Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture by A. V. Kamenskiy, T. M. Akaeva, D. A. Grebenshchikova

“…In order to evaluate the performance of the filter, a comparison of the developed algorithm with the classical two-dimensional convolution algorithm was carried out. …”
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Evaluación de algoritmos para la estimación del Round-Trip Delay Time y una propuesta de mejora by M. Daniel Docmac, Eduardo I. Silva, Agustín J. González

“…There are no works considering a quantitative evaluation metric, comparing the performance achieved by different algorithms. …”
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A data-efficient deep transfer learning framework for methane super-emitter detection in oil and gas fields using the Sentinel-2 satellite by S. Zhao, S. Zhao, Y. Zhang, Y. Zhang, S. Zhao, S. Zhao, X. Wang, X. Wang, D. J. Varon

“…We evaluate the ability of the algorithm to discover new methane sources with a suite of transfer tasks, in which training and evaluation data come from different regions. …”
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Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images. by Ulas Bagci, Jianhua Yao, Kirsten Miller-Jaster, Xinjian Chen, Daniel J Mollura

“…Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

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CTA image segmentation method for intracranial aneurysms based on MGLIA net by Lijie Hou, Jian Zhang, Lihui Zhao, Ke Meng, Xin Feng

“…In response to this issue, this article proposes a more universal segmentation model and develops the GLIA Net algorithm (MGLIA Net model) based on MoblieNet, which can perform adaptive target segmentation on aneurysm images collected under different conditions. …”
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A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…Each method has its own advantages and disadvantages under specific site conditions. To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
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Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

“…The efficiency of the proposed algorithm is evaluated using the challenging benchmark functions from various CEC competitions. …”
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Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

“…Further, an objective function is formulated to achieve the optimal solution for power transmitted by the source and an adaptive particle swarm optimization (OPA-APSO) algorithm is proposed to attain maximized energy efficiency. …”
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Bi-Objective Optimization of Techno-Economic and Environmental Performance for Membrane-Based CO₂ Capture via Single-Stage Membrane Separation by Nobuo Hara, Satoshi Taniguchi, Takehiro Yamaki, Thuy T. H. Nguyen, Sho Kataoka

“…Bi-objective optimization was performed using an original algorithm that combines the adaptive design of experiments, machine learning, a genetic algorithm, and Bayesian optimization. …”
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Uncertainty quantification of CT regularized reconstruction within the Bayesian framework by Negin Khoeiniha, Patricio Guerrero, Wim Dewulf

“…Additionally, we aim to utilize computationally feasible sampling techniques to analyze the distribution of the solution, enabling an in-depth evaluation of the results. To achieve these goals, we apply a rapid regularized Markov Chain Monte Carlo (MCMC) reconstruction method [4, 5], employing the Metropolis-Adjusted Langevin Algorithm (MALA) [6] and its Lipschitz-adaptive variant (LipMALA) [7]. …”
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Robust Optical and SAR Image Registration Using Weighted Feature Fusion by Ao Luo, Anxi Yu, Yongsheng Zhang, Wenhao Tong, Huatao Yu

“…To verify the effectiveness of the method, different optical and SAR datasets are used to compare it with the currently advanced algorithms MOGF, CFOG, and FED-HOPC. …”
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Theoretical analysis of power control and energy efficiency in full-duplex massive MIMO systems by Kwame Salum Ibwe, Libe Valentine Massawe

“…Numerical results evaluate the system’s performance across different interference levels, antenna configurations, and distances, highlighting the role of adaptive SI mitigation. …”
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State information-driven surrogate-assisted differential evolution for computationally expensive constrained optimization problems by Zihua Zhu, Zan Yang, Zhiyong Liu, Liming Chen, Xiwen Cai

“…Abstract In this paper, a state information-driven surrogate-assisted differential evolution called SI-SADE is proposed for solving expensive constrained optimization problems, in which both the population state and adaptive search mechanism are respectively evaluated and designed based on the feasibility and state information. …”
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Growing Correspondence Seeds for Efficient and Accurate Satellite DSM Extraction by Amin Sedaghat, Nazila Mohammadi

“…The main property of the Sat-GCS method is the generation of a set of precise and dense tie-points in stage (2), used as initial correspondence seeds to improve the GCS algorithm in stage (4). The proposed method is evaluated on 12 different datasets from four different satellite sensors including ZY3-01, CartoSat-1, ZY3-02, and Worldview-3, and the results are compared with the CATALYST, SAT-MVSF, and SS-DSM methods. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Thus, scientifically assessing and predicting geological disasters and formulating disaster prevention and mitigation policies are of critical importance for promoting regional sustainable development. However, current evaluations of geological disasters often overlook the adaptive capacity of the disaster-bearing body and focus primarily on cross-sectional comparisons across different regions at specific time points, with insufficient attention to spatiotemporal dynamics. …”
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Investigating the impact of fatty acid profiles on biodiesel lubricity using artificial intelligence techniques by Atthaphon Maneedaeng, Attasit Wiangkham, Atthaphon Ariyarit, Anupap Pumpuang, Ekarong Sukjit

“…To further analyze the impact of fatty acid composition on lubricity, an artificial intelligence (AI)-based approach using the Adaptive Boosting (AdaBoost) algorithm was implemented. …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…However, the difference was slight. Since the output of the multi-objective algorithm was a Pareto solution set, four indices, uniformity, convergence, diversity, and dominance, were selected to evaluate the distribution in the solution space and to compare the solution results of each algorithm. …”
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Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

“…The results show that QIO-RPIDD2 achieves superior performance, adapts quickly to different reference temperatures and performs excellently on key performance indicators. …”
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Full Information Numerical Simulation of Two-Dimensional Steady Ground Temperature Field by Fan Jiang, Shikun Dai, Ying Zhang, Hongjun Tian

“…The equations under different wavenumbers are independent of each other and highly parallel, while retaining vertical spatial domain, with strict upper and lower boundary conditions, which can adapt to the needs of complex terrain simulation. …”
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