Human Resource Allocation Based on Fuzzy Data Mining Algorithm by You Wu, Zheng Wang, Shengqi Wang

“…Data mining involves multiple technologies, such as mathematical statistics, fuzzy theory, neural networks, and artificial intelligence, with relatively high technical content. …”
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The Adaptive Neuroplasticity Hypothesis of Behavioral Maintenance by Janey C. Peterson

“…In this paper, we posit that among older adults with CHD, recidivism after the initiation of physical activity reflects maladaptive neuroplasticity of malleable neural networks, and people will revert back to learned and habitual physical inactivity patterns, particularly in the setting of stress or depression. …”
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Prediction of cold region dew volume based on an ECOA-BiTCN-BiLSTM hybrid model by Yi Zhang, Pengtao Liu, Yingying Xu, Meng Zhang

“…The model integrates BiTCN and BiLSTM neural networks to enhance performance. An enhanced Crayfish optimization algorithm (ECOA) with four mixed strategies was employed to optimize the model’s hyperparameters and reduce the impact of arbitrary selection. …”
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Adversarial Robust Modulation Recognition Guided by Attention Mechanisms by Quanhai Zhan, Xiongwei Zhang, Meng Sun, Lei Song, Zhenji Zhou

“…Deep neural networks have demonstrated considerable effectiveness in recognizing complex communications signals through their applications in the tasks of automatic modulation recognition. …”
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Modelling and optimization of well hole cleaning using artificial intelligence techniques by Nageswara Rao Lakkimsetty, Hassan Rashid Ali Al Araimi, G. Kavitha

“…This study aims to improve the accuracy and practicality of hole cleaning assessment by applying Artificial Intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Genetic Algorithms (GA), to predict downhole parameters and optimize drilling processes. …”
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Is the Linear Modeling Technique Good Enough for Optimal Form Design? A Comparison of Quantitative Analysis Models by Yang-Cheng Lin, Chung-Hsing Yeh, Chen-Cheng Wang, Chun-Chun Wei

“…The consumer-oriented design approach uses quantification theory type I, grey prediction (the linear modeling technique), and neural networks (the nonlinear modeling technique) to determine the optimal form combination of product design for matching a given product image. …”
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Modelling Laser Milling of Microcavities for the Manufacturing of DES with Ensembles by Pedro Santos, Daniel Teixidor, Jesus Maudes, Joaquim Ciurana

“…In total, 162 different conditions are tested in a process that is modeled with the following state-of-the-art data-mining regression techniques: Support Vector Regression, Ensembles, Artificial Neural Networks, Linear Regression, and Nearest Neighbor Regression. …”
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A Bichannel Transformer with Context Encoding for Document-Driven Conversation Generation in Social Media by Yuanyuan Cai, Min Zuo, Qingchuan Zhang, Haitao Xiong, Ke Li

“…Previous studies usually use sequence-to-sequence learning with recurrent neural networks for response generation. However, recurrent-based learning models heavily suffer from the problem of long-distance dependencies in sequences. …”
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Decision models enhancing environmental flow sustainability: A strategic approach to water resource management by Seiran Haghgoo, Jamil Amanollahi, Barzan Bahrami Kamangar, Shahryar Sorooshian

“…The assessment and optimization of EF under uncertain conditions was achieved by combining physical habitat simulation (PHABSIM) modeling with advanced techniques like Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Multilayer Perceptron (MLP) neural networks. This integrated modeling approach contributes to sustainable solutions for river basin management and environmental conservation by effectively optimizing EF, as demonstrated by the results. …”
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Inverse design of promising electrocatalysts for CO2 reduction via generative models and bird swarm algorithm by Zhilong Song, Linfeng Fan, Shuaihua Lu, Chongyi Ling, Qionghua Zhou, Jinlan Wang

“…Here, we present a framework named Material Generation with Efficient Global Chemical Space Search (MAGECS) that addresses this challenge by integrating the bird swarm algorithm and supervised graph neural networks, enabling effective navigation of generative models in the immense chemical space towards materials with target properties. …”
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Using EEG technology to enhance performance measurement in physical education by Zhaofeng Zhai, Zhaofeng Zhai, Lu Han, Wei Zhang

