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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network
Published 2025-04-01“…Next, sparse feature extraction is performed using Discrete Wavelet Transform (DWT), and a sparse matrix is constructed. A Genetic Algorithm (GA) is used to optimize the sparse matrix, which effectively selects the most significant features for prediction. …”
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82
Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization
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83
Research on Denoising of Bridge Dynamic Load Signal Based on Hippopotamus Optimization Algorithm–Variational Mode Decomposition–Singular Spectrum Analysis Method
Published 2025-04-01“…To address this issue, this research proposes a denoising method that combines the hippopotamus optimization algorithm (HOA), variational mode decomposition (VMD), and singular spectrum analysis (SSA). …”
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84
Enhanced Multi-Threshold Otsu Algorithm for Corn Seedling Band Centerline Extraction in Straw Row Grouping
Published 2025-06-01“…The method avoids premature convergence and improves population diversity by embedding the crossover mechanism of Differential Evolution (DE) into the Whale Optimization Algorithm (WOA) and introducing a vector disturbance strategy. …”
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85
A Novel Back Propagation Neural Network Based on the Harris Hawks Optimization Algorithm for the Remaining Useful Life Prediction of Lithium-Ion Batteries
Published 2025-07-01“…In order to achieve accurate and reliable RUL prediction, a novel RUL prediction method which employs a back propagation (BP) neural network based on the Harris Hawks optimization (HHO) algorithm is proposed. This method optimizes the BP parameters using the improved HHO algorithm. …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques
Published 2025-07-01“…The result of Genetic Algorithm analysis also proved the model has converged to the optimal solution effectively, the best solution of X1 = 49.41, X2 = 110.62, X3 = 11.85 and X4 = 20 which gives the maximum removal efficiency = 94.64% of methylene blue. …”
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88
A metaheuristic-based approach for optimizing the allocation of emergency water reservoirs for fire following earthquake suppression
Published 2025-09-01“…Using a metaheuristic algorithm, the optimal allocation zones are identified based on the total distance from urban areas and the FFE risk factor. …”
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Midspan Deflection Prediction of Long-Span Cable-Stayed Bridge Based on DIWPSO-SVM Algorithm
Published 2025-05-01“…The model incorporates wavelet transform to decompose deflection signals into temperature and vehicle load effects, allowing for a more detailed analysis of their individual impacts. The DIWPSO algorithm dynamically adjusts the inertia weight to balance global exploration and local exploitation, optimizing SVM parameters for improved performance. …”
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91
A novel research on network security situation prediction based on iteratively optimized RBF-NN
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92
Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks
Published 2025-07-01“…The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
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93
Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland
Published 2025-08-01“…To achieve this purpose, the Convolutional neural network (CNN) was integrated with Bidirectional long short-term memory network (BiLSTM) as main estimating module, and the Sparrow search algorithm (SSA) was employed to search the optimal hyperparameters of CNN-BiLSTM. …”
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94
Calculation method of line loss rate of substation areas considering tidal current variation with photovoltaic power generation access
Published 2025-04-01“…The proposed method employs an improved K-medoids clustering algorithm for substation area classification, optimized by an enhanced Cuckoo algorithm to minimize classification errors. …”
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95
Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe
Published 2025-07-01“…In contrast, supportive work environments—characterized by ergonomic design, good environmental quality, and worker autonomy—have been shown to improve well-being, productivity, and job satisfaction (4). …”
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96
Short-term Power Prediction of Photovoltaic Power Generation Based on LSTM and Error Correction
Published 2025-04-01“…Similarity measurement is conducted according to Hausdorff distance ( HD), and each modal component is assigned weights, and then LSTM optimized by Sparrow Search Algorithm ( SSA) is used to predict error modal components. …”
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97
A New Approach to Environmental Economic Dispatch Using Multiobjective Differential Evolution: A Case Study
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98
Emergency Resource Dispatch Scheme for Ice Disasters Based on Pre-Disaster Prediction and Dynamic Scheduling
Published 2025-07-01“…First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing of resource scheduling and reducing scheduling costs. …”
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99
Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line
Published 2025-10-01“…For simplification and practical field implementation, the same set of SOP values is applied across all 11 timesteps during the optimization process. Using the proposed optimization framework, the optimal results demonstrate improvements in Pavg, increasing by up to 109.8% (from 13.99 to 29.35 mm) and in S, reducing up to 79.6% (from 34.55 to 7.06 mm) when MOO is conducted as a time series using the simplified method. …”
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Advanced removal of butylparaben from aqueous solutions using magnetic molybdenum disulfide nanocomposite modified with chitosan/beta-cyclodextrin and parametric evaluation through...
Published 2025-06-01“…The predictive stability of PR emerges through these different dataset applications. The L-BFGS algorithm established the optimal control factors as pH = 6.64 and initial concentration = 1.00 mg/L and contact time = 60 min and adsorbent dosage = 0.8 g/L which dramatically improved the removal efficiency due to the collaborative properties of the nanocomposite. …”
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