-
1821
Lithium-Ion Battery State of Health Estimation Based on CNN-LSTM-Attention-FVIM Algorithm and Fusion of Multiple Health Features
Published 2025-07-01“…The model adopts the collaborative architecture of a convolutional neural network and time series module, strengthens the cross-level feature interaction by introducing a multi-level attention mechanism, then uses the FVIM optimization algorithm to optimize the key parameters to realize the overall model architecture. …”
Get full text
Article -
1822
Joint Optimization of Multienergy Virtual Power Plant Configuration and Operation Considering Electric Vehicle Access
Published 2025-01-01“…Based on the gazelle algorithm and mixed integer linear programming (MILP), the capacity and output of the system energy equipment are jointly optimized, and the running curve of MEVPP in a typical quarter is analyzed. …”
Get full text
Article -
1823
Research on Prediction and Optimization of Airport Express Passenger Flow Based on Fusion Intelligence Network Model
Published 2024-12-01“…The purpose of this paper is to optimize the accuracy of airport express passenger flow prediction so as to meet the need for the optimal allocation of traffic resources against the background of accelerated urbanization and the rapid development of airport express services. …”
Get full text
Article -
1824
Optimal Allocation Method of Integrated Energy System Considering Joint Operation of Multiple Flexible Resources
Published 2025-07-01“…Then, aimed at the uncertainty of renewable energy output, the optimal clustering number is determined by Elbow method, and typical wind speed scenarios are obtained by K-means clustering algorithm. …”
Get full text
Article -
1825
Bayesian Optimization-Based State-of-Charge Estimation with Temperature Drift Compensation for Lithium-Ion Batteries
Published 2025-06-01“…For this reason, this study proposes an algorithm focusing on Bayesian optimization-based adaptive extended Kalman filter (BO-AEKF) to enhance the numerical accuracy and stability of state-of-charge (SOC) estimation for lithium batteries under various operating conditions. …”
Get full text
Article -
1826
An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan
Published 2025-01-01“…In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). We designate the resulting algorithm as NEPFM-SSA as it took NEPFM’s Weibull distribution parameters as an initial guess and retuned them with the help of the simplex search algorithm to get updated Weibull distribution parameters, which ensure better fitting characteristics. …”
Get full text
Article -
1827
Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost
Published 2025-07-01“…In order to address the issues of low accuracy and poor interpretability in existing HFMD incidence prediction models, in this paper, we propose an interpretable prediction model, namely, ARIMA–LSTM–XGBoost, which integrates multiple meteorological factors with Autoregressive integrated moving average model (ARIMA), Long short-term memory (LSTM), Extreme gradient boosting (XGBoost), Grey wolf optimizer (GWO), Genetic algorithm (GA) and Shapley additive explanations (SHAP). …”
Get full text
Article -
1828
Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data
Published 2022-01-01“…To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. …”
Get full text
Article -
1829
Tuning of Pareto-optimal robust controllers for multivariable systems. Application on helicopter of two-degress-of-freedom
Published 2015-04-01“…The tuning of Pareto-optimal robust controllers was applied to improve the performance of a helicopter with two-degrees-of-freedom with a linear control algorithm. …”
Get full text
Article -
1830
Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES
Published 2025-05-01“…Then, an integrated energy model is established and it optimized using an improved stepwise carbon trading and power to gas and carbon capture system (P2G-CCS) coupling model. …”
Get full text
Article -
1831
An intelligent stochastic optimization approach for air cargo order allocation under carbon emission constraints.
Published 2025-01-01“…The method finds the optimal solution through an improved adaptive large-scale neighborhood search algorithm and uses a scenario generation technique to generate the scenarios required for evaluating candidate solutions to the high-dimensional stochastic optimization problem. …”
Get full text
Article -
1832
Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue
Published 2022-12-01“…The wind power offset was decomposed by a Butterworth low-pass filter, and the low-frequency and high-frequency components were used as the reference power of lithium battery energy storage and flywheel energy storage, respectively. In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
Get full text
Article -
1833
Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
Published 2021-01-01“…PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. …”
Get full text
Article -
1834
Hybrid Hunger Games Search optimization using a neural networks approach applied to UAVs
Published 2025-09-01“…Optimization methods like population-based algorithms are valuable when applied to multidimensional and nonlinear problems. …”
Get full text
Article -
1835
Research on optimization of C4 repair operation of Harmony electric locomotive based on preventive maintenance.
Published 2025-01-01“…Under the premise of ensuring locomotive operational safety, it effectively saves costs, reduces maintenance downtime and achieves the objective of improving the quality of C4 repairs.…”
Get full text
Article -
1836
Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach
Published 2024-12-01“…This advancement highlights the TS algorithm’s potential to deliver substantial scalability and optimization benefits, particularly for high-demand scenarios, albeit with a necessary consideration for computational cost.…”
Get full text
Article -
1837
Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment
Published 2019-01-01“…For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. …”
Get full text
Article -
1838
-
1839
Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding
Published 2025-07-01“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
Get full text
Article -
1840
UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures
Published 2025-03-01“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
Get full text
Article