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741
Electrical Fault Diagnosis Method for Tunneling Equipment Based on Fault Simulation and Optimized Particle Swarm Algorithm
Published 2025-01-01“…To address the challenges of scarce training data and poor adaptability to dynamic working conditions in electrical fault diagnosis for tunneling equipment, this study proposes an intelligent diagnosis model based on fault simulation and Improved Particle Swarm Optimization (IPSO). …”
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744
Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO
Published 2024-04-01“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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747
A Novel Ship Fuel Sulfur Content Estimation Method Using Improved Gaussian Plume Model and Genetic Algorithms
Published 2025-03-01“…The emission source intensity inversion was formulated as an unconstrained multi-dimensional optimization problem, solved using genetic algorithms. …”
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748
Short-Term Power Load Prediction Based on Level Processing Method and Improved GWO Algorithm
Published 2025-01-01“…To address this issue, this study introduces level processing method and improved grey wolf genetic algorithm to predict short-term power load and optimize the power load prediction accuracy. …”
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749
Heat Dissipation Structure Optimization of Inverter Based on the Optimal Control Strategy
Published 2020-01-01“…Compared with the original air cooling structure, the new cooling method can reduce the maximum working temperature of the chips by 8.49 ℃ . In this paper, the optimal Latin hypercube sampling is used to construct the response surface surrogate model (RSM), and the multi-island genetic algorithm (MIGA) is used to optimize the surrogate model. …”
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750
APPLYING GRAPH THEORY TO OPTIMIZE PRODUCT DELIVERY ROUTES AND MINIMIZE COSTS IN THE RESTAURANT BUSINESS
Published 2025-06-01“…Routing algorithms based on graphical description are considered the most optimal analysis method for developing optimal product delivery routes, which helps minimize enterprise costs. …”
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751
Enhancement of rime algorithm using quadratic interpolation learning for parameters identification of photovoltaic models
Published 2025-07-01“…This paper proposes a novel Improved version of Rime Metaheuristic Optimization (RMO) influenced by rime growth and combined with Quadratic Interpolation Learning (QIL) technique for the simulation and design of the triple-Diode Model (DM). …”
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752
An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date
Published 2025-01-01“…This study evaluates the efficiency of a swarm intelligence algorithm called marriage in honey-bee optimization (MBO) in solving the single-machine weighted earliness/tardiness problem, a type of NP-hard combinatorial optimization problem. …”
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753
A study on method for bearing residual life prediction based on optimized Bray-Curtis dissimilarity and PSO algorithms
Published 2023-05-01“…In this paper, a new bearing health index set was set up by combining the sparse autoencoder (SAE) and the Bray-Curtis dissimilarity algorithm, and the bearing degradation model was established by using the improved particle swarm optimization (PSO) algorithm, to predict the residual life of the tested bearings. …”
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754
Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network
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755
Aquaculture Prediction Model Based on Improved Water Quality Parameter Data Prediction Algorithm under the Background of Big Data
Published 2022-01-01“…Considering the complex relationship between dissolved oxygen and water quality, combined with principal component analysis, a PCA-BP (principal component analysis back propagation) water quality prediction model was proposed. The parameters of PCA-BP water quality prediction model were optimized by genetic algorithm, the threshold and weight of BP neural network were determined, and an improved PCA-BP water quality prediction model was constructed. …”
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756
Discrete Dynamic Modeling Analysis of Engineering Management and Quality Optimization Innovation Mode Based on Big Data Intelligent Algorithm
Published 2022-01-01“…It mainly uses big data technology to collect and classify the obtained data information and uses discrete dynamic modeling technology to optimize the management system, focus on the management and innovation of green engineering, use big data dynamic modeling technology to build engineering management model, and improve the balance of project model through intelligent planning algorithm. …”
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757
Optimization Strategy of Microgrid Hierarchical Scheduling Considering Electric Vehicles User Satisfaction Degree
Published 2020-12-01“…Renewable energy is used to support the load of the microgrid in the source storage layer, and the excess part is absorbed by the dispatchable electric vehicle, which makes the comprehensive cost of the microgrid minimized. The improved ant lion algorithm is used to solve the model of the source storage layer. …”
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758
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
Published 2025-04-01“…This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. …”
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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates
Published 2025-05-01“…The combination of the one-dimensional model, the surrogate model, and the genetic algorithm can effectively improve the optimization efficiency.…”
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