Modelling and Optimisation of Hysteresis and Sensitivity of Multicomponent Flexible Sensing Materials by Kai Chen, Qiang Gao, Yijin Ouyang, Jianyong Lei, Shuge Li, Songxiying He, Guotian He

“…Finally, the optimal solution of the prediction model is obtained using the multi-objective RIME (MORIME) algorithm. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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Motion and Inertia Estimation for Non-Cooperative Space Objects During Long-Term Occlusion Based on UKF-GP by Rabiul Hasan Kabir, Xiaoli Bai

“…In particular, we implement the multi-output GP to predict the projection measurements of a stereo-camera system onboard a chaser spacecraft. …”
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Modeling emotional abuse based on emotional maturity and self-differentiation with the mediating role of marital intimacy by mehran sharifi, qumarth karimi, omid moradi, shokooh navabinejad

“…Data analysis was analyzed using Pearson correlation method, structural equation modeling and partial least squares (SMARTPLS-3) algorithm and SPSS-23. Results: The results indicated the fit of the general research model with the experimental data. …”
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Navigating the Maze of Social Media Disinformation on Psychiatric Illness and Charting Paths to Reliable Information for Mental Health Professionals: Observational Study of TikTok... by Alexandre Hudon, Keith Perry, Anne-Sophie Plate, Alexis Doucet, Laurence Ducharme, Orielle Djona, Constanza Testart Aguirre, Gabrielle Evoy

“…A multilayered perceptron algorithm was used to identify factors predicting disinformation. …”
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Sudden Infant Death Syndrome: Definition Evolution, Epidemiology and Risk Factors by Natalya N. Korableva

“…This algorithm is proposed to be used in educational programs for pregnant women and parents of infants.…”
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Calibration Transfer of Soil Total Carbon and Total Nitrogen between Two Different Types of Soils Based on Visible-Near-Infrared Reflectance Spectroscopy by Xue-Ying Li, Yan Liu, Mei-Rong Lv, Yan Zou, Ping-Ping Fan

“…The RMSEP decreased from 2.42 to approximately 0.04 for TN and from 15.74 to approximately 0.4 for TC. The WMPDS-S/B algorithm had advantages in selecting fewer known samples and obtaining better prediction results. …”
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Applications of machine learning in decision analysis for dose management for dofetilide. by Andrew E Levy, Minakshi Biswas, Rachel Weber, Khaldoun Tarakji, Mina Chung, Peter A Noseworthy, Christopher Newton-Cheh, Michael A Rosenberg

“…A reinforcement learning algorithm informed by unsupervised learning was able to predict dosing decisions with 96.1% accuracy. …”
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The role of MRO as an M2 macrophage-associated gene in non-small cell lung cancer: insights into immune infiltration, prognostic significance, and therapeutic implications by Yue Gu, Miaosen Zheng, Jing Xie

“…Single-cell RNA sequencing data from TISCH2 evaluated MRO expression in different cell types. The ESTIMATE algorithm analyzed correlations between MRO expression and immune scores, while TIDE and Submap analyses predicted immunotherapy responses. …”
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Analysis of Comprehensive Artificial Neural Network Computer Media Aided Construction of Economic Forecasting Model by Tianfeng Li

“…Based on this, this paper first analyzes the economic system prediction, then studies the ANN medium model and learning algorithm, and finally verifies the effectiveness of the ANN economic prediction model integrating computer medium.…”
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Advanced Solar Irradiance Forecasting Using Hybrid Ensemble Deep Learning and Multisite Data Analytics for Optimal Solar-Hydro Hybrid Power Plants by Sudharshan Konduru, Naveen C., Jagabar Sathik M.

“…A novel hybrid decomposed residual ensembling model for deep learning (SBLTSRARW) using models such as autoregressive integrated moving average (ARIMA) and seasonal-trend decomposition using loess (STL) along with prediction and optimization models such as Bidirectional LSTM (Bi-LSTM), and Whale Optimization Algorithm (WOA) methods are used to predict the irradiances. …”
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A Three-Dimensional Ply Failure Model for Composite Structures by Maurício V. Donadon, Sérgio Frascino M. de Almeida, Mariano A. Arbelo, Alfredo R. de Faria

“…A fully 3D failure model to predict damage in composite structures subjected to multiaxial loading is presented in this paper. …”
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Using N-Version Architectures for Railway Segmentation with Deep Neural Networks by Philipp Jaß, Carsten Thomas

“…Our results show that the N-version architecture not only enables a detection of erroneous predictions by utilizing those adjusted confidence values, but it can also partially improve the predictions by using the PMV combination algorithm. …”
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Development of the Model of Diagnostics of Design-Technological Thinking in Secondary School Students in the Subject of Labor (Technology) in the Module “Robotics and Automated Sys... by Yakov M. Mashukov

“…The proposed model can be used to improve the educational process in practice-oriented subject areas.…”
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Research on Air Quality Monitoring System and Evaluation Method in Closed Environment by LI Bo-chen, DING Xi-bo, CAI Qing-yao

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Multi-stage Optimization Forecast of Short-term Power Load Based on VMD and PSO-SVR by Wenwu LI, Qiang SHI, Dan LI, Qunyong HU, Yun TANG, Jinchao MEI

“…In the second stage, phase space reconstruction is used to optimize and reorganize each sequence component, and establish support vector regression（SVR）prediction model for each component. In the third stage, the particle swarm optimization（PSO）algorithm is applied to optimize the internal parameters of the SVR model to facilitate better training and forecasting. …”
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A Deep Learning Model for ERP Enterprise Financial Management System by Hui Zhang

“…The experimental results show that the deep learning risk prediction model has significant superiority in prediction accuracy and stability. …”
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Improved cluster analysis of Werner solutions for geologic depth estimation using unsupervised machine learning by Daniel Eshimiakhe, Raimi Jimoh, Magaji Suleiman, Kola Lawal

“…The unsupervised clustering algorithm was then used to improve the detection of geological structures generated from magnetic field data. …”
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Flexible Scheduling Model of Bus Services between Venues of the Beijing Winter Olympic Games by Jiahao Zhang, Ailing Huang, Rui Jiang, Xingang Li

“…In addition, a genetic-simulated annealing hybrid algorithm (GSAHA) is designed to solve the model based on the characteristics of the genetic algorithm (GA) and simulated annealing. …”
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A Few-shot Learning Method for Intent Analysis of Air Combat Confrontation Behaviors by PAN Ming, ZHENG Jingsong, LI Jinliang, FANG Long, YANG Yang, ZHAO Shijie

“…The experimental simulation results show that the accuracy of the few-shot contrastive learning algorithm based on data augmentation in predicting the behavior intention of few-shot air combat targets is 91. 13% .…”
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