Evaluating Empirical Dynamic Modeling for forecasting: The role of variation among time series replicates by Fleur Slegers, Robbin Bastiaansen, Edwin Pos

“…In this study, we use simulated data from the Lorenz-63 system, a three-species food chain, and a four-species Lotka–Volterra model of competition to evaluate the performance of EDM’s S-Map algorithm across various scenarios, employing three different approaches to generate time series replicates, each with a different type of variation between the replicates: varying initial conditions (Scenario A), sampling distinct sections of the attractor (Scenario B), and varying the system’s parameter controlling chaotic behavior (Scenario C). …”
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Mixed Multi-Strategy Improved Aquila Optimizer and Its Application in Path Planning by Tianyue Bao, Jiaxin Zhao, Yanchang Liu, Xusheng Guo, Tianshuo Chen

“…Key enhancements include the integration of Bernoulli chaotic mapping to improve initial population diversity, a spiral stepping strategy to boost search precision and diversity, and a “stealing” mechanism from the Dung Beetle Optimization algorithm to enhance global search capabilities and convergence. …”
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A Survey on the Key Technologies of UAV Motion Planning by Yuquan Zhou, Li Yan, Yaxi Han, Hong Xie, Yinghao Zhao

“…Motion planning, a cornerstone of UAV autonomous navigation, has garnered extensive attention, with numerous advanced algorithms having been proposed in recent years. This paper provides a comprehensive overview of UAV motion planning frameworks, systematically addressing three key components: map representation, path planning, and trajectory optimization. …”
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Plot-Rice v1.0: A global plot-based rice benchmark dataset with spatiotemporal heterogeneity for scientific deep learning by Ji Ge, Hong Zhang, Wenjiang Huang, Zihuan Guo, Lu Xu, Yazhe Xie, Mingyang Song, Yinhaibin Ding, Chao Wang

“…The absence of a global, standardized satellite dataset for rice mapping benchmarking has long resulted in both substantial redundant data processing efforts and challenges in evaluating new algorithms under a unified benchmark. …”
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Extraction and analysis of aerosol anomalies associated with multiple shallow earthquakes based on MODIS AOD products by Ping Lu, Xiao Gao, Zhixuan Xiong, Yu Shang

“…By employing buffer zones of 0.5°, 1°, and 2°, we isolated pre- and post-seismic AOD anomalies across diverse tectonic settings. The results suggest that a 1° buffer is the optimal spatial window for most earthquake cases. …”
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Orchard variable-rate spraying method integrating GNSS and wind-excited audio-conducted leaf area density by Hangxing Zhao, Hangxing Zhao, Hangxing Zhao, Shenghui Yang, Shenghui Yang, Shenghui Yang, Wenwei Li, Wenwei Li, Han Feng, Han Feng, Shijie Jiang, Shijie Jiang, Weihong Liu, Weihong Liu, Jingbin Li, Yongjun Zheng, Yongjun Zheng, Songchao Zhang

“…A variable-rate spray control model and algorithm were then constructed to regulate spray flow according to the spatial distribution of leaf area density across the orchard.ResultsField experiments demonstrated that the system achieved a mean relative error of only 5.52% in spray flow rate regulation. …”
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Acute Respiratory Infections Identification With Cough Sounds and Overlapping Patch Modulated Vision Transformers by P. V. V. Kishore, D. Anil Kumar, Pasupuleti Sasikiran, Kaja Krishna Mohan, P. Praveen Kumar, Mogadala Vinod Kumar

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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

“…Experimental evaluations across three motion tasks—level walking, stair ascent, and stair descent—demonstrated that the proposed method achieved a minimum root mean square error (RMSE) of 1.31°, with over 50% reduction in feature dimensionality, significantly outperforming Genetic Algorithm (GA), Zebra Optimization Algorithm (ZOA), Liver Cancer Algorithm (LCA), and Pied Kingfisher Optimizer (PKO). …”
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Visceral obesity anthropometric indicators as predictors of acute pancreatitis severity by Kaier Gu, Wenxuan Shang, Dingzhou Wang

