A Hybrid Model for Prediction in Asphalt Pavement Performance Based on Support Vector Machine and Grey Relation Analysis by Xuancang Wang, Jing Zhao, Qiqi Li, Naren Fang, Peicheng Wang, Longting Ding, Shanqiang Li

“…Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. …”
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Rapid Discrimination of Cheese Products Based on Probabilistic Neural Network and Raman Spectroscopy by Zheng-Yong Zhang

“…Therefore, an approach of cheese product brand discrimination method based on Raman spectroscopy and probabilistic neural network algorithm was developed. The experimental results show that the spectrum contains abundant molecular vibration information of carbohydrates, fats, proteins, and other components, and the Raman spectral data collection time of a single sample is only 100 s. …”
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Mathematical Development and Evaluation of Forecasting Models for Accuracy of Inflation in Developing Countries: A Case of Vietnam by Nhu-Ty Nguyen, Thanh-Tuyen Tran

“…In this study, both clarified value calculation and use of a genetic algorithm to find the optimal parameters are adopted simultaneously to construct improved models: ARIMA, GM(1,1), Verhulst, DGM(1,1), and DGM(2,1) by using data of Vietnamese inflation output from January 2005 to November 2013. …”
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Probe Selection and Power Weighting in Multiprobe OTA Testing: A Neural Network-Based Approach by Yong Li, Hao Sun, Xingyu Chen, Lijian Xin, Xiang Zhang

“…., the well-known multishot algorithm, the proposed NN-based approach can yield similar channel emulation accuracy with significantly reduced computational complexity.…”
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A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds by Ming Wei, Binbin Jing, Jian Yin, Yang Zang

“…Since this task is an NP-hard problem, a heuristic-based nondominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto optimal solutions in a reasonable amount of time. …”
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Effective Lock Detectors Based on Costas Loop Output for SBPSK Mobile Communications by D. Ferramola, T. Casilli, S. Pradella, G. Giunta, D. Orlando

“…Such estimates are obtained through an iterative strategy relying on the Expectation Maximization algorithm. Moreover, when possible, we provide exact statistical characterizations of the considered decision schemes (including the competitors) or, in the other case, suitable approximations that allow for a straightforward performance evaluation. …”
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FSPPCFs: a privacy-preserving collaborative filtering recommendation scheme based on fuzzy C-means and Shapley value by Weiwei Wang, Wenping Ma, Kun Yan

“…Specifically, (i) we have modified the traditional recommendation scheme by introducing a similarity balance factor integrated into the Pearson similarity algorithm, enhancing recommendation system performance; (ii) FSPPCFs first clusters the dataset through fuzzy C-means clustering and Shapley value, grouping users with similar interests and attributes into the same cluster, thereby providing more accurate data support for recommendations. …”
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Early Warning and Management Method of Abnormal Performance of Tourist Scenic Spots Assisted by Image Recognition Technology by Zhaozhen Song, Jing Lu

“…In this study, the collaborative filtering algorithm can be used to complete the active recommendation of abnormal performance of tourist scenic spots. …”
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An OFDM Signal Enhancement and Demodulation Method Based on Segmented Asymmetric Bistable Stochastic Resonance by Gaohui Liu, Xiaqiang Chu

“…The quantum particle swarm optimization algorithm is employed to fine-tune system parameters. …”
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Variable-Time-Domain Online Neighboring Optimal Trajectory Modification for Hypersonic Interceptors by Ningbo Li, Humin Lei, Jin Zhou, Lei Shao, Bin Wang

“…In this paper, an online trajectory generation algorithm is designed based on neighboring optimal control (NOC) theory and improved indirect Radau pseudospectral method (IRPM). …”
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Optimization of Identification and Zoning Method for Landscape Characters of Urban Historic Districts by Hong YUN, Zixuan HU, Zehao HU

“…Then the research utilizes K-means clustering algorithm to optimize the zoning method for historic landscape characters. …”
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Use of Open Claims vs Closed Claims in Health Outcomes Research by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser, Fatih Mete

“…**Methods:** We identified 18 different diseases using 2022 data from 2 closed claims data sets (MarketScan® and PharMetrics® Plus) and 1 open claims database (Kythera). After applying an algorithm that removes possible duplications from open claims data, we compared healthcare utilizations such as inpatient, emergency department, and outpatient use and length of stay among these 3 data sets. …”
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<i>Сlostridium difficile</i> Infection in a COVID-19 Patient by A. A. Timofeeva, Yu. O. Shulpekova, V. M. Nechaev, M. R. Skhirtladze

“…The opportunistic bacterial infection of C. difficile often proceeds undetected due to its potential mirroring of COVID-19 presentation. A screening algorithm in COVID-19 patients with diarrhoea should imply steps for C. difficile detection.…”
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Learning from Large-Scale Wearable Device Data for Predicting the Epidemic Trend of COVID-19 by Guokang Zhu, Jia Li, Zi Meng, Yi Yu, Yanan Li, Xiao Tang, Yuling Dong, Guangxin Sun, Rui Zhou, Hui Wang, Kongqiao Wang, Wang Huang

“…In addition to a physiological anomaly detection algorithm defined based on data from wearable devices, an online neural network prediction modelling methodology combining both detected physiological anomaly rate and historical COVID-19 infection rate is explored. …”
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Clinical observation of VR virtual reality rehabilitation training combined with acupuncture in the treatment of mild cognitive impairment by Ying Fu, Hui Wang

“…This paper then establishes the algorithm model of the VR virtual reality rehabilitation training system, which lays a solid foundation for the design of the subsequent rehabilitation training system. …”
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Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data by Mirjam Sophia Glessmer, Rachel Forsyth

“…In some instances, interpretations and extrapolations of data happened when it was clearly stated in the prompt that the tool should only analyse a specified dataset based on explicit instructions. Since both algorithm and training data of the GenAI tools are undisclosed, it is impossible to know how the outputs had been arrived at. …”
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A New Health Condition Detection Method for Planetary Gears Based on Modified Distributed Compressed Sensing and Multiscale Symbol Dynamic Entropy by Zhe Wu, Qiang Zhang, Zeyu Ma, Jialong Lu, Zhiying Qin

“…A distributed compression sensing parameter optimization algorithm based on Rényi entropy is proposed, which uses improved distributed compression sensing technology to simultaneously sample, compress, and denoise the multisource vibration data of rotating machinery. …”
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Advanced Approach of Multiagent Based Buoy Communication by Gediminas Gricius, Darius Drungilas, Arunas Andziulis, Dale Dzemydiene, Miroslav Voznak, Mindaugas Kurmis, Sergej Jakovlev

“…The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. This combined approach was validated on an automotive dataset predicting CO2 emissions from vehicle sensor measurements such as mass air flow, intake pressure, temperature, and speed. …”
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Teaching-Learning-Based Optimization with Learning Enthusiasm Mechanism and Its Application in Chemical Engineering by Xu Chen, Bin Xu, Kunjie Yu, Wenli Du

“…Teaching-learning-based optimization (TLBO) is a population-based metaheuristic search algorithm inspired by the teaching and learning process in a classroom. …”
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