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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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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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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Detection of multiple pesticide residues on the surface of broccoli based on hyperspectral imaging by GUI Jiangsheng, GU Min, WU Zixian, BAO Xiao’an

“…To increase efficiency of the model and reduce the redundancy of the hyperspectral image, using the principal component analysis (PCA) algorithm and successive projection algorithm (SPA) for feature extraction. …”
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EFTGAN: Elemental features and transferring corrected data augmentation for the study of high-entropy alloys by Yibo Sun, Cong Hou, Nguyen-Dung Tran, Yuhang Lu, Zimo Li, Ying Chen, Jun Ni

“…This study provides a new algorithm to improve the performance and usability of deep learning with structures as inputs, which is effective and accurate for the prediction and development of materials for small data sets.…”
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High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE. by Stefano Castellana, Caterina Fusilli, Gianluigi Mazzoccoli, Tommaso Biagini, Daniele Capocefalo, Massimo Carella, Angelo Luigi Vescovi, Tommaso Mazza

“…Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. …”
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An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis by Syed Saad Azhar Ali, Muhammad Moinuddin, Kamran Raza, Syed Hasan Adil

“…Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. …”
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Student employment forecasting model based on random forest and multi-features fusion by Zhenguo Xing, Xiao Wu, Jiangjiang Li

“…Secondly, in order to improve the accuracy of the prediction model, a feature selection model combining principal component analysis and random forest algorithm is used to select the optimal subset from the original features. …”
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Deep learning, irrigation enhancement, and agricultural economics for ensuring food security in emerging economies by Aktam U. Burkhanov, Elena G. Popkova, Diana R. Galoyan, Tatul M. Mkrtchyan, Bruno S. Sergi

“…Leveraging data from the top 10 countries with the lowest climate index values according to the Numbeo ranking, this article introduces a groundbreaking deep learning algorithm. This algorithm has the potential to revolutionize agricultural productivity and food security in the face of climate change, filling the gap in research on deep learning in agriculture. …”
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Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…Traditional short-term power load-forecasting methods have certain limitations in accuracy and stability, especially when dealing with complex weather and voltage changes. To improve the prediction accuracy, this paper proposes a short-term power load-forecasting model of a regional power grid based on multi-source parameter coupling with a long short-term memory neural network (LSTM) and adopts an improved particle swarm optimization (IPSO) algorithm to optimize the LSTM network. …”
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