Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm by Xiaole Tang, Hao Lu, Yanting Kang, Wenjun Zhao

Subjects: “…Photovoltaic power prediction system…”
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Algorithm for teaching students of the special educational department of physical education by Egorychev, Aleksey O., Egorycheva, Elina V.

“…Among students with health restrictions, a high proportion has a passive level of needs for physical education and sports activities. It is topical to create pedagogical conditions for a gradual transition from a passive state to a situational or active-activity state in relation to physical education and sports activities. …”
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Predictable and non-stationary processes of interval PREDICTION BASED ON stochastic differential equations by A. V. Ausiannikau

“…Predictability of such processes is defined. Algorithms of interval prediction in the discrete and continuous time are received.…”
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Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms by Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga, Ana Gómez

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Research on telecom industry customer churn prediction based on explainable machine learning models by WANG Shengjie, ZHANG Qinghong

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Machine Learning-Based Lithium Battery State of Health Prediction Research by Kun Li, Xinling Chen

“…To address the problem of predicting the state of health (SOH) of lithium-ion batteries, this study develops three models optimized using the particle swarm optimization (PSO) algorithm, including the long short-term memory (LSTM) network, convolutional neural network (CNN), and support vector regression (SVR), for accurate SOH estimation. …”
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GAN data reconstruction based prediction method of telecom subscriber loss by Kehong A, Xiaodong HU

“…Users are the core of operators’ interests.With the introduction of the policy of transferring network with a number, the competition between operators becomes more and more fierce.In order to accurately predict subscriber loss tendency in advance, a prediction method of subscriber loss based on generative adversarial network data reconstruction was proposed.Firstly, the dirty data in the telecom subscriber loss data was used by effective data preprocessing method.Secondly, the GAN was used to reconstruct the telecom subscriber loss data to solve the problem of the imbalance of the telecom subscriber loss data.Finally, extreme gradient boosting algorithm was used to train the telecom subscriber loss prediction model based on GAN reconstruction and the SMOTE sampling model based on synthetic minority oversampling technique sampling method respectively, and compare the prediction accuracy of the two models.The experimental results show that the prediction accuracy of the GAN reconstructed telecom subscriber loss prediction model is increased by 6.75%, the accuracy rate is increased by 25.91%, the recall rate is increased by 30.91%, and the F1-score is increased by 28.73% compared with the unreconstructed prediction model.This method can effectively improve the accuracy of telecom subscriber loss prediction.…”
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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“… This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. …”
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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

Subjects: “…dissolved oxygen prediction…”
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Predicting Movie Production Years through Facial Recognition of Actors with Machine Learning by Asraa Muayed Abdalah, Noor Redha Alkazaz

Subjects: “…Artificial Intelligence, Machine Learning Algorithms, Face Recognition, Age Prediction, Naive Bayes (NB), Decision Tree (DT), Support Vector Machine (SVM), and Artificial Neural Network (ANN)…”
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Performance Predictions of Solar-Assisted Heat Pumps: Methodological Approach and Comparison Between Various Artificial Intelligence Methods by Minghui Ma, Oguzhan Pektezel, Vincenzo Ballerini, Paolo Valdiserri, Eugenia Rossi di Schio

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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction by Babu Kumar, Radhakrishnan Soundararajan, Kanimozhi Natesan, Roobini Maridhas Santhi

“…Clinical data analysis must predict cardiovascular disease. Machine learning (ML) may aid decision making and prediction using the healthcare field’s massive data set. …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

“…The IDBO algorithm was then utilized to optimize the hyperparameters of the KELM model for predicting pile bearing capacity. …”
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Study of SDN intrusion intent identification algorithm based on Bayesian attack graph by Zhiyong LUO, Yu ZHANG, Qing WANG, Weiwei SONG

Subjects: “…SDN security prediction;intrusion intention;attack graph;PageRank algorithm…”
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A novel Knowledge Graph recommendation algorithm based on Graph Convolutional Network by Hui Guo, Chengyong Yang, Liqing Zhou, Shiwei Wei

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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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Mechanism-learning prediction model for pitting depth of buried pipeline based on HMOGWO-RF by Fulin SONG, Hong ZHAO, Xingyuan MIAO

“…By leveraging the combination of the three-objective HMOGWO algorithm and the RF model, it significantly outperformed the three-objective MOGWO algorithm, the two-objective HMOGWO algorithm, the two-objective MOGWO algorithm, as well as both the single-objective GWO algorithm and the single-objective PSO algorithm in terms of prediction performance and stability. …”
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Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale by Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak

“…This combined dataset, named GeoBlendMDWC, was specifically designed for SOC prediction. The primary aim of this research is to develop and evaluate a novel optimization algorithm for accurate SOC prediction by leveraging multi-source environmental data. …”
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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…The current study introduces an optimization algorithm, Learner Performance-Based Behavior with Simulated Annealing (LPBSA), integrated with Multilayer Perceptron (MLP) as a neural network technique to improve disease prediction accuracy. …”
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Noninvasive Blood Glucose Level Monitoring for Predicting Insulin Infusion Rate Using Multivariate Data by G. Geetha, J. Godwin Ponsam, K. Nimala

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