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3381
Road Performance and Ice-Melting Characteristics of Steel Wool Asphalt Mixture
Published 2022-01-01“…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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3382
A hybrid model for prediction of software effort based on team size
Published 2021-12-01“…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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3383
Comparison of Fully Convolutional Networks and U-Net for Optic Disc and Optic Cup Segmentation
Published 2025-01-01“…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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3384
Transcranial Alternating Current and Random Noise Stimulation: Possible Mechanisms
Published 2016-01-01“…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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3385
Gradient Enhancement Techniques and Motion Consistency Constraints for Moving Object Segmentation in 3D LiDAR Point Clouds
Published 2025-01-01“…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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3386
A Semi-supervised Deep Learning Method for Cervical Cell Classification
Published 2022-01-01“…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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3387
Perception Analysis and Early Warning of Home-Based Care Health Information Based on the Internet of Things
Published 2021-01-01“…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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3388
A Hybrid Process Monitoring and Fault Diagnosis Approach for Chemical Plants
Published 2015-01-01“…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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3389
Refinement Method of Evaluation and Ranking of Innovation and Entrepreneurship Ability of Colleges and Universities Based on Optimal Weight Model
Published 2022-01-01“…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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3390
Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning
Published 2020-01-01“…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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3391
The process of budgeting the strategy of industrial complex transformation in the context of digitalisation
Published 2022-09-01“…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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3392
Semantic-Based Classification of Long Texts on Higher Education in China
Published 2021-01-01“…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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3393
Fault Diagnosis and Detection in Industrial Motor Network Environment Using Knowledge-Level Modelling Technique
Published 2017-01-01“…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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3394
Mitigating Sinkhole Attacks in MANET Routing Protocols using Federated Learning HDBNCNN Algorithm
Published 2025-02-01“…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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3395
Deep Learning for Plastic Waste Classification System
Published 2021-01-01“…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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3396
A Network Traffic Prediction Model Based on Layered Training Graph Convolutional Network
Published 2025-01-01“…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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3397
Real-Time Multi-Task Deep Learning Model for Polyp Detection, Characterization, and Size Estimation
Published 2025-01-01“…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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3398
Anticipating Stock Market of the Renowned Companies: A Knowledge Graph Approach
Published 2019-01-01“…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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3399
Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network
Published 2013-01-01“…The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.…”
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3400
Perfusion MRI in automatic classification of multiple sclerosis lesion subtypes
Published 2022-06-01“…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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