“…APEO combines biomechanical modeling, engagement prediction through recurrent neural networks, and reinforcement learning to tailor physical activity interventions. …”
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Innovative laboratory techniques shaping cancer diagnosis and treatment in developing countries by Azeez Okikiola Lawal, Tolutope Joseph Ogunniyi, Oriire Idunnuoluwa Oludele, Oluwaloseyi Ayomipo Olorunfemi, Olalekan John Okesanya, Jerico Bautista Ogaya, Emery Manirambona, Mohamed Mustaf Ahmed, Don Eliseo Lucero-Prisno

“…The integration of artificial intelligence, particularly deep learning and convolutional neural networks, has enhanced the diagnostic accuracy and data analysis capabilities. …”
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Chinese Mathematical Knowledge Entity Recognition Based on Linguistically Motivated Bidirectional Encoder Representation from Transformers by Wei Song, He Zheng, Shuaiqi Ma, Mingze Zhang, Wei Guo, Keqing Ning

“…In order to improve the accuracy of mathematical knowledge entity recognition and provide effective support for subsequent functionalities, this paper adopts the latest pre-trained language model, LERT, combined with a Bidirectional Gated Recurrent Unit (BiGRU), Iterated Dilated Convolutional Neural Networks (IDCNNs), and Conditional Random Fields (CRFs), to construct the LERT-BiGRU-IDCNN-CRF model. …”
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Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction by Asraar Anjum, Meftah Hrairi, Abdul Aabid Shaikh, Noorfazrina Yatim, Maisarah Ali

“…This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs), Design of Experiments (DOE), and fuzzy logic (FL), are transforming civil engineering practices. …”
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Artificial intelligence based prediction and multi-objective RSM optimization of tectona grandis biodiesel with Elaeocarpus Ganitrus by V Vinoth Kannan, Bhavesh Kanabar, J Gowrishankar, Ali Khatibi., Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Pushparaj Thomai, Jasmina Lozanović

“…Advanced Machine Learning (ML) models, including Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), and Random Trees (RT), were employed for predictive analysis, with ANN outperforming RSM in accuracy. …”
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FFUNet: A novel feature fusion makes strong decoder for medical image segmentation by Junsong Xie, Renju Zhu, Zezhi Wu, Jinling Ouyang

“…Abstract Convolutional neural networks (CNNs) have strong ability to extract local features, but it is slightly lacking in extracting global contexts. …”
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Bearing Fault Diagnosis Method Based on Multidomain Heterogeneous Information Entropy Fusion and Model Self-Optimisation by Renwang Song, Xiaolu Bai, Rui Zhang, You Jia, Lihu Pan, Zengshou Dong

“…The spatiotemporal approach uses a multiscene domain fusion strategy based on heterogeneous sensors (HSMSF) to extract feature fusion strategies and analyses the characteristics of the bearing fault features by multichannel processes with convolutional neural networks to vibration signals. After the mapping of multiple quality characteristics, the high-quality features are combined with each other, and the adaptive entropy weighted fusion method is used to analyse and make decisions on sensor information from different detection points. …”
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Research on 3D printing concrete mechanical properties prediction model based on machine learning by Yonghong Zhang, Suping Cui, Bohao Yang, Xinxin Wang, Tao Liu

“…Our study explores the fundamentals and practicality of several models, such as artificial neural networks, decision trees, random forests, support vector regression, and linear regression. …”
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An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games by Wang, Guillaume, Chizat, Lénaïc

“…We illustrate our results with numerical experiments and discuss applications to max-margin and distributionally-robust classification using two-layer neural networks, where our method has a natural interpretation as a simultaneous training of the network’s weights and of the adversarial distribution.…”
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Research on bearing fault diagnosis based on a multimodal method by Hao Chen, Shengjie Li, Xi Lu, Qiong Zhang, Jixining Zhu, Jiaxin Lu

“…In parallel, 13 key features are extracted from the original vibration data in the time-frequency domain. Convolutional neural networks are then employed for deep feature extraction. …”
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