UAV Data Collection Co-Registration: LiDAR and Photogrammetric Surveys for Coastal Monitoring by Carmen Maria Giordano, Valentina Alena Girelli, Alessandro Lambertini, Maria Alessandra Tini, Antonio Zanutta

“…The combination of multiple drone datasets (LiDAR and photogrammetric clouds) is performed via indirect georeferencing, using different executions of the ICP procedure. The ICP algorithm is affected by the differences in the vegetation reconstruction by the two sensors, which may lead to a rotation of the slave cloud. …”
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A low functional redundancy-based network slimming method for accelerating deep neural networks by Zheng Fang, Bo Yin

“…In this research, we propose a low functional redundancy-based network slimming method (LFRNS) that can find and remove functional redundant filters by feature clustering algorithm. However, the redundancy of some key features is beneficial to the model, and removing these features will limit the potential of the model to some extent. …”
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Prospective of climate change impact on water resources and sugar beet yield in the Urmia Lake basin by Somayeh Naderi, Bohloul Alijani, Zahra Hedjazizadeh, Hasan Heidari, Karim Abbaspour

“…Afterward, the output was calibrated (1989-2004) and validated (2005-2014) in the SWAT-CUP software using the SUFI2 algorithm to simulate streamflow of 23 gauging stations and crop yield. …”
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Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

“…Furthermore, a new hybrid loss function, adaptive focal and Dice loss (AFD loss), is introduced through the adaptive AdaLoss algorithm by combining focal loss and Dice loss, improving the model’s ability to handle unbalanced samples. …”
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AdaptiveDet: Defect Detection for Digital Printing Fabric with Complex Background by Zebin Su, Xingyi Zhang, Jiamin Li, Yunlong Shao, Pengfei Li, Huanhuan Zhang

“…First, the initial anchor box was generated using the K-means++ algorithm to better adapt to the complex target shape. …”
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Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting by Hai Tao, Ali Omran Al-Sulttani, Ameen Mohammed Salih Ameen, Zainab Hasan Ali, Nadhir Al-Ansari, Sinan Q. Salih, Reham R. Mostafa

“…The results revealed the potential of the hybridized support vector regression model with a genetic algorithm (SVR-GA) over the other ML forecasting models for monthly river flow forecasting using 90%–10% data division. …”
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Hypergraph-based resource allocation for Device-to-Device underlay H-CRAN network by Pan Zhao, Wenlei Guo, Datong Xu, Zhiliang Jiang, Jie Chai, Lijun Sun, He Li, Weiliang Han

“…Finally, the simulation results show that the proposed scheme improves the throughput performance at least 6% over other algorithms.…”
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Design and Experiment of Electric Uncrewed Transport Vehicle for Solanaceous Vegetables in Greenhouse by Chunsong Guan, Weisong Zhao, Binxing Xu, Zhichao Cui, Yating Yang, Yan Gong

“…A SLAM system based on fusion of LiDAR and inertial navigation ensures precise positioning and navigation with the help of an overall path planner using an A* algorithm and a 3D scanning constructed local virtual environment. …”
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Microscopic stress-constrained two-scale topology optimisation for additive manufacturing by Xiaopeng Zhang, Zheng Ni, Akihiro Takezawa, Yaguang Wang, Zhan Kang

“…The sensitivities of the aggregated stress constraints are derived using the adjoint variable method, and the optimisation problem is solved using a gradient-based mathematical algorithm. Numerical examples illustrate the effect of the stress constraints by comparing the optimisation results with and without microscopic stress constraints. …”
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Novel Optimized Support Vector Regression Networks for Estimating Fresh and Hardened Characteristics of SCC by Babak Naeim, Ali Javadzade Khiavi, Parisa Dolatimehr, Behnam Sadaghat

“…Overall, the HGSO-SVR model beats PSO-SVR, showing the capacity of the algorithm to choose the most effective parameters for the method under examination.…”
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Coordinated Optimization of Multi-Regional Integrated Energy Service Providers with Flexible Reserve Resources by Xueting Wang, Hao Zhong, Xianqiu Zou, Qiujie Wang, Lanfang Li

