Improving the navigation optimization of hospital logistics robots under complex lighting changes by using improved ORB-SLAM3 and deep learning visual SLAM algorithm by Feng Xiao, Youhai Zhang, Jie Fang, Xing Guo, Rubing Huang

“…The improved ORB-SLAM3 algorithm extracts feature points of different scales by constructing an image pyramid to ensure that effective visual information can be stably obtained under different lighting conditions; the strategy of combining adaptive threshold and dual threshold methods is used to optimize the accuracy of feature point extraction, and the feature points are efficiently managed through a four-tree model to ensure the uniform distribution of feature points. …”
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Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model by Bo Zhou, Erchao Li, Wenjing Liang

“…Finally, a combination algorithm of improved robust optimization over time (ROOT) and CPLEX is proposed to solve the established game model. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The model is based on TBESO (Multi-strategy Boosted Snake Optimizer) and utilizes monthly Dairy Herd Improvement (DHI) data to forecast the status of subclinical mastitis in cows.Materials and methodsThe Monthly Dairy Herd Improvement (DHI) data spanning from January 2022 to July 2022 (full dataset) was partitioned into both the training and testing datasets. …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…The inherent characteristics of unbalanced three-phase distribution networks can have negative technical and financial effects. In this vein, optimal conductor size selection and phase balancing are among the most common strategies for improving these indicators, which involves dealing with complex optimization problems. …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…The variables are microgrid optimal location and capacity of the HMG components in the network which are determined through a multi-objective improved Kepler optimization algorithm (MOIKOA) modeled by Kepler’s laws of planetary motion, piecewise linear chaotic map and using the FDMT. …”
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Improvement of Wild Horse Optimizer Algorithm with Random Walk Strategy (IWHO), and Appointment as MLP Supervisor for Solving Energy Efficiency Problem by Şahiner Güler, Erdal Eker, Nejat Yumuşak

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A Non-Rigid Three-Dimensional Image Reconstruction Algorithm Based on Deformable Shape Reliability by Haiying Chen, Syed Atif Moqurrab

“…This paper introduces an enhanced-reliability reconstruction algorithm for non-rigid 3D images. Our algorithm models the dynamic non-rigid shape basis as a low-rank matrix composed of image points and depth factors, improving the restoration of non-rigid shape base changes and providing accurate parameters for constructing objective functions. …”
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Simulation-Based Two-Stage Scheduling Optimization Method for Carrier-Based Aircraft Launch and Departure Operations by Jue Liu, Nengjian Wang

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An Improved NSGA-III Algorithm for Scheduling Ships Arrival and Departure the Main Channel of Tianjin Port by Luzhen Ren, Yuzheng Li, Shibo Zhou

“…The improved NSGA-III algorithm employs the Metropolis criterion in the simulated annealing algorithm in conjunction with the small habitat technique to optimize the initial population of NSGA-III. …”
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Ultra-Short-Term Wind Power Forecasting Based on the MSADBO-LSTM Model by Ziquan Zhao, Jing Bai

“…Incorporating an improved Sine Algorithm (MSA) into the forecasting model for this nonlinear problem significantly improves the position update strategy of the Dung Beetle Optimization Algorithm (DBO), which tends to be overly random and prone to local optima. …”
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An improved multiclass classification of acute lymphocytic leukemia using enhanced glowworm swarm optimization by Saranya N, Kalamani M

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Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…Key findings include: (1) Threat Detection: GESAC achieves an F1-score of 0.915–0.931 in identifying physical-layer attacks such as wavelength eavesdropping and cross-domain privilege escalation, with a false positive rate as low as 0.7%. (2) Resource Optimization: Compared to greedy strategies, GESAC improves wavelength utilization variance by up to 58.9% and reduces end-to-end latency standard deviation by up to 57.7% under high-load conditions. (3) Policy Robustness: In scenarios involving topological mutations, the model increases Pareto frontier coverage by over 100% and reduces policy entropy decay rate by more than 65%, indicating strong robustness. (4) Scalability: At a scale of 100,000 network nodes, GESAC achieves a single-step decision latency of just 25.6µs and significantly reduces communication overhead, demonstrating excellent scalability. …”
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Competitive Elimination Improved Differential Evolution for Wind Farm Layout Optimization Problems by Sichen Tao, Yifei Yang, Ruihan Zhao, Hiroyoshi Todo, Zheng Tang

“…Therefore, metaheuristic algorithms with inherent discrete characteristics like genetic algorithms (GAs) and particle swarm optimization (PSO) have been extensively developed into current state-of-the-art WFLOP optimizers. …”
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Research on a Target Detection Algorithm for Common Pests Based on an Improved YOLOv7-Tiny Model by He Gong, Xiaodan Ma, Ying Guo

“…Additionally, compared to algorithms like Faster R-CNN, SSD, and RetinaNet, the improved model delivers superior detection performance. …”
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Improved genetic algorithm based on Shapley value for a virtual machine scheduling model in cloud computing by Lili Chen, Lili Chen, Yuxia Niu

“…As the number of evolutionary generations increases, the ability of SVM-GA to reach the optimal solution of the model increases. In the simulated light load case, the SVM-GA migration time and Q10 migration count optimal solutions are slightly inferior to those of the logistic regression algorithm (3.02 s > 2.38 s; 1,129 times >999 times), but the migration energy consumption and service level agreement violation rate optimal solutions are superior. …”
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Improved Virtual Potential Field Algorithm Based on Probability Model in Three-Dimensional Directional Sensor Networks by Junjie Huang, Lijuan Sun, Ruchuan Wang, Haiping Huang

“…The extensive simulations results demonstrate the effectiveness of our proposed 3D sensing model and IPA3D (improved virtual potential field based algorithm in three-dimensional directional sensor networks).…”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm by Alaa O. Khadidos, Ayman Yafoz

“…This paper proposes a novel Object Detection Model for Visually Impaired Individuals with a Metaheuristic Optimization Algorithm (ODMVII-MOA) technique. …”
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Improvement of Methodological Tools for Business Analysis of the Effective Company’s Performance by N. S . Plaskova

“…The purpose of the study is to develop methods of analysis and algorithms for calculating the most important characteristics of assessing the performance of economic entities for internal management and external stakeholders based on a complementary approach to the use of classical methods of forming a piece of information and analytical base by clarifying the values of the indicators used in financial and management reporting and supplementing the list of analytical indicators. …”
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Optimization method of time of use electricity price considering losses in distributed photovoltaic access distribution network by Tianshou Li, Qing Xu, Weiwu Li, Xinying Wang, Zhengying Liu

“…And refer to the basic requirements for electricity pricing in the distribution network, set a series of constraints for optimizing electricity prices. Applying an improved imperialist competition algorithm this paper integrates Tent chaotic reverse learning to solve a multi-objective optimization model and obtain an optimized time of use electricity pricing plan. …”
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