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2621
Shoulder–Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration
Published 2025-05-01“…To address the precision challenges in upper-limb joint motion prediction, this study proposes a novel artificial neural network (COANN) enhanced by the Cheetah Optimization Algorithm (COA). The model integrates surface electromyography (sEMG) signals with joint angle data through multi-source information fusion, effectively resolving the local optima issue in neural network training and improving the accuracy limitations of single sEMG predictions. …”
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2622
An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction
Published 2025-07-01“…The model incorporates a neuron model with internal dynamics, including adaptive thresholds and inter-neuron feedback, into the reservoir structure. A Bayesian Optimization algorithm was employed for the selection of hyperparameters. …”
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2623
Investigation on the Role of Artificial Intelligence in Measurement System
Published 2025-01-01“…Hardware approach with soft computation has reduced non linearity error by 84.63% for thermocouple linearization, meanwhile novel hybrid approach using genetic algorithm (GA) and particle swarm optimization (PSO) combined with back propagation neural network (BPNN) have reduced mean absolute percentage error to 1.2 % for industrial weir than conventional hardware approaches using sensors and signal conditioning circuits but at higher computational cost. …”
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2624
Multimodal Control by Variable-Structure Neural Network Modeling for Coagulant Dosing in Water Purification Process
Published 2020-01-01“…In this paper, combined with rule base, through the PCA method, an improved multimodal variable-structure random-vector neural network algorithm (MM-P-VSRVNN) is proposed for coagulant dosing, which is a key production process in water purification process. …”
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2625
Orchard Navigation Method Based on RS-SC Loop Frame Search Method and SLAM Technology
Published 2025-01-01“…In the loop frame matching, an optimization algorithm combining normal distribution transformation and iterative nearest point is used to reduce the cumulative error significantly. …”
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2626
Bearing Fault Diagnosis in the Mixed Domain Based on Crossover-Mutation Chaotic Particle Swarm
Published 2021-01-01“…Finally, the support vector machine is optimized using the improved chaotic particle swarm to improve fault classification diagnosis. …”
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2627
Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model
Published 2011-01-01“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method(MLM) for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound(CRB) for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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2628
Scheduling and Evaluation of a Power-Concentrated EMU on a Conventional Intercity Railway Based on the Minimum Connection Time
Published 2025-02-01“…Moreover, they have certain cost advantages and practical operational value for improving the market competitiveness of conventional railways. …”
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2629
RFID-embedded mattress for sleep disorder detection for athletes in sports psychology
Published 2025-04-01“…This approach shows significant potential for sports psychology applications, enabling personalized recovery strategies and performance optimization. Future work will focus on expanding the dataset, integrating additional biometric sensors, and refining algorithms to improve diagnostic accuracy and real-time usability in clinical and home settings.…”
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2630
Unsupervised fake news detection on social media using hybrid Gaussian Mixture Model.
Published 2025-01-01“…In particular, it also proposes a novel hybrid method that leverages the Gaussian Mixture Model (GMM) in conjunction with the Group Counseling Optimizer (GCO), a metaheuristic optimization algorithm, to identify the optimal number of clusters for the detection of fake news. …”
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2631
An integrated approach of feature selection and machine learning for early detection of breast cancer
Published 2025-04-01“…Feature selection using recommended algorithm and optimization of the LightGBM model through PSO can significantly enhance the accuracy of breast cancer prediction. …”
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2632
Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights
Published 2025-04-01“…The study found that combining soil and climatic variables improved prediction accuracy, with ST, AT, and soil EC being the most influential variables. …”
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2633
PRIMARY CARE: HOW TO INCREASE PHYSICAL ACTIVITY IN YOUR PATIENTS
Published 2019-07-01“…The variant of rational outpatient counseling with the help of the algorithm of organization of physical activity mode, providing stratification of patients, planning, optimization and control of personal motor activity was presented. …”
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2634
Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning
Published 2024-11-01“…YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. …”
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2635
A dynamic service migration strategy based on mobility prediction in edge computing
Published 2021-02-01“…Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. …”
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2636
Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model
Published 2011-01-01“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method(MLM) for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound(CRB) for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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2637
Simulation analysis of path planning for workpiece clamping robots based on digital twin technology
Published 2025-06-01“…These results underscore the ability of the algorithm to efficiently and cost-effectively navigate complex obstacle configurations. …”
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2638
Hybridized Deep Learning Model for Perfobond Rib Shear Strength Connector Prediction
Published 2021-01-01“…In the second scenario, a comparable AI model hybridized with genetic algorithm (GA) as a robust bioinspired optimization approach for optimizing the related predictors for the PRSC is proposed. …”
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2639
HUMAN-ORIENTED QUALITY MANAGEMENT SYSTEM OF ENTERPRISE: CONTROL OF NON-CONFORMING PRODUCT AND UTILIZATION
Published 2013-09-01“…The existing classifications and operation algorithms of the QMS basic types allow optimizing the processes of product improvement, and the quality of life of the system participants improvement. …”
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2640
A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study
Published 2025-01-01“…To address the challenges (eg, the curse of dimensionality and increased model complexity) posed by high-dimensional features, we developed a dynamic adaptive feature selection optimization algorithm to identify the most impactful subset of features for classification performance. …”
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