A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping by Wang Yan, Le Jiajin, Zhang Yun

“…In order to improve the schema mapping efficiency and get more accurate learning results, this paper proposes a heterogeneous data schema mapping method basing on multianalyzer machine learning model. The multianalyzer analysis the learning results comprehensively, and a fuzzy comprehensive evaluation system is introduced for output results’ evaluation and multi factor quantitative judging. …”
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Machine learning algorithms can predict emotional valence across ungulate vocalizations by Romain A. Lefèvre, Ciara C.R. Sypherd, Élodie F. Briefer

“…The present study used a machine learning algorithm (eXtreme Gradient Boosting [XGBoost]) to distinguish between contact calls indicating positive (pleasant) and negative (unpleasant) emotional valence, produced in various contexts by seven species of ungulates. …”
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Improving the segmentation of the vertebrae using a multi-stage machine learning algorithm by Vladyslav Koniukhov

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Retracted: Digital Art Feature Association Mining Based on the Machine Learning Algorithm by null Complexity

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Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides by Heqian Zhang, Yihan Wang, Yanran Zhu, Pengtao Huang, Qiandi Gao, Xiaojie Li, Zhaoying Chen, Yu Liu, Jiakun Jiang, Yuan Gao, Jiaquan Huang, Zhiwei Qin

Subjects: “…Machine learning…”
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Innovative machine learning approaches for indoor air temperature forecasting in smart infrastructure by Nataliya Shakhovska, Lesia Mochurad, Rosana Caro, Sotirios Argyroudis

“…This paper presents an innovative approach to surrogate modeling for predicting indoor air temperature (IAT) in buildings, leveraging advanced machine learning techniques. At the core of this study is the application of Long Short-Term Memory (LSTM) networks for time-series modeling, which significantly enhances the capture of temporal dependencies in temperature predictions. …”
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A hybrid machine learning approach for the personalized prognostication of aggressive skin cancers by Tom W. Andrew, Mogdad Alrawi, Ruth Plummer, Nick Reynolds, Vern Sondak, Isaac Brownell, Penny E. Lovat, Aidan Rose, Sophia Z. Shalhout

“…MCC and DeepMerkel provide the exemplar model of personalised machine learning prognostic tools in aggressive skin cancers.…”
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Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm by Van Quan Tran

“…The aim of this paper was to select a highest performance and reliable machine learning (ML) model to predict the permeability coefficient of soil and quantify the feature importance on the predicted value of the soil permeability coefficient with aided machine learning-based SHapley Additive exPlanations (SHAP) and Partial Dependence Plot 1D (PDP 1D). …”
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Nonpenalty Machine Learning Constraint Handling Using PSO-SVM for Structural Optimization by Marco M. Rosso, Raffaele Cucuzza, Fabio Di Trapani, Giuseppe C. Marano

“…In this paper, a new nonpenalty-based constraint handling approach for PSO is implemented, adopting a supervised classification machine learning method, the support vector machine (SVM). …”
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Feature Selection and Machine Learning Approaches for Detecting Sarcopenia Through Predictive Modeling by Akhrorbek Tukhtaev, Dilmurod Turimov, Jiyoun Kim, Wooseong Kim

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Predictive Analytics in Construction: Multi-Output Machine Learning Models for Abrasion Resistance by Shaheen Mohammed Saleh Ahmed, Hakan Güneyli, Süleyman Karahan

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Prediction and Analysis of Slope Stability Based on IPSO-SVM Machine Learning Model by Yu Wang, Erxia Du, Sanqiang Yang, Li Yu

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Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms by Lamiae Azouggagh, Noelia Ibáñez-Escriche, Marina Martínez-Álvaro, Luis Varona, Joaquim Casellas, Sara Negro, Cristina Casto-Rebollo

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AI-Driven precision in solar forecasting: Breakthroughs in machine learning and deep learning by Ayesha Nadeem, Muhammad Farhan Hanif, Muhammad Sabir Naveed, Muhammad Tahir Hassan, Mustabshirha Gul, Naveed Husnain, Jianchun Mi

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Machine learning framework for sustainable traffic management and safety in AlKharj city by Ali Louati

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Semi-Supervised Machine Learning for Fault Detection and Diagnosis of a Rooftop Unit by Mohammed G. Albayati, Jalal Faraj, Amy Thompson, Prathamesh Patil, Ravi Gorthala, Sanguthevar Rajasekaran

Subjects: “…semi-supervised machine learning…”
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Machine learning and AI for advancing Parkinson's disease diagnosis: exploring promising applications by Shohreh Abdollahi, Ramin Safa

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Unsupervised machine learning clustering approach for hospitalized COVID-19 pneumonia patients by Nuttinan Nalinthasnai, Ratchainant Thammasudjarit, Tanapat Tassaneyasin, Dararat Eksombatchai, Somnuek Sungkanuparph, Viboon Boonsarngsuk, Yuda Sutherasan, Detajin Junhasavasdikul, Pongdhep Theerawit, Tananchai Petnak

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An investigation of machine learning methods applied to genomic prediction in yellow-feathered broilers by Bogong Liu, Huichao Liu, Junhao Tu, Jian Xiao, Jie Yang, Xi He, Haihan Zhang

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Prediction and Analysis of Saltwater Intrusion in Pearl River Estuary Based on Machine Learning by DU Boheng, ZHANG Jingwen, KANG Zheng, CHEN Yifan, HUANG Hanliang, LIN Kairong, XIAO Mingzhong

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