Prediction of Potato Rot Level by Using Electronic Nose Based on Data Augmentation and Channel Attention Conditional Convolutional Neural Networks by Jiayu Mai, Haonan Lin, Xuezhen Hong, Zhenbo Wei

“…Several machine learning and deep learning models, including traditional classifiers (SVM, LR, RF, ANN) and advanced neural networks (CNN, ECA-CNN, CAM-CNN, Conditional CNN), were trained and evaluated. …”
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A Pipeline for Multivariate Time Series Forecasting of Gas Consumption in Pelletization Process by Thadeu Pezzin Melo, Jefferson Andrade, Karin Satie Komati

“…The methodology was tested on a dataset with 45 operational parameters collected over 90 days from an industrial plant, with predictions evaluated using Root Mean Squared Error (RMSE). In step (iii), twelve features were identified as the most relevant based on the Random Forest importance index. …”
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Nitrate Content in Open Field Spinach, Applicative Case for Hyperspectral Reflectance Data by Walter Polilli, Angelica Galieni, Fabio Stagnari

“…Shallow artificial neural networks (ANN) and ensemble techniques—majority voting (MV) and stacked generalization (stacked)—were applied. …”
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TMBO-AOD: Transparent Mask Background Optimization for Accurate Object Detection in Large-Scale Remote-Sensing Images by Tianyi Fu, Hongbin Dong, Benyi Yang, Baosong Deng

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HY-Deepnet : A new Optimal Deep transfer learning empowered framework for an autonomous Alzheimer’s disease detection and diagnosis system by S. Veluchamy, R. Bhuvaneswari, K. Ashwini, Samah Alshathri, Walid El-Shafai

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Comparison and Analysis of Network Construction Methods for Seismicity Based on Complex Networks by Xuan He, Syed Bilal Hussain Shah, Bo Wei, Zheng Liu

“…By using the same dataset from the Southern California Seismic Network, three networks are constructed. They all present the scale-free, small-world properties, a strength-degree correlation, and an assortative mixing feature. …”
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Evaluating the impact of hyperparameters on the performance of 1D CNN model for nutritional profiling of underutilized crops using NIRS data by Simardeep Kaur, Naseeb Singh, Amit Kumar, Philanim W S, Veerendra Kumar Verma, Amit Kumar Patil, Rakesh Bhardwaj, Amritbir Riar

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Victimization analysis model of user network behavior based on network traffic by Shengli ZHOU, Xiaoyang XU

“…The analysis of network victimization is of great significance to the prevention and control of telecom fraud.By studying the network traffic generated by the interaction between users and websites, a victimization identification model of telecom fraud crime based on network behavior flow analysis was proposed, the association rules between different behavior characteristics were analyzed, the behavior sequence features were reconstructed, and the victimization of network behavior sequence with random forest algorithm was evaluated.Based on the network behavior data set of public security organs, the experiment proves that the model can effectively improve the recognition accuracy of network behavior victimization.…”
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Flow Field Analysis and Development of a Prediction Model Based on Deep Learning by Yingjie Yu, Xiufeng Zhang, Lucai Wang, Rui Tian, Xiaobin Qian, Dongdong Guo, Yanwei Liu

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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…From the results measured by evaluation metrics, the proposed model ANN with the combination of parameter tuning, feature selection algorithm, SMOTE-ENN, and optimal hyper-parameters demonstrates superior performance compared to traditional methods, achieving an F1 Score of 98.5% and an accuracy of 98.6%. …”
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Data-driven seismic mechanical performance evaluation of RC columns based on adaptive optimization ensemble learning method integrating random forest and back propagation neural ne... by Ayong Jiao, Ziqing Jiao, Bin Gao

“…To address this, this study proposes an adaptive optimization ensemble learning model (AO-RF-BP) for seismic mechanical performance evaluation. The model integrates the strengths of random forest (RF) and back propagation neural network (BP) models, employing the dynamic weighting strategy based on mean absolute error (MAE). …”
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Quantum neural network-based approach for optimizing road network selection by Haohua Zheng, Heying Li, Jianchen Zhang, Guangxia Wang, Jianzhong Guo, Jiayao Wang

“…Our study delves into the impact of feature encoding methods and circuit structures on the performance of quantum neural networks in road selection. …”
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New acorane-sesequiterpenes and anti-retinoblastoma constituents from the marine algicolous fungus Trichoderma harzianum NTU2180 guided by molecular networking strategy by Andrea Gu, Fan-Li Lin, Chung-Kuang Lu, Tz-Wei Yeh, Yih-Fung Chen, Ho-Cheng Wu, Tzong-Huei Lee

“…To facilitate the exploration of bioactive secondary metabolites of Trichoderma harzianum NTU2180, the OSMAC approach MS/MS molecular networking was applied in the current study. Results The feature-based molecular networking (FBMN) analysis showed that T. harzianum NTU2180 fermented on germinated brown rice (GBR) produced more terpenoids. …”
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Striking the Balance: Evaluating Content Quality and Reward Dynamics in Blockchain Online Social Media by Davide Mancino, Barbara Guidi, Andrea Michienzi, Marco Viviani

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DDoS classification of network traffic in software defined networking SDN using a hybrid convolutional and gated recurrent neural network by Ahmed M. Elshewey, Safia Abbas, Ahmed M. Osman, Eman Abdullah Aldakheel, Yasser Fouad

“…This paper presents a comprehensive evaluation of six deep learning models (Multilayer Perceptron (MLP), one-dimensional Convolutional Neural Network (1D-CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and a proposed hybrid CNN-GRU model) for binary classification of network traffic into benign or attack classes. …”
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Business Ecosystems: Specific Features of Organising Interactions and Communications by A. V. Lopukhin, E. A. Plaksenkov, S. N. Silvestrov

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Research on Multi-Step Prediction of Pipeline Corrosion Rate Based on Adaptive MTGNN Spatio-Temporal Correlation Analysis by Mingyang Sun, Shiwei Qin

“…In order to comprehensively investigate the spatio-temporal dynamics of corrosion evolution under complex pipeline environments and improve the corrosion rate prediction accuracy, a novel framework for corrosion rate prediction based on adaptive multivariate time series graph neural network (MTGNN) multi-feature spatio-temporal correlation analysis is proposed. …”
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FEATURES OF CYTOKINE PRODUCTION IN PATIENTS WITH RECURRENT HERPETIC INFECTION by I. A. Novikovа, O. A. Romanivа

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PRO-BiGRU: Performance Evaluation Index System for Hardware and Software Resource Sharing Based on Cloud Computing by Nan Wang

“…To achieve this, we propose an enhanced performance evaluation method by integrating the Poor-Rich Optimization (PRO) algorithm with the Bidirectional Gated Recurrent Unit (BiGRU) network. …”
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Evaluation of the precision and accuracy in the classification of breast histopathology images using the MobileNetV3 model by Kenneth DeVoe, Gary Takahashi, Ebrahim Tarshizi, Allan Sacker

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