Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang, Jian Yang

“…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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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…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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Optimization of Body Size and Centroid Position of the Quadruped Robot based on Improved Particle Swarm Optimization Algorithm by Kai Tang, Huanlong Wu, Liang′an Zhang, Ranming Ji, Yongjie Zhao, Xiaoyi Wang, Xinjian Lu

“…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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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…<b>Objectives</b>: The aim of this study is to evaluate and enhance the predictive capabilities of machine learning models for SSIs by assessing the effects of feature selection, resampling techniques, and hyperparameter optimization. …”
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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…The CFOPS-BSBEA technique leverages the strengths of both steganography and encryption to provide a secure and effective approach to digital image protection. The Crayfish Optimization algorithm is used to select the most suitable pixels for steganography, ensuring that the secret image is embedded in a way that minimizes detection. …”
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Optimization of electric vehicle charging facility layout considering the enhancement of renewable energy consumption capacity and improvement of PSO algorithm by Di Zheng, Baobao Zheng

“…To deal with the optimization model, the particle swarm optimization is adopted and improved in three aspects. …”
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Robot Calibration Sampling Data Optimization Method Based on Improved Robot Observability Metrics and Binary Simulated Annealing Algorithm by Huakun Jia, Hanbo Zeng, Jiyan Zhang, Xiangyang Wang, Yang Lu, Liandong Yu

“…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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Illustration Design Model with Clustering Optimization Genetic Algorithm by Jing Liu, Qixing Chen, Xiaoying Tian

“…This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. …”
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Food sorting trajectory optimization based on improved NURBS and Delta parallel robots by CHEN Guangdong, SHAO Jian, WANG Feini, ZHAO Xuecheng

“…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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Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access by Xiping Ma, Xiping Ma, Xiaoyang Dong, Haitao Xiao, Yaxin Li, Rui Xu, Kai Wei, Juanjuan Cai, Juan Wei

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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…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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Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm by Zeyu Zou, Hui Zeng, Xiaodong Zheng, Junming Chen

“…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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Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning by Shijin Li, Fucai Wang

“…Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. …”
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Construction Scheduling Optimization of Prefabricated Buildings Under Resource Constraints Based on an Improved Whale Optimization Algorithm by Rui Su, Joey S. Aviles

“…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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A model for assessing lethal resistance levels of various buildings based on improved genetic algorithm + BP neural network optimization by Jie Zhang, Jie Zhang, Bin Tan, Bin Tan, Chaoxu Xia, Wenbin Yan, Yuan Tao, Yuan Tao, Ben Ma, Ben Ma

“…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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Bus Arrival Time Prediction Based on the Optimized Long Short-Term Memory Neural Network Model With the Improved Whale Algorithm by Bing Zhang, Lingfeng Tang, Dandan Zhou, Kexin Liu, Yunqiang Xue

“…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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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

“…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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Model updating method for detect and localize structural damage using generalized flexibility matrix and improved grey wolf optimizer algorithm (I-GWO) by Sina Sadraei, Majid Gholhaki, Omid Rezaifar

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Path Optimization Strategy for Unmanned Aerial Vehicles Based on Improved Black Winged Kite Optimization Algorithm by Shuxin Wang, Bingruo Xu, Yejun Zheng, Yinggao Yue, Mengji Xiong

“…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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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…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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