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3281
HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson’s Disease Classification and Severity Prediction
Published 2025-01-01“…This leads to richer feature extraction, besides fusing different data modalities with accurate integration. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods are used in optimizing the model, by which the convergence speed raised by 15–20 %. …”
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3282
Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification
Published 2025-01-01“…The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. …”
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3283
A Trusted Sharing Strategy for Electricity in Multi-Virtual Power Plants Based on Dual-Chain Blockchain
Published 2025-05-01“…Again, an improved-Practical Byzantine Fault Tolerant (I-PBFT) consensus algorithm combining the schnorr protocol with the Diffie–Hellman key exchange algorithm and a smart contract for multi-VPP electricity trading are designed to realize trusted, secure, and efficient distributed transactions. …”
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3284
Dual-Closed-Loop Control System for Polysilicon Reduction Furnace Power Supply Based on Hysteresis PID and Predictive Control
Published 2025-07-01“…Meanwhile, the outer loop employs a hybrid MFAC-based improved PID algorithm to optimize the temperature tracking performance, achieving precise temperature control even in the presence of system uncertainties. …”
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3285
A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response
Published 2025-05-01“…First, feature selection is performed on the TON_IoT dataset to develop a Dream Optimization Algorithm (DOA)-optimized backpropagation neural network (DOA-BPNN) model for efficient anomaly detection. …”
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3286
Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC
Published 2025-01-01“…Compared to the hybrid A* algorithm, the optimized trajectory demonstrates superior space utilization and improved smoothness. …”
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3287
Knowledge graph-based intelligent control systems for real-time machine tool optimization
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3288
A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification
Published 2025-07-01“…To further improve the performance of the model, SSA was increased to select relevant features. …”
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3289
Lightweight and Efficient CSI-Based Human Activity Recognition via Bayesian Optimization-Guided Architecture Search and Structured Pruning
Published 2025-01-01“…Motivated by the need for accuracy and efficiency in resource-constrained environments, we combine Bayesian Optimization-based Neural Architecture Search (NAS) with a structured pruning algorithm. …”
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3290
Process Optimization for Complex Product Assembly Workshops with AGV Integration via Discrete Event Simulation
Published 2025-07-01“…This model simulates the coordination between AGVs and workstations while optimizing workstation layout and material flow. …”
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3291
An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection
Published 2020-01-01“…Numerical experiments indicate that this new algorithm makes much improvement by involving l0-norm regularization.…”
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3292
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3293
Research on Calibration Method of Laser Camera Sensor
Published 2020-01-01“…In this paper, a laser camera sensor calibration mathematical model was established, and the process of solving the calibration model parameters by the nonlinear least square method and Gauss-Newton iterative method was analyzed, and a L-M algorithm based on maximum likelihood estimation was proposed. …”
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3294
Fault classification of meta-action unit using CEEMDAN double-layer decomposition and COA-SVM
Published 2025-12-01“…Third, the model is optimized by the Coati Optimization Algorithm (COA) to optimize the fault classification performance of the SVM to achieve efficient and accurate fault diagnosis of the meta-action unit of the model. …”
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3295
TIM-FEM-ML synthetic technology for longitudinal optimization of tunnel excavated in the interlayered rock mass
Published 2025-08-01“…Python codes are programmed to realize automatic processing of numerical simulation and results are extracted to the ML algorithm for the prediction model. An optimization algorithm is implanted in the numerical stream file to retrieve the optimal relative intersection angle between the tunnel axis and the trend of rocks. …”
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3296
Method on intrusion detection for industrial internet based on light gradient boosting machine
Published 2023-04-01“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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3297
Improving forest above-ground biomass estimation using genetic-based feature selection from Sentinel-1 and Sentinel-2 data (case study of the Noor forest area in Iran)
Published 2024-04-01“…Furthermore, incorporating GA-based feature selection substantially improved the accuracy of both models, resulting in more dependable AGB estimations. …”
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3298
Robust Multi-Stage Planning of Park-Level Integrated Energy System Considering Source-Load Uncertainties
Published 2025-04-01“…[Objective] A robust multi-stage planning model is established for a park-level integrated energy system (PIES) to minimize the total life-cycle present-value cost while considering source-load uncertainties, optimal construction sequencing, and tiered carbon trading to enhance economic efficiency and low-carbon benefits. …”
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3299
Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience
Published 2025-03-01“…To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. …”
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3300
The role of artificial intelligence in vascular care
Published 2025-01-01“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
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