METHODS OF APPROXIMATION OF FUNCTIONS BY GENERALIZED POLYNOMIALS IN NUMERICAL ANALYSIS PROBLEMS RELATED TO CALCULATIONS ON APPROXIMATE DATA by Igor Eduardovich Naats, Victoria Igorevna Naats, Elena Pavlovna Yartseva

“…Introduction: the methods of representation of functions given approximately by their singular integrals in relation to approximation problems and numerical methods for solving boundary value problems for differential equations are Investigated. …”
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Machine learning models for the prediction of preclinical coal workers’ pneumoconiosis: integrating CT radiomics and occupational health surveillance records by Yankun Ma, Fengtao Cui, Yulong Yao, Fuhai Shen, Hongyi Qin, Bing Li, Yan Wang

“…Second, two feature selection algorithms were applied to select critical features from both CT radiomics and occupational health data. …”
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DBSANet: A Dual-Branch Semantic Aggregation Network Integrating CNNs and Transformers for Landslide Detection in Remote Sensing Images by Yankui Li, Wu Zhu, Jing Wu, Ruixuan Zhang, Xueyong Xu, Ye Zhou

“…Deep learning-based semantic segmentation algorithms have proven effective in landslide detection. …”
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Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma by Meiling Qin, Xinxin Li, Xun Gong, Yuan Hu, Min Tang

“…Prognostic and diagnostic values were assessed using survival analysis and ROC curves. …”
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The Load Cycle Amplitude Model: An Efficient Time-Domain Extrapolation Technique for Non-Stationary Loads in Agricultural Machinery by Zihan Yang, Xuke Liu, Zhenghe Song, Hanting Liu

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Presenting a multi-objective mathematical model with an integrated approach to scheduling and financial flow in production projects using NSGA-II by Sajad Janbaz, Seyed Mohammadreza Davoodi, Abdolmajid Abdolbaghi Ataabadi

“…The statistical population is in the form of a case study, and the required information and data were collected through interviews with managers of Kisson Construction Company.Findings: NSGA-II was used as an optimization algorithm to find efficient multi-objective solutions, and optimal results were presented to select civil and construction projects.Originality/Value: This research contributes to the field by proposing a novel multi-objective mathematical model that integrates scheduling and financial flow considerations in production projects. …”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…To address the above problems, we proposed a typing evaluation method for KASP primers by integrating deep learning and traditional machine learning algorithms, called TAL-SRX. …”
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Incremental predictive value of liver fat fraction based on spectral detector CT for major adverse cardiovascular events in T2DM patients with suspected coronary artery disease by Min Wang, Tanglin Wei, Li Sun, Yanhua Zhen, Ruobing Bai, Xiaomei Lu, Yue Ma, Yang Hou

“…Abstract Background The purpose of this study was to explore the incremental predictive value of liver fat fraction (LFF) in forecasting major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM). …”
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An Efficient K-Best MIMO Detector for Large Modulation Constellations by Yu-Xin Liu, Shih-Jie Jihang, Yeong-Luh Ueng

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Integrated single-cell and transcriptome sequencing to construct a prognostic model of M2 macrophage-related genes in prostate cancer by TANG Kairan, FENG Chengling, HAN Bangmin

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Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

“…In this paper, a hybrid-driven modeling method integrating Bidirectional Long Short-Term Memory network (BiLSTM) and Adaptive Boosting (AdaBoost) algorithm is proposed, aiming to improve the accuracy and stability of crystal diameter prediction in the medium diameter stage of the SSC growth by the Czochralski (CZ) method. …”
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LULC change detection and future LULC modelling using RF and MLPNN-Markov algorithms in the uMngeni catchment, KwaZulu-Natal, South Africa by Orlando Bhungeni, Michael Gebreslasie, Ashadevi Ramjatan

“…Thus, the adoption of remote sensing data and Machine Learning Algorithms (MLAs) is a novel approach that provides spatiotemporal data on the environmental changes resulting from LULC dynamics. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…The experimental results show that the GYS-RT-DETR model has a precision of 79.1%, a recall of 77.9%, an F1 score of 78.0%, a model size of 23.0 MB, and an mAP value of 77.8%. Compared to the original model, the precision, recall, the F1 score, the mAP value, and the FPS value have improved by 3.5%, 5.3%, 5.0%, 5.3%, and 10.3 f/s, respectively. …”
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A Predictive Model for the Shear Capacity of Ultra-High-Performance Concrete Deep Beams Reinforced with Fibers Using a Hybrid ANN-ANFIS Algorithm by Hossein Mirzaaghabeik, Nuha S. Mashaan, Sanjay Kumar Shukla

“…Subsequently, a novel hybrid algorithm, integrating an ANN and ANFIS, was developed to enhance prediction accuracy by utilizing numerical data as input for training. …”
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Machine-Learning-Based Optimal Feed Rate Determination in Machining: Integrating GA-Calibrated Cutting Force Modeling and Vibration Analysis by Yu-Peng Yeh, Han-Hao Tsai, Jen-Yuan Chang

“…This study proposes a machine learning-based approach to optimize feed rate in machining operations by integrating a genetic algorithm (GA)-calibrated cutting force model with vibration analysis. …”
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Construction of a digital twin model for incremental aggregation of multi type load information in hybrid microgrids under integrity constraints by Yibo Lai, Libo Fan, Weiyan Zheng, Rongjie Han, Kai Liu

“…Establish integrity constraints for multiple load data of hybrid microgrids and extract load characteristics of hybrid microgrids. …”
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Augmented robustness in home demand prediction: Integrating statistical loss function with enhanced cross-validation in machine learning hyperparameter optimisation by Banafshe Parizad, Ali Jamali, Hamid Khayyam

“…Using three evolutionary algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) we optimize two ensemble models: XGBoost and LightGBM. …”
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Optimization and characterization of wood decay mushroom Ganoderma adspersum extract: A comparison between response surface methodology and artificial neural network-ant lion algor... by Ayşenur Gürgen

“…The extraction conditions were designed according to the I-optimal design and optimized using both the response surface method and the integration of artificial neural networks–ant lion algorithm. …”
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The Influence of Non-Landslide Sample Selection Methods on Landslide Susceptibility Prediction by Yu Fu, Zhihao Fan, Xiangzhi Li, Pengyu Wang, Xiaoyue Sun, Yu Ren, Wengeng Cao

“…This study compares three sample selection strategies: whole-region random selection, landslide buffer zone selection, and the enhanced information value (EIV) method. By integrating these methods with the random forest (RF) algorithm, three models—random-RF, buffer zone-RF, and EIV-RF—were developed and evaluated. …”
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Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula by Chen Pan, Jiaming Guo, Haibo Li, Jiawei Wu, Nengjie Qiu, Shengzhen Wu

“…The methodological integration of RAGA-PPM and SHAP advances the innovative paradigm of applying interpretable machine learning to the study of urban form.…”
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