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Cable Force Optimization in Cable-Stayed Bridges Using Gaussian Process Regression and an Enhanced Whale Optimization Algorithm
Published 2025-07-01“…This study proposes an integrated framework combining Gaussian process regression (GPR) with an enhanced whale optimization algorithm improved by the Salp Swarm Algorithm (EWOSSA). …”
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483
Optimization of Multi-Energy Grid Integration and Energy Storage in Low-Carbon Power Systems Based on the TCM-MBZOA Algorithm: A Case Study of Yunnan Province
Published 2025-01-01“…To address this limitation, this paper proposes a multi-source coordinated optimization strategy based on a bi-level programming model and an improved tent chaotic mapping-memory backtracking zebra optimization algorithm (TCM-MBZOA). …”
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484
Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow
Published 2025-06-01“…In this study, a novel innovative deep neural network (DNN) structure by integrating a double Gated Recurrent Units (GRU) neural network model with a multiplication layer and meta-heuristic whale optimization algorithm (WOA) (i.e., hybrid 2GRU×–WOA model) is developed to improve the prediction accuracy and performance of mean monthly Chehel-Chai River’s streamflow (CCRSF m ) in Iran. …”
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485
Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm
Published 2023-02-01“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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486
Optimal Design of Multiband Microstrip Antennas by Self-Renewing Fitness Estimation of Particle Swarm Optimization Algorithm
Published 2019-01-01“…In order to reduce the time of designing microstrip antenna, this paper proposes a self-renewing fitness estimation of particle swarm optimization algorithm (SFEPSO) to improve the design efficiency. …”
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487
Short-term solar irradiance forecasting model based on hyper-parameter tuned LSTM via chaotic particle swarm optimization algorithm
Published 2025-05-01“…The output of the comparative study demonstrates that the proposed CPSO-LSTM model outperforms benchmark models, attaining a significant improvement in forecasting accuracy. …”
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488
Optimization Study of Centrifugal Fan Volute Parameters based on Non-dominated Sorting Genetic Algorithm III Algorithm
Published 2025-08-01“…The BP neural network provided highly accurate fitting and predictions, yielding a reliable surrogate model. After optimization, the centrifugal fan’s Q increased by 2.29%, and η improved by 2.96%. …”
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489
Identifying Capsule Defect Based on an Improved Convolutional Neural Network
Published 2020-01-01“…The Adam optimizer is introduced to accelerate model training and improve model convergence. …”
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490
Generative Target Tracking Method with Improved Generative Adversarial Network
Published 2023-01-01“…In this paper, we proposed a target tracking algorithm based on the conditional adversarial generative twin networks, using the improved you only look once multitarget association algorithm to classify and detect the position of the target to be detected in the current frame, constructing a feature extraction model using generative adversarial networks (GANs) to learn the main features and subtle features of the target, and then using GANs to generate the motion trajectories of multiple targets, finally fuzing the motion and appearance information of the target to obtain the optimal match. …”
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491
Robust Bi-Objective Optimization and Dynamic Modeling of Hydropneumatic Suspension Unit Considering Real Gas Effects
Published 2025-06-01“…The optimized design based on a metamodel and a hybrid metaheuristic algorithm resulted in an 81.4% reduction in peak lateral forces and a 53.3% improvement in acceleration robustness, which marks a significant increase in suspension system durability. …”
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492
An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm
Published 2025-08-01“…Abstract This paper introduces a novel optimization algorithm, Young’s double-slit experiment algorithm (YSDE), for accurately estimating the unknown parameters of Proton Exchange Membrane Fuel Cell (PEMFC) models. …”
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493
Structural Parameter Optimization of the Vector Bracket in a Vertical Takeoff and Landing Unmanned Aerial Vehicle
Published 2025-05-01“…The functionality of unmanned aerial vehicles (UAVs) in agricultural applications was improved by optimizing the parameters of the vector bracket in a vertical takeoff and landing UAV to maximize thrust and lift-to-drag ratio. …”
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494
Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization
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495
A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion
Published 2025-08-01“…The method incorporates an adaptive sampling strategy for RGB-D cameras based on IMU data calibration, introduces a pose estimation optimization algorithm that combines dynamic feature point cluster centroid prediction with bias detection, establishes a progressive 3D modeling approach constrained by structural features, and develops a prototype system for in-depth case study analysis. …”
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496
Object Detection Method of Inland Vessel Based on Improved YOLO
Published 2025-03-01“…Finally, GSConv and VovGSCSP in Slim-Neck are introduced into the Neck network to optimize the network architecture, reduce part of the model complexity, and further improve the performance of the model. …”
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497
Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model
Published 2025-08-01“…Finally, the parameter tuning of the fusion models is performed by using the Hiking Optimisation Algorithm (HOA) method. …”
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498
RRMSE-enhanced weighted voting regressor for improved ensemble regression.
Published 2025-01-01“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. …”
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499
FATIGUE CRACK GROWTH PREDICTION BASED ON IPSO-PF ALGORITHM
Published 2025-04-01“…The traditional Paris formula ignores the influence of various uncertain factors in the crack growth process, which leads to a big difference between the predicted crack growth process and the real crack growth process. In order to improve the prediction accuracy of fatigue crack growth, a fatigue crack growth prediction method based on the improved particle swarm optimization particle filtering (IPSO-PF) algorithm was proposed. …”
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500
Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment
Published 2025-04-01“…The detection and classification of DoW attacks, the multi-head attention-based bi-directional gated recurrent unit (MHA-BiGRU) model is utilized. Eventually, the improved secretary bird optimizer algorithm (ISBOA)-based hyperparameter choice process is accomplished to optimize the detection results of the MHA-BiGRU model. …”
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