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  1. 11481

    Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

    Published 2024-12-01
    “…After the chemometrics related to hyperspectral imaging had been examined, the least square-support vector regression models based on the feature bands, which were selected by the shuffled frog leaping algorithm, showed the best performance, and the determination coefficients of prediction (R2P) for cherry sugar content and acidity reached 0.976 and 0.906, respectively. …”
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  2. 11482

    Machine-Learning-Based Optimal Feed Rate Determination in Machining: Integrating GA-Calibrated Cutting Force Modeling and Vibration Analysis by Yu-Peng Yeh, Han-Hao Tsai, Jen-Yuan Chang

    Published 2025-06-01
    “…Surface quality evaluations showed that the model-predicted feed rates consistently resulted in better surface finish and reduced chatter effects compared to conventional settings. …”
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  3. 11483

    “Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

    Published 2025-01-01
    “…This study employs the K-means clustering algorithm to partition warm-season precipitation in Zhejiang Province into distinct regions. …”
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  4. 11484

    Utilising AI technique to identify depression risk among doctoral students by Changhong Teng, Chunmei Yang, Qiushi Liu

    Published 2024-12-01
    “…Based on the data from the 2019 Nature Global Doctoral Student Survey, we first screened 13 highly relevant features from a total of 37 features potentially related to the risk of depression among doctoral students by Random Forest algorithm. Subsequently, we trained the optimal prediction model to predict the doctoral students with depression risk using a Multilayer Perceptron (MLP), achieving an accuracy of 89.09% on the test set. …”
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  5. 11485

    3D conformation and crystal interaction insights into drug development challenges for HCV drug analogues via molecular simulations by Richard S. Hong, Alessandra Mattei, Mark E. Tuckerman, Ahmad Y. Sheikh

    Published 2025-08-01
    “…In this article, we demonstrate how a suite of molecular simulation approaches, including crystal structure prediction augmented with a new hydrate CSP algorithm, free-energy perturbation, molecular dynamics (MD) based solubility predictions, and topological assessment to evaluate surface re-crystallization tendencies, provide key atomistic-level insights into the differentiated performance of the two analogs. …”
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  6. 11486

    Artificial Intelligence in Numerical Modeling of Silver Nanoparticles Prepared in Montmorillonite Interlayer Space by Parvaneh Shabanzadeh, Norazak Senu, Kamyar Shameli, Maryam Mohaghegh Tabar

    Published 2013-01-01
    “…In this investigation, the accuracy of artificial neural network training algorithm was applied in studying the effects of different parameters on the particles, including the AgNO3 concentration, reaction temperature, UV-visible wavelength, and montmorillonite (MMT) d-spacing on the prediction of size of silver nanoparticles. …”
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  7. 11487

    Adaptive Panoramic Video Multicast Streaming with Limited FoV Feedback by Jie Li, Ling Han, Cong Zhang, Qiyue Li, Weitao Li

    Published 2020-01-01
    “…Then, we design a QoE-driven panoramic video streaming system with a client/server (C/S) architecture, in which the server performs rate adaptation based on the bandwidth and the predicted FoV. We then formulate it as a nonlinear integer programming (NLP) problem and propose an optimal algorithm that combines the Karush–Kuhn–Tucker (KKT) conditions with the branch-and-bound method to solve this problem. …”
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  8. 11488

    Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand by Liu He, Tangyi Guo, Kun Tang

    Published 2020-01-01
    “…A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). …”
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  9. 11489

    CONSUMER PREFERENCE RESEARCH IN FORMING RATIONAL COMPONENT OF REGIONAL BRANDS IN THE MEAT PRODUCT MARKET by Mel'nikova E.I., Ponomareva N.V., Bogdanova E.V.

    Published 2017-03-01
    “…The research results confirm that the obtained neural network predicts the main characteristics of normalized mixes with α-lactoglobulin hydrolysate almost accurately; the relative error does not exceed 2.6% when predicting α-lactoglobulin content, 3.9% when predicting residual antigenicity and 3.1% when predicting titratable acidity and organoleptic characteristics. …”
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  10. 11490

    Image Processing Method Based on Chaotic Encryption and Wavelet Transform for Planar Design by Yiying Liu, Young Chun Ko

    Published 2021-01-01
    “…The plaintext image is decomposed in odd-even sequence using the boosting algorithm to get the sequence with an even index and the sequence with an odd index; then, the diffusion algorithm is applied to the two sequences by the prediction and update algorithm, and this process is repeated many times to get the two ciphertext sequences after scrambling, merging these two sequences, and matrixing them to get the ciphertext image. …”
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  11. 11491

    Rapid and simultaneous determination of mixed pesticide residues in apple using SERS coupled with multivariate analysis by Ting-feng Shi, Ting-tiao Pan, Ping Lu

