An Analytic Policy Gradient-Based Deep Reinforcement Learning Motion Cueing Algorithm for Driving Simulators by Xiaowei Huang, Xuhua Shi, Peiyao Wang, Hongzan Xu, Xiaojun Tang, Gaoran Zhang

“…At higher prediction horizons, the algorithm achieves performance on par with state-of-the-art MPC-based motion cueing algorithms while exhibiting reduced algorithmic delay. …”
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Evaluation of genomic mating approach based on genetic algorithms for long-term selection in Huaxi cattle by Yuanqing Wang, Bo Zhu, Jing Wang, Lupei Zhang, Lingyang Xu, Yan Chen, Zezhao Wang, Huijiang Gao, Junya Li, Xue Gao

“…Our results showed that the GM method could significantly improve the genetic gain while effectively controlling the inbreeding accumulation within the population. …”
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TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning model... by Yutong Wang, Yutong Wang, Yutong Wang, Yutong Wang, Yutong Wang, Ailing Yu, Ailing Yu, Ailing Yu, Ailing Yu, Ailing Yu, Ziping Gao, Ziping Gao, Ziping Gao, Ziping Gao, Xiaoying Yuan, Xiaochen Du, Peng Shi, Haoyun Guan, Shuang Wen, Honglong Wang, Liang Wang, Liang Wang, Liang Wang, Liang Wang, Bo Fan, Bo Fan, Bo Fan, Bo Fan, Zhiyu Liu, Zhiyu Liu, Zhiyu Liu, Zhiyu Liu

“…Comparative evaluation of eight algorithms revealed the GBM model achieved superior discriminative ability for BRFS (AUC for 3-year: 0.752, 4-year: 0.786, 5-year: 0.796). …”
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A High-Speed, Multi-Channel Lossless Compression Algorithm for High-Resolution Video on FPGA by Xingkai Du, Longhua Xie, Hongchuan Huang, Huawei Chen, Xiaolong Guo, Tingyu Zhao

“…The performance of the proposed algorithm is evaluated through on-board FPGA experiments. …”
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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification by Hang Yanping, Zheng Haixia, Yang Minmin, Wang Nan, Kong Miaomiao, Zhao Mingming

“…The algorithm enhances cancer detection while ensuring data privacy. …”
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MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets by Jared Lichtarge, Gerarda Cappuccio, Gerarda Cappuccio, Soumya Pati, Soumya Pati, Alfred Kwabena Dei-Ampeh, Alfred Kwabena Dei-Ampeh, Senghong Sing, Senghong Sing, Senghong Sing, LiHua Ma, Zhandong Liu, Zhandong Liu, Mirjana Maletic-Savatic, Mirjana Maletic-Savatic, Mirjana Maletic-Savatic

“…This method is designed to reduce the dimensionality of large datasets while preserving significant variance. For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.ResultsThe MetaboLINK analysis of longitudinal metabolomics data has revealed distinct pathways related to amino acids, lipids, and energy metabolism, uniquely associated with specific cell progenies. …”
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Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China by Yunjian Liang, Rong Shang, Jing M. Chen, Xudong Lin, Peng Li, Ziyi Yang, Lingyun Fan, Shengwei Xu, Yingzheng Lin, Yao Chen

“…When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.…”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…To solve this problem, this paper combines a deep neural network model with the traditional PhU model and proposes a novel two-stage learning-based phase unwrapping (TLPU) algorithm via multimodel fusion. The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm by Yao Gan, Li Kuang, Xiao-Ming Xu, Ming Ai, Jing-Lan He, Wo Wang, Su Hong, Jian mei Chen, Jun Cao, Qi Zhang

