Algorithm development for recognizing human emotions using a convolutional neural network based on audio data by V. V. Semenuk, M. V. Skladchikov

Subjects: “…neural network…”
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Exponential Stability of Stochastic Delayed Neural Networks with Inverse Hölder Activation Functions and Markovian Jump Parameters by Yingwei Li, Huaiqin Wu

“…The exponential stability issue for a class of stochastic neural networks (SNNs) with Markovian jump parameters, mixed time delays, and α-inverse Hölder activation functions is investigated. …”
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Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models by Imran Said, Vasit Sagan, Kyle T. Peterson, Haireti Alifu, Abuduwanli Maiwulanjiang, Abby Stylianou, Omar Al Akkad, Supria Sarkar, Noor Al Shakarji

“…Sensitivity analyses were also conducted to identify the most sensitive bands for seed protein estimation. Convolutional neural networks (CNNs) with attention mechanisms were proposed along with traditional machine learning models based on feature engineering including Random Forest (RF) and Support Vector Machine (SVM) regression for comparative analysis. …”
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Fuzzy Neural Network for Fuzzy Quadratic Programming With Penalty Function and Mean-Variance Markowitz Portfolio Model by Izaz Ullah Khan, Muhammad Aamir, Mehran Ullah, Muhammad Shahbaz Shah

“…This research tries to integrate fuzzy neural networks with penalty function to address the quadratic programming based on the mean-variance Markowitz portfolio model. …”
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Identification of Vibration Signal for Residual Pressure Utilization Hydraulic Unit Using MRFO-BP Neural Network by Qingjiao Cao, Liying Wang, Jiajie Zhang, Tengfei Guo, Xiyuan Liu

“…Compared with Particle Swarm Optimization-BP (PSO-BP) neural network, Bat Algorithm-BP (BA-BP) neural network, and BP neural network, the results show that the identification rate of each measuring point from the MRFO-BP neural network is greatly improved. …”
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Hydrological Models and Artificial Neural Networks (ANNs) to Simulate Streamflow in a Tropical Catchment of Sri Lanka by Miyuru B. Gunathilake, Chamaka Karunanayake, Anura S. Gunathilake, Niranga Marasingha, Jayanga T. Samarasinghe, Isuru M. Bandara, Upaka Rathnayake

“…Hydrological modelling is a frequently adopted and a matured technique to simulate streamflow compared to the data driven models such as artificial neural networks (ANNs). In addition, usage of ANNs is minimum to simulate streamflow in the context of Sri Lanka. …”
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Global Robust Exponential Stability and Periodic Solutions for Interval Cohen-Grossberg Neural Networks with Mixed Delays by Yanke Du, Rui Xu

“…A class of interval Cohen-Grossberg neural networks with time-varying delays and infinite distributed delays is investigated. …”
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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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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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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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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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