“…First, for the uncertainty of new energy and load, Latin hypercube sampling is used to generate scenarios, and the scenarios are reduced by a K-means clustering algorithm. Second, based on the interaction relationship between the active distribution network (ADN) and multi-region IESPs, a mixed game model of the ADN and IESP alliance is established. …”
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Sorting Data via a Look-Up-Table Neural Network and Self-Regulating Index by Ying Zhao, Dongli Hu, Dongxia Huang, You Liu, Zitong Yang, Lei Mao, Chao Liu, Fangfang Zhou

“…Learned sorting pioneers a new generation of sorting algorithms and shows a great potential because of a theoretical time complexity ON and easy access to hardware-driven accelerating approaches. …”
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Thermodynamic and economic analysis, optimization of SOFC/GT/SCO2/ORC hybrid power systems for methanol reforming-powered ships with carbon capture by Shouguang Yao, Xuan Yan, Minjie Xia, Chuang Wang, Shaofan Wang

“…Ultimately, a genetic algorithm-based approach was employed to optimize the system's performance through multi-objective optimization, aiming for the best possible outcome. …”
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On the Search for Supersingular Elliptic Curves and Their Applications by Ismel Martinez-Diaz, Rashad Ali, Muhammad Kamran Jamil

“…As our main result, we define for the first time an objective function to measure the supersingularity in ordinary curves, and we apply local search and a genetic algorithm using that function. The study not only finds these supersingular elliptic curves but also investigates possible uses for them. …”
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An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO by Qiaoqiao Xiong, Qipeng Chen, Saihong Tang, Yiting Li

“…Finally, EIoU Loss replaced CIoU Loss to address bounding box aspect ratio variability and sample imbalance challenges, significantly improving overall detection task performance. The algorithm’s performance was evaluated using a dataset to detect stranded elastic needle defects. …”
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Compliance Control of a Cable-Driven Space Manipulator Based on Force–Position Hybrid Drive Mode by Runhui Xiang, Hejie Xu, Xinliang Li, Xiaojun Zhu, Deshan Meng, Wenfu Xu

“…Finally, the feasibility of the proposed algorithm is demonstrated through simulations and compared with the PID control method. …”
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Test Items Validation in the Context of Education Export by I. A. Selivanova, I. Yu. Markovina, I. R. Ilyasov, A. K. Zhevlakova, R. P. Terekhov

“…Valid MSCs (600 items) served as the basis for the creation of extended examination MSQs bank. An algorithm for modeling the “Organic chemistry” MCQs based examination was proposed. …”
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A Particle Swarm Optimization Variant with an Inner Variable Learning Strategy by Guohua Wu, Witold Pedrycz, Manhao Ma, Dishan Qiu, Haifeng Li, Jin Liu

“…The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL) is particularly efficient for optimizing functions with symmetric variables. …”
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DCE-MRI and DWI Integration for Breast Lesions Assessment and Heterogeneity Quantification by C. Andrés Méndez, Francesca Pizzorni Ferrarese, Paul Summers, Giuseppe Petralia, Gloria Menegaz

“…The distributions of the diffusion parameter values in subregions identified by the algorithm are extracted and compared through nonparametric testing for posterior evaluation of the tissue heterogeneity. …”
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Parametric Evaluation of Simultaneous Effects of Damaged Zone Parameters and Rock Strength Properties on GRC by Ali Ghorbani, Hadi Hasanzadehshooiili, Amin Eslami

“…Besides, effects of intermediate principal stress and the exponential decaying dilation parameter are taken into account thanks to adoption of the unified strength criterion (USC) as the material strength criteria. To do so, genetic algorithm (GA) via the method of evolutionary polynomial regression (EPR) is used to find a relationship between a number of 19 affecting parameters on the GRC as the input, and the internal support pressure as the target of prediction. …”
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