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261
Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques
Published 2025-08-01“…The Superimposed Image combined these heatmaps with the original lesion images, making it clear which parts of the lesions influenced the model’s classification. These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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262
Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II
Published 2025-02-01“…Given the complex modeling and numerous constraints faced by the production of prefabricated components, we propose an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. …”
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263
Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms
Published 2025-06-01“…Simulation results demonstrate that the proposed algorithm reduces the average path length by 15.4% and 7.5% compared to traditional genetic algorithm and particle swarm optimization, respectively, while improving computational efficiency by 45.5% and 16.8%.…”
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264
Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer
Published 2025-07-01“…Key observations include: (1) the CNN-LSTM-BMO model converges 27% faster than traditional optimization methods; (2) SHapley Additive exPlanations (SHAP) analysis reveals that temperature-related features, particularly saturation temperature, are the most influential predictors across all models; and (3) the proposed model maintains prediction accuracy even under varying operational conditions. …”
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265
Robot Calibration Sampling Data Optimization Method Based on Improved Robot Observability Metrics and Binary Simulated Annealing Algorithm
Published 2024-09-01“…By utilizing the least squares method, the ideal pose transformation relationship between the robot’s base coordinate system and the laser tracker measurement coordinate system is derived, resulting in an error calibration model based on spatial single points. An improved robot observability metric combined with the Binary Simulated Annealing Algorithm (BSAA) is introduced to optimize the selection of calibration sampling data. …”
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266
Food sorting trajectory optimization based on improved NURBS and Delta parallel robots
Published 2024-10-01“…ObjectiveReduce the running time and impact of Delta robot in food sorting trajectory, improve the efficiency and stability of Delta robot operation.MethodsBased on the analysis of the food sorting system (using Delta robots), a Delta robot food sorting trajectory optimization method was proposed, which combined NURBS algorithm, sparrow search algorithm and butterfly optimization algorithm. …”
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267
A model for assessing lethal resistance levels of various buildings based on improved genetic algorithm + BP neural network optimization
Published 2025-03-01“…This study proposes a novel model that integrates an improved genetic algorithm (IGA) with an optimized backpropagation neural network (OBPNN) to address data imbalance in classifying building types for lethal resistance levels assessment. …”
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268
Bus Arrival Time Prediction Based on the Optimized Long Short-Term Memory Neural Network Model With the Improved Whale Algorithm
Published 2024-01-01“…Accurate prediction of bus arrival time is essential to achieve efficient bus dispatch and improve bus trip sharing rate. This article proposes using the improved whale optimization algorithm–long short-term memory (IWOA–LSTM) model to predict bus arrival times and improving the whale algorithm by optimizing the hyperparameters of the LSTM model, so that the advantages and disadvantages of the whale algorithm and the LSTM model can complement each other, thus enhancing the robustness of the model. …”
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269
A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm
Published 2025-06-01“…Traditional empirical formulas often yield unsatisfactory prediction results. To improve the prediction accuracy of the peak particle velocity (PPV), this paper combines the ability of an artificial neural network (ANN) to solve complex nonlinear function approximations and the global optimization ability of 10 metaheuristic optimization algorithms and establishes an improved ANN prediction model. …”
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270
Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm
Published 2025-02-01“…Case studies were conducted to evaluate the feasibility and effectiveness of both the proposed model and the algorithm. Results indicate that the model accurately reflects the dynamics of emergency logistics operations, while the hybrid algorithm exhibits strong local optimization capabilities and robust performance in handling diverse and complex scenarios. …”
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271
Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning
Published 2020-01-01“…Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. …”
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272
Construction Scheduling Optimization of Prefabricated Buildings Under Resource Constraints Based on an Improved Whale Optimization Algorithm
Published 2025-07-01“…To solve this model effectively, an Improved Whale Optimization Algorithm (IWOA) is developed, addressing the limitations of the standard WOA such as premature convergence and poor local search ability. …”
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273
Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm
Published 2025-05-01“…Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. …”
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274
Optimization of Body Size and Centroid Position of the Quadruped Robot based on Improved Particle Swarm Optimization Algorithm
Published 2021-07-01“…Taking the quadruped robot as research object, a method to optimize body size and centroid position of the quadruped robot based on improved particle swarm optimization algorithm to enhance its stability is proposed. …”
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275
Path Optimization Strategy for Unmanned Aerial Vehicles Based on Improved Black Winged Kite Optimization Algorithm
Published 2025-05-01“…The Black-winged Kite Optimization Algorithm (BKA) is likely to experience a sluggish convergence rate when confronted with the optimization of complex multimodal functions. …”
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276
Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization
Published 2025-08-01“…Moreover, the convolutional autoencoder (CAE) model is implemented for classification. Additionally, the hippopotamus optimization algorithm (HOA)-based hyperparameter selection model is implemented to improve the classification result of the CAE technique. …”
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277
Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments
Published 2025-08-01“…This study presents Cybersecurity using a Crested Porcupine Optimizer Algorithm with Hybrid Deep Learning Models (CCPOA-HDLM). …”
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278
SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study
Published 2025-03-01“…Abstract In this study, we propose a novel approach for breast cancer classification that integrates the Seagull Optimization Algorithm (SGA) for feature selection with the Random Forest (RF) classifier for effective data classification. …”
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279
Parameter identification of photovoltaic inverter based on improved particle swarm optimization algorithm
Published 2025-01-01“…The advantages of the proposed method can be obtained by comparing the synchronous identification results of the parameters, and the identification results were substituted into the simulation model.ResultsThe error of synchronous identification results of low sensitivity parameters was far beyond the acceptable range, and the error of relevant parameters identified by CGAPSO step by step was less than 1.1%, which was much higher than the accuracy of synchronous identification results.ConclusionsThe output data of the identification model based on the improved particle swarm optimization algorithm had a high agreement with the actual inverter working data,which could accurately reflect the actual working characteristics of the inverter.…”
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280
Optimization of Planning Layout of Urban Building Based on Improved Logit and PSO Algorithms
Published 2018-01-01“…Then, the evaluation model of urban building planning based on improved logit and PSO algorithm is established. …”
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