Road Performance and Ice-Melting Characteristics of Steel Wool Asphalt Mixture by Yifeng Xia, Jie Jia, Qian Chen

“…A prediction model of the ice-melting rate of steel wool asphalt mixture based on a double-hidden layer backpropagation (BP) neural network was established. The results show that the road performance of the asphalt mixture mixed with steel wool mostly meets the requirements of the specification. …”
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A hybrid model for prediction of software effort based on team size by Prerana Rai, Dinesh Kumar Verma, Shishir Kumar

“…These techniques are mostly based on statistical methods (viz. simple linear regression (SLR), multi linear regression, support vector machine, cascade correlation neural network (CCNN) etc.) and some probability‐based models. …”
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Comparison of Fully Convolutional Networks and U-Net for Optic Disc and Optic Cup Segmentation by Jin Zixiao

“…This paper aims to compare two well-known convolutional neural network (CNN) structures, namely Fully Convolutional Networks (FCNs) and U-Net for the segmentation of the optic disc (OD) and optic cup (OC) from retinal fundus images which play an important role in glaucoma diagnosis. …”
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Transcranial Alternating Current and Random Noise Stimulation: Possible Mechanisms by Andrea Antal, Christoph S. Herrmann

“…Such findings are further supported by neural network simulations and knowledge from physics on entraining physical oscillators in the human brain. …”
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Gradient Enhancement Techniques and Motion Consistency Constraints for Moving Object Segmentation in 3D LiDAR Point Clouds by Fangzhou Tang, Bocheng Zhu, Junren Sun

“…In this paper, we introduce a novel deep neural network designed to enhance the performance of 3D LiDAR point cloud moving object segmentation (MOS) through the integration of image gradient information and the principle of motion consistency. …”
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A Semi-supervised Deep Learning Method for Cervical Cell Classification by Siqi Zhao, Yongjun He, Jian Qin, Zixuan Wang

“…Cervical cell classification is a key technology in the intelligent cervical cancer diagnosis system. Training a deep neural network-based classification model requires a large amount of data. …”
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Perception Analysis and Early Warning of Home-Based Care Health Information Based on the Internet of Things by Yi Mao, Lei Zhang, Xin Wu

“…In order to improve the accuracy of prediction, the DS evidence theory is used to optimize the traditional BP neural network (BPNN) algorithm and conduct experimental tests. …”
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A Hybrid Process Monitoring and Fault Diagnosis Approach for Chemical Plants by Lijie Guo, Jianxin Kang

“…Based on hazard and operability (HAZOP) analysis, kernel principal component analysis (KPCA), wavelet neural network (WNN), and fault tree analysis (FTA), a hybrid process monitoring and fault diagnosis approach is proposed in this study. …”
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Refinement Method of Evaluation and Ranking of Innovation and Entrepreneurship Ability of Colleges and Universities Based on Optimal Weight Model by Wei Guo, Lihua Liu, Yao Yao, Tong Shen

“…This paper proposes a sorting refinement method based on the optimal weight model and uses the BP neural network to determine the optimal weight. Weight is a scoring mechanism for comprehensive ranking, that is, a scoring system. …”
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Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning by Won Joong Kim, Gunho Jung, Sun-Yong Choi

“…In this study, we analyze the term structure of credit default swaps (CDSs) and predict future term structures using the Nelson–Siegel model, recurrent neural network (RNN), support vector regression (SVR), long short-term memory (LSTM), and group method of data handling (GMDH) using CDS term structure data from 2008 to 2019. …”
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The process of budgeting the strategy of industrial complex transformation in the context of digitalisation by A. G. Boev

“…The author determines the recommended amount and horizon of the strategy budget planning and also presents a 6-stage algorithm of methodical reception on the use of neural network modeling tools to optimize the budget of the strategy of changes in the industrial complex. …”
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Semantic-Based Classification of Long Texts on Higher Education in China by Chun Li, Yanying Fei

“…To solve these problems, this paper improves the convolutional neural network (CNN) into the HE-CNN classification model for HE texts. …”
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Fault Diagnosis and Detection in Industrial Motor Network Environment Using Knowledge-Level Modelling Technique by Saud Altaf, Muhammad Waseem Soomro, Mirza Sajid Mehmood

“…This paper presents efficient supervised Artificial Neural Network (ANN) learning technique that is able to identify fault type when situation of diagnosis is uncertain. …”
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Mitigating Sinkhole Attacks in MANET Routing Protocols using Federated Learning HDBNCNN Algorithm by Sherril Sophie Maria Vincent

“…Further, the Hierarchical Deep Belief Network Convolutional Neural Network (HDBNCNN) algorithm has analysed the accumulated data in detecting the anomalies revealing the sinkhole activity centred on learning routing patterns. …”
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Deep Learning for Plastic Waste Classification System by Janusz Bobulski, Mariusz Kubanek

“…One of the opportunities is the use of deep learning and convolutional neural network. In household waste, the most problematic are plastic components, and the main types are polyethylene, polypropylene, and polystyrene. …”
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A Network Traffic Prediction Model Based on Layered Training Graph Convolutional Network by Yulian Li, Yang Su

“…Routing deployment and resource scheduling in communication networks require accurate traffic prediction. Neural network-based models that extract the time-correlated or space-correlated features of traffic flow have been developed for traffic prediction. …”
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Real-Time Multi-Task Deep Learning Model for Polyp Detection, Characterization, and Size Estimation by Phanukorn Sunthornwetchapong, Kasichon Hombubpha, Kasenee Tiankanon, Satimai Aniwan, Pasit Jakkrawankul, Natawut Nupairoj, Peerapon Vateekul, Rungsun Rerknimitr

“…In this work, we present a modified convolutional neural network (CNN) based deep learning (DL) model to perform these tasks in real-time, utilizing existing object detection models: YOLOv5 and YOLOv8. …”
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Anticipating Stock Market of the Renowned Companies: A Knowledge Graph Approach by Yang Liu, Qingguo Zeng, Joaquín Ordieres Meré, Huanrui Yang

“…A comparison of the average accuracy with which the same feature combinations were extracted over six stocks indicated that the proposed method achieves better performance than that exhibited by an approach that uses only stock data, a bag-of-words method, and convolutional neural network. Our work highlights the usefulness of knowledge graph in implementing business activities and helping practitioners and managers make business decisions.…”
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Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network by Mutasem Sh. Alkhasawneh, Umi Kalthum Ngah, Lea Tien Tay, Nor Ashidi Mat Isa, Mohammad Subhi Al-batah

“…The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.…”
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Perfusion MRI in automatic classification of multiple sclerosis lesion subtypes by Ehsan Homayouny, Rasoul Mahdavifar Khayati, Seyed Massood Nabavi, Vania Karami

“…Therefore, a Bayesian classifier based on the adaptive mixture method was used to segment all lesions, and an artificial neural network (ANN) employed a multi‐layer Perceptron as a subtype classifier. …”
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