The impact of quantum circuit architecture and hyperparameters on variational quantum algorithms exemplified in the electronic structure of the GaAs crystal by Ivana Miháliková, Michal Krejčí, Martin Friák

“…We observed that while both algorithms offer promising results, the choice of ansatz and hyperparameter tuning were especially critical in achieving reliable outcomes, particularly for higher energy states. …”
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Reliability-Based Geotechnical Design Method Using the Gaussian Process Regression–Based Differential Evolution Algorithm by Kai Wen, Zemin Kuang, Wei Zeng, Sanyou Zeng, Yue Qiu

“…A fundamental challenge in reliability-based geotechnical design is optimizing cost-effectiveness while adhering to a predefined failure probability target. …”
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A greedy approach to solve maximum independent set problem: Differential Malatya independent set algorithm by Furkan Öztemiz

“…The analysis results showed that DMISA produced optimal results in lattice, bipartite, and complete multipartite graphs, while it produced generally non-optimal results for randomly generated and social graphs. …”
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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

“…The contribution in this paper proposes the following: the radial basis function (RBF) model will be enhanced by using two optimization algorithms, namely Horse Herd Optimization (HHO) and Wild Geese Algorithm (WGA). …”
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Development of a machine learning algorithm for geometric compensation of Single Point Incremental Forming (SPIF) process by Gralha Margarida F., Magrinho João P. G., Sousa João M. C., Silva M. Beatriz

“…This study outlines the development of a machine learning algorithm designed to generate optimized CAD geometries, minimizing geometric deviations in SPIF-formed components. …”
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A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…The FCM captures expert knowledge through causal relationships between symptoms, treatments, and diagnoses, while the GA optimizes treatment actions to achieve desired health outcomes. …”
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A Cooperative Decision-Making and Control Algorithm for UAV Formation Based on Non-Cooperative Game Theory by Yongkang Jiao, Wenxing Fu, Xinying Cao, Kunhu Kou, Ji Tang, Rusong Shen, Yiyang Zhang, Haibo Du

“…By utilizing the theoretical foundations of non-cooperative game theory, a novel control strategy is introduced, which allows UAVs to autonomously determine the optimal flight trajectory without relying on centralized coordination while concurrently mitigating conflicts with other UAVs. …”
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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…Experimental results demonstrate that compared with classical UNet, the optimized network achieves 2.05% and 2.58% improvements in F1-Score and IoU, respectively, while reducing the parameter count to 57.25% of the original model. …”
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Multi-layer obstacle-avoiding rectilinear steiner minimal tree algorithm based on deep reinforcement learning by Xing Huang, Yuhan Zhu, Yanbo Xu, Yajun Xie, Genggeng Liu

“…Finally, a post-processing stage is applied to further shorten the total wirelength through fast pruning and local optimization. Experimental results demonstrate that the proposed algorithm achieves better wirelength quality compared to state-of-the-art heuristic algorithms. …”
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Forecasting Wind Farm Production in the Short, Medium, and Long Terms Using Various Machine Learning Algorithms by Gökhan Ekinci, Harun Kemal Ozturk

“…The results indicate that Min-Max Scaling improved short-term predictions with KNN, while XGBoost and Random Forest provided more stable and accurate forecasts in medium- and long-term predictions. …”
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Enhanced Harmony Search Algorithm for Maximum Power Point Tracking Under Partial Shading in PV Systems by Geon Hee Lee, Zong Woo Geem, Jehyuk Won

“…The results show that the proposed algorithm outperforms conventional HS and particle swarm optimization algorithms in terms of the number of iterations and convergence time, while maintaining a similar level of accuracy.…”
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Comparative Analysis of A3C and PPO Algorithms in Reinforcement Learning: A Survey on General Environments by Alberto del Rio, David Jimenez, Javier Serrano

“…This research article presents a comparison between two mainstream Deep Reinforcement Learning (DRL) algorithms, Asynchronous Advantage Actor-Critic (A3C) and Proximal Policy Optimization (PPO), in the context of two diverse environments: CartPole and Lunar Lander. …”
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Combining Smartphone Inertial Sensors and Machine Learning Algorithms to Estimate Power Variables in Standing Long Jump by Beatrice De Lazzari, Giuseppe Vannozzi, Valentina Camomilla

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Singular Value Decomposition (SVD) Method for LiDAR and Camera Sensor Fusion and Pattern Matching Algorithm by Kaiqiao Tian, Meiqi Song, Ka C. Cheok, Micho Radovnikovich, Kazuyuki Kobayashi, Changqing Cai

“…Unlike traditional calibration methods that require manual targets, our approach is targetless, extracting matched patterns from projected LiDAR point clouds and 2D image segments. The algorithm computes the optimal transformation matrix between sensors, correcting misalignments in rotation, translation, and scale. …”
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Connectivity-Enhanced 3D Deployment Algorithm for Multiple UAVs in Space–Air–Ground Integrated Network by Shaoxiong Guo, Li Zhou, Shijie Liang, Kuo Cao, Zhiqun Song

“…Finally, a height optimization algorithm is proposed to adjust the height of each UAV, completing the 3D deployment of multiple UAVs. …”
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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…After a series of improvements, LBT-YOLO outperforms YOLOv8n and other detection algorithms on the Autonomous Driving BDD100K dataset, with an average accuracy improvement of 2.4% while reducing the number of model parameters by 48.2%.…”
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Improved Aerial Surface Floating Object Detection and Classification Recognition Algorithm Based on YOLOv8n by Lili Song, Haixin Deng, Jianfeng Han, Xiongwei Gao

“…To address the aforementioned challenges, we proposed an improved YOLOv8-HSH algorithm based on YOLOv8n. The proposed algorithm introduces several key enhancements: (1) an enhanced HorBlock module to facilitate multi-gradient and multi-scale superposition, thereby intensifying critical floating object characteristics; (2) an optimized CBAM attention mechanism to mitigate background noise interference and substantially elevate detection accuracy; (3) the incorporation of a minor target recognition layer to augment the model’s capacity to discern floating objects of differing dimensions across various environments; and (4) the implementation of the WIoU loss function to enhance the model’s convergence rate and regression accuracy. …”
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Precision forecasting for hybrid energy systems using five deep learning algorithms for meteorological parameter prediction by Ceren Ceylan, Zehra Yumurtacı

“…Using five years of Istanbul meteorological data (2018–2022), optimal algorithms were systematically identified for each parameter through rigorous hyperparameter optimization and cross-validation. …”
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Evaluation of Thermal Damage Effect of Forest Fire Based on Multispectral Camera Combined with Dual Annealing Algorithm by Pan Pei, Xiaojian Hao, Ziqi Wu, Rui Jia, Shenxiang Feng, Tong Wei, Wenxiang You, Chenyang Xu, Xining Wang, Yuqian Dong

“…This study introduces an innovative approach combining multispectral imaging with a dual annealing constrained optimization algorithm to enable dynamic monitoring of fire temperature distribution. …”
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Synergetic simplified super-twisting algorithm control for stability enhancement of PV/BESS-based DC microgrid by Naamane Debdouche, Ali Chebabhi, Habib Benbouhenni, Fatma-Zohra Hadjaidji, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…It ensures the desired voltage level at the common DC bus while tailoring energy allocation to meet load requirements. …”
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