays a key role of failure prediction and health management (PHM) in equipment. …”
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