The Two-Echelon Unmanned Ground Vehicle Routing Problem: Extreme-Weather Goods Distribution as a Case Study by Chuncheng Fang, Yanguang Cai, Yanlin Wu

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Spontaneous emergence of metacognition in neuronal computation by Hengyuan Ma, Wenlian Lu, Jianfeng Feng

“…We showcase this capability through diverse cognitive tasks and learning algorithms, including reservoir computing and backpropagation. …”
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Facies-Controlled Modeling for Permeability of Tight Gas Reservoir Based on Hydrodynamic and Geophysics Characteristics by Peng Yu

“…Due to poor physical properties and strong heterogeneity of Daniudi tight gasfield (China), traditional methods are not ideal for predicting reservoir permeability. Based on geoscience data mining algorithms and modeling techniques, this parameter is predicted and characterized from a new perspective. …”
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Regional Economy Using Hybrid Sequence-to-Sequence-Based Deep Learning Approach by Bo Peng

“…Hybrid sequence to sequence (seq2seq) algorithms of deep learning fed with previous information from past years and run the system to compare the predicted result data with current information to evaluate the method to be certified for the coming years.…”
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Foreign Trade Export Forecast Based on Fuzzy Neural Network by Yang Liu

“…Subsequently, the related concepts and principles of artificial neural network and fuzzy theory are explained, the types and training algorithms of the fuzzy neural network are introduced, and the neural network and fuzzy theory are combined to establish the prediction model. …”
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Eco-assessment of meat raw materials: A convolutional neural network approach to sustainable quality control by Verezubova Natalia, Sakovich Natalia, Yukovleva Olga, Chekulaev Artur, Verezubova Irina

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Comparative Analysis of Bio-Inspired Enhancement Techniques for Localization in 2D Wireless Sensor Networks by Rabhi Seddik

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Awareness of Unethical Artificial Intelligence and its Mitigation Measures by Sonja HÖLLER, Thomas DILGER, Teresa SPIESS, Christian PLODER, Reinhard BERNSTEINER

“…The most frequently mentioned mitigation measures by survey participants are laws and regulations, various types of algorithm audits, and education and training. This work thus provides new empirical insights for researchers and practitioners in the field of ethical artificial intelligence.…”
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Comparison and Evaluation of Rain Gauge, CMORPH, TRMM PR and GPM DPR KuPR Precipitation Products over South China by Rui Wang, Huiping Li, Hao Huang, Liangliang Li

“…This study aims to provide valuable insights for enhancing precipitation retrieval algorithms and improving the applicability of remote sensing precipitation products.…”
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Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…In terms of intelligent control, deep reinforcement learning is used to optimize irrigation decision-making, and adaptive algorithms are combined to improve the flexibility of agricultural equipment scheduling. …”
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Work Place Safety: Machine Learning Techniques for Assessing Workplace Incident Severity by Munayr Hasan Khalleefah Hassan, Wagdi M. S. Khalifa

“…Occupational injury severity prediction is paramount across all industries, necessitating the adoption of advanced methodologies to enhance predictive analysis. …”
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Preliminary exploration and application research on the model of gathering distillate according to the quality based on Fourier transform near infrared spectroscopy by LIAO Li, ZHANG Guiyu, ZOU Yongfang, ZHU Xuemei, PENG Houbo, ZHANG Wei, LI Yan

“…Multiplicative scatter correction (MSC), competitive adaptive reweighting algorithms sampling (CARS) and support vector regression (SVR) were better methods to construct the regression prediction model, with coefficient of determination R² and root mean square error (RMSE) mean values of 0.8951 and 0.03, respectively. …”
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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Secondly, variables that were highly correlated with sales were analyzed using gray relational analysis (GRA) and utilized as input parameters for the support vector regression (SVR) model, which was constructed to optimize sales predictions for EVs. Finally, a combined model incorporating different algorithms was verified against market sales data to explore the optimal sales prediction approach. …”
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Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing by Katarzyna Antosz, Lucia Knapčíková, Jozef Husár

“…A variety of classification algorithms, including neural networks (NNs), bagged trees (BT), and support vector machines (SVMs), were employed to efficiently analyse and predict defects. …”
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Reply to Comment on “Improving Bayesian Model Averaging for Ensemble Flood Modeling Using Multiple Markov Chains Monte Carlo Sampling” by Jasper Vrugt by Tao Huang, Venkatesh Merwade

“…Results reinforce the findings obtained from Huang and Merwade (2023a) https://doi.org/10.1029/2023wr034947 and further indicate that the proposed M‐H algorithm is better than the DREAM algorithm in terms of sampling efficiency and prediction accuracy. …”
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AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review by Xuanchi Guo, Yuhan Shao

“…This review will focus on the fusion of AI-driven multimodal data analysis (e.g., cone-beam CT, intraoral scanning, and 3D facial images) and deep learning algorithms (e.g., convolutional neural networks) to elucidate the technological breakthroughs in key aspects such as tooth movement trajectory prediction and early detection of root resorption. …”
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Machine learning-based hybrid risk estimation system (ERES) in cardiac surgery: Supplementary insights from the ASA score analysis. by Ayşe Banu Birlik, Hakan Tozan, Kevser Banu Köse

“…A retrospective analysis of 543 patients was performed using six machine learning algorithms applied to preoperative clinical data to assess predictive accuracy and clinical outcomes. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…This paper applies machine learning models to predict travel time reliability in transportation networks, using XGBoost, LightGBM, and CatBoost optimized with seven metaheuristic algorithms. …”
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Research on Resource Reservation Strategy for Edge Federation by Hengzhou Ye, Huangran Li, Jiaming Li, Qiu Lu, Gong Chen

“…Furthermore, the RRP-MADDPG strategy exhibits excellent convergence performance and outperforms both the load prediction-based reservation strategy and other similar deep reinforcement learning algorithms.…”
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Hybrid LSTM–Seq2Seq Models: Improved Patient Interaction for Healthcare Chatbots by saba abdalmnam, Suha Mohammed Hadi, Mustafa Musa

“…The capability of the model for sequence prediction is attributed to its robustness. Other methods of evaluation employing measures such as the Nash–Sutcliffe efficiency coefficient, correlation coefficient, and normalized root mean square error demonstrate that the model is superior to other machine learning algorithms utilizing linear regression and GP regression. …”
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