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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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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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…Experiments were conducted on data for noise reduction and correlation analysis, followed by analysis of the model’s prediction performance and generalization ability. …”
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Machine learning model to predicting synergy of ultrasonication and solvation impacts on crude oil viscosity by Nasir Khan, Mehdi Razavifar, Qazi Adnan Ahmad, Muhammad Siyar, Masoud Riazi, Waqar Khan, Jafar Qajar

“…In this study, we develop a machine learning-based algorithm to rigorously predict the synergistic effects of ultrasonication and solvation on crude oil viscosity. …”
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Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

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Analytical Device and Prediction Method for Urine Component Concentrations by Zhe Wang, Jianbang Huang, Qimeng Chen, Yuanhua Yu, Xuan Yu, Yue Zhao, Yan Wang, Chunxiang Shi, Zizhao Zhao, Dachun Tang

“…To tackle the low-accuracy problem with analyzing urine component concentrations in real time, a fully automated dipstick analysis device of urine dry chemistry was designed, and a prediction method combining an image acquisition system with a whale optimization algorithm (WOA) for BP neural network optimization was proposed. …”
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Nematophagous Fungi Occurrence: Prediction Using Bioclimatic Variables by Ana Martha Cruz-Avalos, Montserrat Chagoya-Sánchez, César Andres Ángel-Sahagún, Ana Isabel Mireles-Arriaga, Griselda Maki-Díaz, René Loredo-Portales, Jesús Hernández-Ruíz

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Biometric monitoring system based on K-means ＆MTLS-SVM algorithm by Jingming XIA, Lingling TANG, Ling TAN, Han ZHENG

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Biometric monitoring system based on K-means ＆MTLS-SVM algorithm by Jingming XIA, Lingling TANG, Ling TAN, Han ZHENG

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AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

Subjects: “…predictive maintenance…”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. …”
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Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges by Ebenezer Afrifa‐Yamoah, Eric Adua, Emmanuel Peprah‐Yamoah, Enoch O. Anto, Victor Opoku‐Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

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Feature Selection Using a Genetic Algorithms and Fuzzy logic in Anti-Human Immunodeficiency Virus Prediction for Drug Discovery by Houda Labjar, Mohammad Al-Sarem, Mohamed Kissi

“…This paper presents an approach that uses both genetic algorithm (GA) and fuzzy inference system (FIS), for feature selection for descriptor in a quantitative structure activity relationships (QSAR) classification and prediction problem. …”
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Prediction of CO2 emission for the central European countries through five metaheuristic optimization techniques helping multilayer perceptron by Hossein Moayedi, Azfarizal Mukhtar, Serhan Alshammari, Mohamed Boujelbene, Isam Elbadawi, Quynh T Thi, Mojtaba Mirzaei

“…To develop a reliable predictive network considering the problem complexity, multilayer perceptron (MLP) is combined with several nature-inspired optimization algorithms, namely, black hole algorithm (BHA), future search algorithm (FSA), backtracking search algorithm (BSA), biogeography-based optimization (BBO), and shuffled complex evolution (SCE). …”
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Algorithm for selecting predictors and prognosis of atrial fibrillation in patients with coronary artery disease after coronary artery bypass grafting by B. I. Geltser, K. I. Shakhgeldyan, V. Yu. Rublev, B. O. Shcheglov, E. A. Kokarev

“…These values in best model based on multivariate LR were lower (0,75; 0,7; 0,68 and 0,7, respectively).Conclusion. The developed algorithm for selecting predictors made it possible to verify significant predictive ranges and weight coefficients characterizing their influence on PAF development. …”
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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…Specifically, the VToMe algorithm achieves stable detection of medium to long term system faults, while the BiGRU network achieves rapid fault prediction in the short term. …”
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Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network by Yansheng Huang, Atthapol Ngaopitakkul, Suntiti Yoomak

“…., the model optimization process stays in the non-optimal regional minimum) in complex parameter space, the study innovatively proposes a hybrid prediction model that combines the whale optimization algorithm with the gated recurrent unit-long short-term memory neural network. …”
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An Ultra-Short-Term Wind Power Prediction Method Based on the Fusion of Multiple Technical Indicators and the XGBoost Algorithm by Xuehui Wang, Yongsheng Wang, Yongsheng Qi, Jiajing Gao, Fan Yang, Jiaxuan Lu

“…However, its inherent volatility and unpredictability pose challenges for accurate short-term prediction. This study proposes an ultra-short-term wind power prediction framework that integrates multiple technical indicators with the extreme gradient boosting (XGBoost) algorithm. …”
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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

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