A Customized Deep Neural Network Approach to Investigate Travel Mode Choice with Interpretable Utility Information by Zhengchao Zhang, Congyuan Ji, Yineng Wang, Yanni Yang

“…Thus far, this field has been dominated by multinomial logit (MNL) models with a linear utility specification. However, deep neural networks (DNNs), owing to their powerful capacity of nonlinear fitting, are now rapidly replacing these models. …”
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The construction of a digital dissemination platform for the intangible cultural heritage using convolutional neural network models by Zhurong Liu

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An oral microbiota-based deep neural network model for risk stratification and prognosis prediction in gastric cancer by Xue-Feng Gao, Can-Gui Zhang, Kun Huang, Xiao-Lin Zhao, Ying-Qiao Liu, Zi-Kai Wang, Rong-Rong Ren, Geng-Hui Mai, Ke-Ren Yang, Ye Chen

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PM10 AIR POLLUTION IN MASHAD CITY USING ARTIFICIAL NEURAL NETWORK AND MAKOV CHAIN MODEL

Subjects: “…artificial neural networks…”
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Quasi-Matrix and Quasi-Inverse-Matrix Projective Synchronization for Delayed and Disturbed Fractional Order Neural Network by Jinman He, Fangqi Chen, Qinsheng Bi

“…This paper is concerned with the quasi-matrix and quasi-inverse-matrix projective synchronization between two nonidentical delayed fractional order neural networks subjected to external disturbances. First, the definitions of quasi-matrix and quasi-inverse-matrix projective synchronization are given, respectively. …”
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Improving multi-talker binaural DOA estimation by combining periodicity and spatial features in convolutional neural networks by Reza Varzandeh, Simon Doclo, Volker Hohmann

Subjects: “…Convolutional neural networks…”
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A Comparison Study on Rule Extraction from Neural Network Ensembles, Boosted Shallow Trees, and SVMs by Guido Bologna, Yoichi Hayashi

“…One way to make the knowledge stored in an artificial neural network more intelligible is to extract symbolic rules. …”
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Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints by Fenghui Lian, Yingjie Sun, Meiyu Li

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LDDP-Net: A Lightweight Neural Network with Dual Decoding Paths for Defect Segmentation of LED Chips by Jie Zhang, Ning Chen, Mengyuan Li, Yifan Zhang, Xinyu Suo, Rong Li, Jian Liu

“…This paper proposes a lightweight neural network with dual decoding paths for LED chip segmentation, named LDDP-Net. …”
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On the improvement of schizophrenia detection with optical coherence tomography data using deep neural networks and aggregation functions by Paweł Karczmarek, Małgorzata Plechawska-Wójcik, Adam Kiersztyn, Adam Domagała, Agnieszka Wolinska, Steven M. Silverstein, Kamil Jonak, Paweł Krukow

“…Numerical experiments involved applying several individual 1D Convolutional Neural Network-based models as well as further using the aggregation of classification results to improve the initial classification results. …”
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Graph Neural Networks for Analyzing Trauma-Related Brain Structure in Children and Adolescents: A Pilot Study by Harim Jeong, Minjoo Kang, Shanon McLeay, R. J. R. Blair, Unsun Chung, Soonjo Hwang

Subjects: “…graph neural networks (GNNs)…”
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SOM Neural Network Fault Diagnosis Method of Polymerization Kettle Equipment Optimized by Improved PSO Algorithm by Jie-sheng Wang, Shu-xia Li, Jie Gao

“…For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. …”
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Target Threat Assessment in Air Combat Based on Improved Glowworm Swarm Optimization and ELM Neural Network by Yuan Cao, Ying-Xin Kou, An Xu, Zhi-Fei Xi

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Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms by Özgür Özer, Harun Kemal Öztürk

“…Heuristic methods, particularly the widely used artificial neural networks and genetic algorithms, are explained in general terms. …”
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Calculation for Primary Combustion Characteristics of Boron-Based Fuel-Rich Propellant Based on BP Neural Network by Wu Wan'e, Zhu Zuoming

“…A practical scheme for selecting characterization parameters of boron-based fuel-rich propellant formulation was put forward; a calculation model for primary combustion characteristics of boron-based fuel-rich propellant based on backpropagation neural network was established, validated, and then was used to predict primary combustion characteristics of boron-based fuel-rich propellant. …”
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Email Spam Detection Using a Hybrid Approach of Feedforward Neural Network and Penguin Optimization Algorithm by Layth Al-busultan

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Research on Food Security Risk Assessment and Early Warning in China Based on BP Neural Network Model by Yuke Hou, Xin Liang

“…This paper constructs a food security evaluation system from the perspective of data, breaks through the limitations of existing research, and improves the completeness of food security early warning indicators. Because the BP neural network is a multilayer feedforward neural network with strong adaptability, it is one of the most widely used and successful neural network models at present. …”
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Stability Analysis of Discrete Hopfield Neural Networks with the Nonnegative Definite Monotone Increasing Weight Function Matrix by Jun Li, Yongfeng Diao, Mingdong Li, Xing Yin

“…The original Hopfield neural networks model is adapted so that the weights of the resulting network are time varying. …”
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Sentiment analysis of Algerian Arabic dialect on social media Using Bi-LSTM recurrent neural networks by Abdelghani BOUZIANE, Benamar BOUOUGADA, Djelloul BOUCHIHA, Noureddine DOUMI

“… This paper presents a sentiment analysis approach using Bidirectional Long Short-Term Memory (Bi-LSTM) Recurrent Neural Networks to train predictive models for sentiment analysis on social media, particularly focusing on Algerian Arabic Dialect. …”
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Seismic Response Analysis and Evaluation of Laminated Rubber Bearing Supported Bridge Based on the Artificial Neural Network by Bingzhe Zhang, Kehai Wang, Guanya Lu, Weizuo Guo

“…A new constitutive model of bearing based on the artificial neural network (ANN) technique is established through the static cyclic test of laminated rubber bearings, considering the bearing initial stiffness, friction coefficient, and other parameters such as the bearing sectional area, height, loading velocity, vertical load, and aging time. …”
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