    Published 2024-12-01
    “…This study aims to apply multivariate analysis algorithms for modeling the same spectra, for simultaneous determination of pymetrozine and carbendazim residues in apple. …”
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  12. 11492

    Hydrodynamic coefficients identification of ship simplified modular model based on support vector regression by Lifei SONG, Yuqing WANG, Wei PENG, Peiyong LI, Yushan LIu, Yongfeng ZHANG

    Published 2025-02-01
    “…The calculated values of root mean square error (RMSE) and correlation coefficient (CC) fall within a favorable range. ConclusionsThe SVR algorithm successfully identifies the hydrodynamic derivatives of the modular model, the identified hydrodynamic coefficients exhibit high accuracy, and the established model demonstrates good predictive capability and robustness.…”
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  13. 11493

    Indirect Determination Approach of Blast-Induced Ground Vibration Based on a Hybrid SSA-Optimized GP-Based Technique by Zhaoxin Jiang, Hongyan Xu, Hui Chen, Bei Gao, Shijie Jia, Zhi Yu, Jian Zhou

    Published 2021-01-01
    “…Then, an ANN model, an SVR model, a GP model, an SSA-GP model, and three empirical models were established, and the predictive performance was evaluated by using the root-mean-square error (RMSE), determination coefficient (R2), value account for (VAF), Akaike Information Criterion (AIC), Schwarz Bayesian Criterion (SBC), and the run time. …”
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  14. 11494

    Estimating Import Lead Times Using Business Intelligence and Machine Learning Within the CRISP-DM Framework: A Case Study in Oil and Gas Services Industry by Mohamed Annis Souames, Larbi Abderrahmane Mohammedi, Iskander Zouaghi, Angappa Gunasekaran, Samia Beldjoudi, Abderrazak Laghouag

    Published 2025-01-01
    “…Addressing the challenge of limited data availability, we employ data synthesis techniques alongside machine learning algorithms to model and predict lead times accurately across diverse import scenarios. …”
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  15. 11495

    QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors by Auwal Isa, Adamu Uzairu, umar Umar, Muhammad Tukur Ibrahim, Abdullahi Umar

    Published 2024-04-01
    “…A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts chemical activity (pGI50) against breast cancer receptors. …”
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  16. 11496

    Autonomous Aircraft Tactical Pop-Up Attack Using Imitation and Generative Learning by Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama

    Published 2025-01-01
    “…By applying imitation learning techniques and comparing three algorithms – Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) – the research trains models to predict aircraft control inputs through sequences of state-action pairs. …”
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  17. 11497

    Infra-Red Imaging to Detect Respirator Leak in Healthcare Workers During Fit-Testing Clinic by Darius Chapman, Campbell Strong, Kathryn D Tiver, Dhani Dharmaprani, Even Jenkins, Anand N Ganesan

    Published 2024-01-01
    “…Results: The study achieved high accuracy in predicting pass or fail outcomes of quantitative fit tests for flat-fold P2 FFRs. …”
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  18. 11498

    A Novel ANN-PSO Method for Optimizing a Small-Signal Equivalent Model of a Dual-Field-Plate GaN HEMT by Haowen Shen, Wenyong Zhou, Jinye Wang, Hangjiang Jin, Yifan Wu, Junchao Wang, Jun Liu

    Published 2024-11-01
    “…We initially train an ANN model to predict the S-parameters of the device, and subsequently utilize the PSO algorithm for parameter optimization. …”
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  19. 11499

    Early Warning of Nerve Agent Release in Large Indoor Environments Based on Encoder-Decoder Coupling Physics-Informed Neural Network by Shuobei Sun, Yang Peng, An Wang, Yiwen Xie, Yang Hu, Zhongyu Hou

    Published 2025-01-01
    “…Extensive experiments are conducted, and the results indicate that our model attains the highest performance among all the algorithms proposed in this paper. The difference between the actual and predicted results is small, and the scatter points are distributed around the fitted curves. …”
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  20. 11500

    Multimodal AI diagnostic system for neuromyelitis optica based on ultrawide-field fundus photography by Simin Gu, Tiancheng Bao, Tao Wang, Qiting Yuan, Weiguang Yu, Jiayi Lin, Haocheng Zhu, Shihai Cui, Yi Sun, Xiuhua Jia, Lina Huang, Shiqi Ling

    Published 2025-05-01
    “…The performance of the AI model was evaluated based on the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.ResultsThe multimodal AI diagnostic model achieved an AUC of 0.9923, a maximum Youden index of 0.9389, a sensitivity of 97.0% and a specificity of 96.9% in predicting the prevalence of NMO on test data set.ConclusionOur study demonstrates the feasibility of DL algorithms in diagnosing and predicting of NMO.…”
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