Machine learning algorithms as early diagnostic tools for prolonged operative time in patients with fluorescent laparoscopic cholecystectomy: a retrospective cohort study by Chu Wang, Chu Wang, JunYe Wen, ZiYi Su, HanXiang Yu

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Parallelizing process model integration for model predictive control through oracle design and analysis for a Grover’s algorithm-inspired optimization strategy by Kip Nieman, Helen Durand, Saahil Patel, Daniel Koch, Paul M. Alsing

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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

Subjects: “…|coalbed methane|random forest algorithm|multi-task learning|particle swarm optimization algorithm|production prediction|fracturing parameter optimization…”
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Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…Additionally, we developed a Multi-Objective Genetic Algorithm (MOGA)-enhanced RNN model to optimize hyperparameters and achieve accurate traffic speed predictions. …”
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iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction by Bicheng Ye, Jun Fan, Lei Xue, Yu Zhuang, Peng Luo, Aimin Jiang, Jiaheng Xie, Qifan Li, Xiaoqing Liang, Jiaxiong Tan, Songyun Zhao, Wenhang Zhou, Chuanli Ren, Haoran Lin, Pengpeng Zhang

“…Abstract To address the substantial variability in immune checkpoint blockade (ICB) therapy effectiveness, we developed an innovative R package called integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis (iMLGAM), which establishes a comprehensive scoring system for predicting treatment outcomes through advanced multi‐omics data integration. …”
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A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021) by Min Seok Kim, Young Wook Choi, Borghare Shubham Prakash, Youngju Lee, Soo Lim, Se Joon Woo

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Trustworthy Load Prediction for Cantilever Roadheader Robot Without Imputation by Pengjiang Wang, Yuxin Li, Yunwang Li, Yang Shen, Weixiong Zheng, Shigen Fu

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Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model by Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG

Subjects: “…esdd prediction…”
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Identifying the Latitude and Longitude of ATMs in ATM Networks by Niloofar Haghjoo, Mohammad rahmati, Ali Zare Mirakabad

Subjects: “…atm location prediction algorithm…”
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Research on Slope Stability Prediction Based on MC-BKA-MLP Mixed Model by Yan Lu, Hongze Zhao

“…Subsequently, a novel Black Kite Algorithm (BKA) was developed to enhance the prediction model of a multilevel perceptron neural network. …”
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Predicting Coronary Heart Disease Using Data Mining and Machine Learning Solutions by VIJAI M. MOORTHY, BHUPAL N. DHARAMSOTH, VIJAYALAKSHMI MUTHUKARUPPAN, ARUL ELANGO, KALAIARASI GANESAN

“…The true positive rate for the GB algorithm’s predictions of patients was 98.3%. The study hypothesizes that the GB method predicts the Framingham dataset better than other algorithms using 4240 samples.…”
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Research on 5G base station energy saving system based on DCNN-LSTM load prediction algorithm by Jianbin WANG, Shuchun WANG, Shangjin LIAO, Shuyuan SHI

“…With the rapid construction of the 5G wireless communication network, the energy consumption pressure of operators, and even the overall communication industry, is simultaneously highlighted.Achieving sustainable development of the industry through energy conservation and consumption reduction has become a new research direction for the current 5G network development.Taking the PRB rate as the load evaluation index, LSTM model was improved by using DCNN to extract the depth feature of the cell’s indicators.A set of DCNN-LSTM deep learning model that could predict the future value of PRB rate was proposed.On the basis of the improved algorithm, the network topology of the current 5G access network was optimized.An additional network element and its working system were designed.An intelligent energy-saving system, which ensured the network experience, of 5G base stations was realized.…”
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Development of Digital Twin for FDM Printer With Preventive Cyber-Attack and Control Algorithms by Md Hazrat Ali, Asad Waqar Malik, Nursultan Jyeniskhan, Muhammad Arif Mahmood, Essam Shehab, Frank Liou

“…It also highlights a model predictive control (MPC) algorithm based on a real-time feedback system for controlling the material feed. …”
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Prediction of IPO performance from prospectus using multinomial logistic regression, a machine learning model by Mazin Fahad Alahmadi, Mustafa Tahsin Yilmaz

“…The MLR model had a higher level of accuracy when compared with other machine learning algorithms. By using the model developed here, investors can improve their ability to predict the direction of the return on their investment in an IPO, at least for the first month. …”
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Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement by Qingmeng Shen, Yuming Wu, Limin Wan, Qian Chen, Yue Li, Zichao Liao, Wenbo Wang, Feng Li, Tao Li, Jiajun Shu

“…The results show that the prediction model with the integrated decomposition algorithm reduces the RMSE and MAE by 33% and 37%, respectively, which significantly improves the prediction accuracy and generalization ability of the neural network to meet the demand of practical engineering prediction and simultaneously enhances the risk warning ability of the model.…”
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Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm by G. Ayappan, S. Anila

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Health State Prediction of Lithium-Ion Battery Based on Improved Sparrow Search Algorithm and Support Vector Regression by Deyang Yin, Xiao Zhu, Wanjie Zhang, Jianfeng Zheng

“…To enhance prediction performance, this paper introduces an SOH prediction model based on an improved sparrow algorithm and support vector regression (ISSA-SVR). …”
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Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique by Punita Panwar, Sandeep Chaurasia, Jayesh Gangrade, Ashwani Bilandi, Dayananda Pruthviraja

“…In the present investigation, four pre-trained models, specifically CNN, AlexNet, ResNet34 and ResNet-50, were utilized to predict the severity of KOA. Further, a Deep stack ensemble technique was employed to achieve optimal performance resulting to the accuracy of 99.71%.…”
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Aging Prediction of IGBT Based on Improved Support Vector Regression by Zhengxiong CHEN, Mahemuti PAZILAI, Wei SHEN

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Optimization algorithms for multivariate sampling reduction using spatial-temporal data by Tamara Cantú Maltauro, Luciana Pagliosa Carvalho Guedes, Miguel Angel Uribe-Opazo

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