-
3461
A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain
Published 2025-03-01“…Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. …”
Get full text
Article -
3462
Design optimization of multipoles radial magnetic bearings for large industrial rotors
Published 2025-07-01“…The design objective is to minimize the bearing volume while providing the required bearing capacity, taking into consideration the design constraints imposed. …”
Get full text
Article -
3463
-
3464
Fusion of MHSA and Boruta for key feature selection in power system transient angle stability
Published 2025-01-01“…Subsequently, the Boruta algorithm is employed to determine the number of key features. …”
Get full text
Article -
3465
Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization
Published 2024-11-01“…The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
Get full text
Article -
3466
Knowledge Graph-Enhanced Digital Twin Framework for Optimized Job Shop Scheduling in Smart Manufacturing
Published 2025-01-01“…The approach is grounded in a DT framework that leverages a knowledge graph to represent the assets of the manufacturing system. Two algorithms are designed to balance the time required to complete a list of jobs with the energy consumed by the machines in the factory, all while considering the delivery deadline of the final product. …”
Get full text
Article -
3467
A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling
Published 2025-12-01“…To solve large-scale problems, an improved adaptive large neighborhood search algorithm (ALNS) is designed accordingly. The proposed method's solution efficiency is compared with genetic algorithms (GA) and commercial solvers (CPLEX) through small case studies. …”
Get full text
Article -
3468
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. …”
Get full text
Article -
3469
Comprehensive quality assessment of 296 sweetpotato core germplasm in China: A quantitative and qualitative analysis
Published 2024-12-01“…Landraces had higher sugar content in roots, while wild relatives showed increased total flavonoid and phenol contents. …”
Get full text
Article -
3470
Salp Navigation and Competitive based Parrot Optimizer (SNCPO) for efficient extreme learning machine training and global numerical optimization
Published 2025-04-01“…The results demonstrate that SNCPO consistently outperforms existing state-of-the-art algorithms, achieving superior convergence speed, solution quality, and robustness while effectively avoiding local optima. …”
Get full text
Article -
3471
Energy-efficient artificial fish swarm-based clustering protocol for enhancing network lifetime in underwater wireless sensor networks
Published 2024-12-01“…It also reduces energy consumption by 25.6% and decreases packet loss by 50.5%, while achieving 20.4% higher throughput at the initial stage. …”
Get full text
Article -
3472
A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework
Published 2025-08-01“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
Get full text
Article -
3473
An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection
Published 2025-03-01“…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
Get full text
Article -
3474
Grid Integration of PV Systems With Advanced Control and Machine Learning Strategies
Published 2025-01-01“…The primary objective is to optimize voltage output from PV system while concurrently maximizing power using a novel Modified Zeta-Cuk converter, coupled with Hybrid Maximum Power Point Tracking (MPPT) algorithm combining Incremental Conductance and Bat Optimization Algorithm (InC-BOA). …”
Get full text
Article -
3475
RLEAFS: Reinforcement Learning-Based Energy Aware Forwarding Strategy for NDN-Based IoT Networks
Published 2024-01-01“…Our Strategy integrates Q learning algorithm into path selection procedure, focusing on minimizing energy consumption and extending network lifetime while maintaining efficient data delivery. …”
Get full text
Article -
3476
-
3477
-
3478
The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model
Published 2025-05-01“…This research offers a solid scientific foundation for risk classification and hazard mitigation strategies while introducing a novel methodological framework through the integration of innovative algorithms. …”
Get full text
Article -
3479
Optimization of OPM-MEG Layouts with a Limited Number of Sensors
Published 2025-04-01“…We applied a sequential selection algorithm (SSA), originally developed for body surface potential mapping in electrocardiography, which requires a large database of full-head MFMs. …”
Get full text
Article -
3480
A solution to the Single-School school bus routing problem considering accessibility and economy
Published 2025-07-01“…In the third stage, Dijkstra’s algorithm is combined with GIS to optimize the bus routes, with a focus on accessibility and economy.Experimental results demonstrate that the THGO method can efficiently find the global optimal solution while satisfying constraints such as time windows, bus capacity, and road directionality. …”
Get full text
Article