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1601
A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and Deep Learning Paradigms
Published 2025-01-01“…The findings underscore the synergy of advanced data augmentation, meta-heuristic optimization, and modern predictive algorithms in modelling hybrid nanofluid density with unprecedented precision. …”
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1602
Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children
Published 2025-03-01Subjects: Get full text
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1603
A KNN-based model for non-invasive prediction of hemorrhagic shock severity in prehospital settings: integrating MAP, PBUCO2, PTCO2, and PPV
Published 2025-05-01Subjects: Get full text
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1604
Machine learning-based seismic response forecasting using feature mapping algorithms and scientometric analysis of nailed vertical excavation in a soil mass
Published 2025-12-01“…The traditional approaches are constrained by unclear mechanisms and imprecise models to predict the stability of geostructures. The research gap between the accuracy of observed and predicted values can be bridged by employing artificial intelligence-based machine learning (ML) models. …”
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1605
Comparison, optimization and application of multiple prestack inversion algorithm for intermediate basic volcanic reservoirs: A case study of Huoshiling Formation in Chaganhua area
Published 2024-04-01“…Currently, the most widely used pre-stack simultaneous inversion algorithm is based on the Zoeppritz equation approximation of isotropic horizontal media. …”
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1606
Enhancing Upper Limb Exoskeletons Using Sensor-Based Deep Learning Torque Prediction and PID Control
Published 2025-06-01Subjects: “…torque estimation and prediction…”
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1607
Three-dimensional Underwater Dynamic Target Tracking Based on Adaptive Interactive Multi-model Algorithm
Published 2023-12-01“…In response to this, the paper introduces an adaptive parallel IMM (APIMM) based on current adaptive IMM algorithms. This method adaptively adjusts transition probabilities and pairs with the unscented Kalman filter (UKF) algorithm for state prediction of maneuvering targets in a 3D underwater environment. …”
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1608
Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models
Published 2025-05-01Subjects: “…PV prediction…”
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1609
A Multi-Input Multi-Output Considering Correlation and Hysteresis Prediction Method for Gravity Dam Displacement with Interpretative Functions
Published 2025-06-01Subjects: Get full text
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1610
Retracted: Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm
Published 2023-08-01“…Shaik, Suman Saha, Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm, IET Software 2023 (https://doi.org/10.1049/sfw2.12092)]. …”
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1612
Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm
Published 2024-11-01“…Addressing the non-linear and non-stationary characteristics of battery capacity sequences, a novel method for predicting lithium battery SOH is proposed using a deep hybrid kernel extreme learning machine (DHKELM) optimized by the improved black-winged kite algorithm (IBKA). …”
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1613
Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine
Published 2024-11-01“…Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. …”
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1614
Support of individual educational trajectories based on the concept of explainable artificial intelligence
Published 2022-01-01“…The authors proposed a methodology for digital support of IET, corresponding to the principles of explainable artificial intelligence, i.e. machine learning models predict educational outcomes, and a special algorithm automatically generates personalised recommendations based on the results of the analysis of data on the educational process. …”
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1615
Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting
Published 2023-08-01Subjects: Get full text
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1616
Enhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study
Published 2024-12-01“…Subsequently, we constructed 6 predictive models using different algorithms: logistic regression, support vector machine, gradient boosting machine, Extreme Gradient Boosting, multilayer perception, and graph convolutional networks. …”
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Enhanced Hyperspectral Forest Soil Organic Matter Prediction Using a Black-Winged Kite Algorithm-Optimized Convolutional Neural Network and Support Vector Machine
Published 2025-01-01“…This study uses 206 hyperspectral soil samples from the state-owned Yachang and Huangmian Forest Farms in Guangxi, using the SPXY algorithm to partition the dataset in a 4:1 ratio, to provide an effective spectral data preprocessing method and a novel SOM content prediction model for the study area and similar regions. …”
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1619
Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm
Published 2021-01-01“…In recent years, the use of artificial intelligence algorithms for gas outburst prediction has made progress, such as using BP neural network, GA algorithm, and SVM algorithm. …”
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1620
Performance Evaluation of a Radial Distribution Network Under Emerging Load Prediction Modeling Approach and DG Integration Using a Particle Swarm Optimization Algorithm
Published 2025-01-01“…These performance metrics are evaluated under various load conditions, including base load and forecasted loads derived from both ANN and ANFIS predictions, incorporating DG integration. The results highlight that the PSO algorithm excels in optimizing network performance, achieving remarkable results across all evaluated parameters. …”
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