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2921
Hybrid adaptive ant lion optimization with traditional controllers for driving and controlling switched reluctance motors to enhance performance
Published 2025-04-01“…To address these issues, this work introduces a novel hybrid adaptive ant lion optimization (HAALO) algorithm, combined with PI and FOPID controllers, to improve SRM performance. …”
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2922
An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration
Published 2025-04-01“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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2923
Midspan Deflection Prediction of Long-Span Cable-Stayed Bridge Based on DIWPSO-SVM Algorithm
Published 2025-05-01“…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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2924
Short‐term electric power and energy balance optimization scheduling based on low‐carbon bilateral demand response mechanism from multiple perspectives
Published 2024-12-01“…The enhanced decision tree classifier (EDTC) algorithm is used to predict the electricity consumption behavior of transferable load (TL) users, and an improved particle swarm optimization (PSO) algorithm with “ε‐greedy” strategy is proposed to solve this model. …”
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2925
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2926
Optimization of Vessel Traffic Scheduling in a Compound Channel of an Estuarine Port with Opposing Distribution of Inner Anchorages and Terminals
Published 2025-03-01“…The entropy-weighted technique for order preference by similarity to ideal solution (TOPSIS) is used to calculate the objective weights of the Pareto frontier and identify the optimal solution. Experimental results show that the proposed model and algorithm yield optimal port entry and exit scheduling solutions. …”
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2927
Multi-Objective Optimization of Daylighting–Thermal Performance in Cold-Region University Library Atriums: A Parametric Design Approach
Published 2025-02-01“…In this paper, we take the library project in the cold region as a practical case, use the measured data to support the simulation experiment, combine the parametric platform and multi-objective coupling optimization algorithm to carry out digital modeling, and explore the dynamic relationship between the atrium light, heat environment, and the value of energy consumption under the influence of a variety of parameters. …”
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2928
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2929
Hybrid optimization for efficient 6G IoT traffic management and multi-routing strategy
Published 2024-12-01“…Data was successfully routed using a hybrid Quantum Genetic Algorithm and Ant Colony Optimization (QGA-ACO) approach. …”
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2930
Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm
Published 2021-01-01“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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2931
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2932
SMA-YOLO: An Improved YOLOv8 Algorithm Based on Parameter-Free Attention Mechanism and Multi-Scale Feature Fusion for Small Object Detection in UAV Images
Published 2025-07-01“…Using YOLOv8n as the baseline, SMA-YOLO is evaluated on the VisDrone2019 dataset, achieving a 7.4% improvement in mAP@0.5 and a 13.3% reduction in model parameters, and we also verified its generalization ability on VAUDT and RSOD datasets, which demonstrates the effectiveness of our approach.…”
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2933
Coordinated multi-objective optimization scheduling for electric vehicle swapping station cluster and grid
Published 2025-05-01“…Meanwhile, an electricity mutual assistance strategy between EVBESS is proposed to improve overall energy efficiency. Subsequently, an improved many-objective optimization algorithm based on multiple update strategies (G-MOMUS) is used to solve the model. …”
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2934
Surface Reconstruction Planning with High-Quality Satellite Stereo Pairs Searching
Published 2025-07-01Get full text
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2935
DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS
Published 2025-03-01“…Due to incorporation of dual bioinspired optimizers with autoregressive correlation, the model is able to improve prediction accuracy by 8.5%, precision by 4.9%, recall by 1.5%, while reducing computational delay by 3.4% when compared with standard air quality analysis models. …”
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2936
Evolutionary Synthesis of High-Capacity Reconfigurable Multilayer Road Networks Using a Multiagent Hybrid Clustering-Assisted Genetic Algorithm
Published 2025-01-01“…To achieve this goal, a new multiagent hybrid clustering-assisted genetic algorithm (MA-HCAGA). The proposed algorithm combines the use of binary-coded crossovers and mutations as genetic operators, and biobjective discrete particle swarm optimization (BODPSO) techniques to improve the evolutionary search process. …”
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2937
Model Predictive Control of Nonlinear System Based on GA-RBP Neural Network and Improved Gradient Descent Method
Published 2021-01-01“…A model predictive control (MPC) method based on recursive backpropagation (RBP) neural network and genetic algorithm (GA) is proposed for a class of nonlinear systems with time delays and uncertainties. …”
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2938
Gradient descent based dynamic optimization for VSG dominated microgrid
Published 2024-12-01“…This article proposes an optimization method based on the gradient descent algorithm to fine‐tune the control parameters of multiple VSGs in independent microgrids. …”
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2939
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2940
A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints
Published 2025-07-01“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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