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Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…IntroductionParkinson’s disease (PD) heterogeneity poses challenges to the current development of discovering the best therapeutic targets.MethodsHere, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …”
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Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

“…The experimental results show that the algorithm excels at solving the MOAEOSSP, outperforming competing algorithms across several metrics and demonstrating its effectiveness for complex optimization problems.…”
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Inversion of multiphase tectonic stress field and fracture evolution in shale gas reservoirs by WANG Jiawei, ZHANG Bohu, HU Yao, HE Zhengyi, HU Xinxin, CHEN Wei, LUO Chao

“…The research indicates that numerical simulation methods and neural network algorithms effectively invert the crustal stress field across multiple stages. …”
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Beyond the Current Curve: A Novel Curve Warning System Considering Subsequent Curve Speed Limits by N. S. Manikandan, Ganesan Kaliyaperumal

“…We evaluate the existing path-tracking algorithms across various speed scenarios (50, 70, and 80 km/h) and different speed considerations: curve-aware speed and our proposed adjacent curve-speed-limit-aware speed. …”
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Integrating infiltration processes in hybrid downscaling methods to estimate sub-surface soil moisture by Mo Zhang, Yong Ge, Jianghao Wang

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Bio-Inspired Metaheuristics in Deep Learning for Brain Tumor Segmentation: A Decade of Advances and Future Directions by Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana, Wahyu Caesarendra, Nurul Huda

“…Through bibliometric mapping, methodological synthesis, and performance analysis, we highlight trends in algorithm usage, application domains (e.g., preprocessing, architecture search), and segmentation outcomes measured by metrics such as Dice Similarity Coefficient (DSC), Jaccard Index (JI), Hausdorff Distance (HD), and ASSD. …”
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Riparian habitat quality and seasonality drives spatiotemporal habitat ecology of sympatric Asian otters in southern Western Ghats by Ankit Moun, Tharmalingam Ramesh, Tharmalingam Ramesh, Riddhika Kalle, Riddhika Kalle

“…In dynamic ecosystems, we have scant knowledge on the interactive role of season and local riparian habitat conditions in driving spatiotemporal habitat use of sympatric semi-aquatic mustelids.MethodologyWe conducted seasonal monitoring of 169-196 riverine segments (250 m) in 2020 and 2021 to measure the sign encounter rates of Asian small-clawed otter (SCL) and smooth-coated otter (SCO) and recorded 29 riparian habitat variables.ResultsOur self-organizing map algorithm characterized alarge multivariate habitat data into six habitat clusters representing a gradient of riparian habitat conditions. …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…The exponential growth of big data in recent years has positioned artificial intelligence as a focal point of inquiry across various fields. Machine learning has catalyzed substantial advancements in the field of data science. …”
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Enhancing gender equity in resume job matching via debiasing-assisted deep generative model and gender-weighted sampling by Swati Tyagi, Anuj, Wei Qian, Jiaheng Xie, Rick Andrews

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A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting by Jing Liu, Qingling He, Zhikun Yue, Yulong Pei

“…First, we replace the random initialization method of the population in the SSA with Circle mapping to enhance its diversity and quality. Second, we introduce a hybrid mechanism combining dimensional small-hole imaging backward learning and Cauchy mutation, which improves the diversity of the individual sparrow selection of optimal positions and helps overcome the algorithm’s tendency to become trapped in local optima and premature convergence. …”
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Five-Year Evaluation of Sentinel-2 Cloud-Free Mosaic Generation Under Varied Cloud Cover Conditions in Hawai’i by Francisco Rodríguez-Puerta, Ryan L. Perroy, Carlos Barrera, Jonathan P. Price, Borja García-Pascual

“…We conducted a comparative analysis of three cloud-masking methods: two Google Earth Engine algorithms (CloudScore+ and s2cloudless) and a new proprietary deep learning-based algorithm (L3) applied to Sentinel-2 imagery. …”
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