“…Performance of the random forest, multi-level perceptron, and extreme gradient models was acceptable, while the K-nearest neighbor algorithm and support vector machine performed poorly.ConclusionThe detection rate of suicidal and self-injurious behaviors is higher in women than in men. …”
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Energy optimization and plant comfort management in smart greenhouses using the artificial bee colony algorithm by Muhammad Jawad, Fazli Wahid, Sikandar Ali, Yingliang Ma, Ahmed Alkhyyat, Jawad Khan, Youngmoon Lee

“…Additionally, the suggested method was contrasted with other effective algorithms, such as Genetic Algorithm (GA), Firefly Algorithm (FA), and Ant Colony Optimization (ACO). …”
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A Comprehensive Review of Artificial Intelligence-Based Algorithms for Predicting the Remaining Useful Life of Equipment by Weihao Li, Jianhua Chen, Sijuan Chen, Peilin Li, Bing Zhang, Ming Wang, Ming Yang, Jipu Wang, Dejian Zhou, Junsen Yun

“…Central to these methodologies is the accurate prediction of remaining useful life (RUL), which serves as a pivotal cornerstone for effective maintenance and operational decision-making. While significant advancements in computer hardware and artificial intelligence (AI) algorithms have catalyzed substantial progress in AI-based RUL prediction, extant research frequently exhibits a narrow focus on specific algorithms, neglecting a comprehensive and comparative analysis of AI techniques across diverse equipment types and operational scenarios. …”
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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

“…Correspondingly, unique circuits were engineered for each algorithm.To enhance the sensitivity of the sensor while simplifying the circuit's complexity and dimensions, the lm324 Op-Amp was used in the interrupt-based sensor circuit. …”
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Integrated transportation system planning with gravitational search algorithm approach based on fuzzy mutant controller by Alireza Hosseinzadeh Kashani, Seyed Ahmad Shayannia, Mohammad Mehdi Movahedi, Soheila Sardar

“…In functions F1, F2, F15, the best results are observed in the gravitational particle population algorithm, while for functions F13, F14, the best results are observed in the particle population optimizer algorithm, and in F9, the real inheritance algorithm has better performance. …”
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Clustering of ECG Signals Based on Fuzzy Neural Network with Initial Weights Generated by Genetic Algorithm by Elaheh Sayari, Mahdi Yaghoobi

“…In this regard, neural network and fuzzy logic have been used in many application areas while each of them has advantages and disadvantages. …”
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Low-Power Intelligent Wireless Sensor Network for Precision Agriculture Oriented Agricultural Greenhouse Management System by Hongguo Jin

“…When the number of sensor nodes was 100, the improved whale optimization algorithm accounted for only 15% of the routing energy consumption, while the simulated annealing algorithm accounted for 53% of the routing energy consumption. …”
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Solving a low-carbon routing problem for perishable distribution food by Martinson Yeboah Appiah, Sun Huaping

“…The model is solved by using a hybrid genetic algorithm with heuristic rules, after which the algorithm’s efficiency is tested with a globally recognised Proudhon data set. …”
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Elite Evolutionary Discrete Particle Swarm Optimization for Recommendation Systems by Shanxian Lin, Yifei Yang, Yuichi Nagata, Haichuan Yang

“…Traditional deep models are computationally expensive, while heuristic methods like particle swarm optimization struggle with discrete optimization. …”
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Facial recognition optimization based on adversarial sample generation in the field of artificial intelligence by Jie Yang

“…Then, an integrated learning facial adversarial sample generation algorithm based on improved AdaBoost is designed. The results show that the improved AdaBoost algorithm can significantly improve training speed while ensuring algorithm performance, with an average training time of 53 seconds and fewer average weak classifiers. …”
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Impact of an improved random forest-based financial management model on the effectiveness of corporate sustainability decisions by Jianhui Zhang

“…With the development of the economy, more and more electronic manufacturing enterprises are emerging like mushrooms after rain. These enterprises, while developing, also face financial risks caused by various reasons. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…This study proposes a quantum bee colony algorithm based on Boltzmann’s selection and dimensional dynamic update strategy (BDQABC). …”
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