An Intelligent Ship Image/Video Detection and Classification Method with Improved Regressive Deep Convolutional Neural Network by Zhijian Huang, Bowen Sui, Jiayi Wen, Guohe Jiang

“…Thus, this paper makes a self-built dataset for the ship image/video detection and classification, and its method based on an improved regressive deep convolutional neural network is presented. This method promotes the regressive convolutional neural network from four aspects. …”
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A Classroom Emotion Recognition Model Based on a Convolutional Neural Network Speech Emotion Algorithm by Qinying Yuan

“…In this paper, we construct a model of convolutional neural network speech emotion algorithm, analyze the classroom identified by the neural network with a certain degree of confidence together with the school used in the dataset, find the characteristics and rules of teachers’ control of classroom emotion nowadays using big data, find the parts of classroom emotion, and design a classroom emotion recognition model based on convolutional neural network speech emotion algorithm according to these characteristics. …”
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A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network by Ran Wang, Chunbiao Li, Serdar Çiçek, Karthikeyan Rajagopal, Xin Zhang

“…Finally, the proposed memristive hyperjerk system is successfully predicted with artificial neural networks for AI based engineering applications.…”
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Estimation of zooplankton density with artificial neural networks (a new statistical approach) method, Elazığ-Türkiye by Bulut Hilal

Subjects: “…artificial neural network…”
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Delay-Dependent Stability Criteria of Uncertain Periodic Switched Recurrent Neural Networks with Time-Varying Delays by Xing Yin, Jun Li, Weigen Wu, Qiranrong Tan

“…This paper deals with the problem of delay-dependent stability criterion of uncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. …”
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Komparasi Data Mining Naive Bayes dan Neural Network memprediksi Masa Studi Mahasiswa S1 by Azahari Azahari, Yulindawati Yulindawati, Dewi Rosita, Syamsuddin Mallala

“…Sedangkan akurasi prediksi neural network adalah 72,58%, sehingga metode alternatif inilah yang lebih baik. …”
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A Real-Time Angle- and Illumination-Aware Face Recognition System Based on Artificial Neural Network by Hisateru Kato, Goutam Chakraborty, Basabi Chakraborty

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Walking Gait Phase Detection Based on Acceleration Signals Using Voting-Weighted Integrated Neural Network by Lei Yan, Tao Zhen, Jian-Lei Kong, Lian-Ming Wang, Xiao-Lei Zhou

“…In this paper, a novel voting-weighted integrated neural network (VWI-DNN) is proposed to detect different gait phases from multidimensional acceleration signals. …”
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Prediction Model for Safe Operation of Pumping Stations Optimized by the Sparrow Search Algorithm and BP Neural Network by Ziwei Yu, Jinhuang Yu, Jinjie Liu, Chenglong Hu, Shengsheng Hu, Junjie Wang, Hehe Zhang, Huiting Lu

“…This article intends to use the BP neural network to predict the safe operation status of pump stations and optimize the initial threshold and weight information of the BP network using the sparrow search algorithm (SSA) to improve the accuracy and generalization ability of the model. …”
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Long Short-Term Memory Projection Recurrent Neural Network Architectures for Piano’s Continuous Note Recognition by YuKang Jia, Zhicheng Wu, Yanyan Xu, Dengfeng Ke, Kaile Su

“…Long Short-Term Memory (LSTM) is a kind of Recurrent Neural Networks (RNN) relating to time series, which has achieved good performance in speech recogniton and image recognition. …”
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Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm by M. O. Zelenskih, A. E. Saprygin, S. S. Tamozhnikov, P. D. Rudych, D. A. Lebedkin, A.  N. Savostyanov

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ARTIFICIAL NEURAL NETWORK IN THE MODELLING OF THE EFFECT OF CHROMIUM DOPANTS ON THE MECHANICAL PROPERTIES OF AL-4%CU ALLOY by EYERE EMAGBETERE, OGHENEKOWHO PETER ARUOTURE, FESTUS IFEANYI ASHIEDU

“… Artificial Neural Network (ANN) was used to model the effect of Chromium dopants on the mechanical properties duralumin (Al-4 %Cu). …”
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Predicting and synthesizing terahertz spoof surface plasmon polariton devices with a convolutional neural network model by Vahid Najafy, Bijan Abbasi-Arand, Maryam Hesari-Shermeh

“…Abstract With the increasing global attention to deep learning and the advancements made in applying convolutional neural networks in electromagnetics, we have recently witnessed the utilization of deep learning-based networks for predicting the spectrum and electromagnetic properties of structures instead of traditional tools like fully numerical-based methods. …”
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Presenting a neural network-based hybrid method for ADAS damper optimization in absorption of earthquake energy by Faezeh Nejati, Milad Jiyan

Subjects: “…neural network…”
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Environmental Fault Diagnosis of Solar Panels Using Solar Thermal Images in Multiple Convolutional Neural Networks by Tamilselvi Selvaraj, Ramasubbu Rengaraj, GiriRajanbabu Venkatakrishnan, SoundhariyaGanesan Soundararajan, Karuppiah Natarajan, PraveenKumar Balachandran, PrinceWinston David, Shitharth Selvarajan

“…In recent years, deep learning precisely convolutional neural networks have achieved wonderful results in many applications. …”
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Efficient and Explainable Virtual Screening of Molecules through Fingerprint-Generating Networks Integrated with Artificial Neural Networks by Rivaaj Monsia, Sudeep Bhattacharyya

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Prediction of NOx Emissions from a Direct Injection Diesel Engine Using Artificial Neural Network by J. Mohammadhassani, Sh. Khalilarya, M. Solimanpur, A. Dadvand

“…In the present study, artificial neural network is used to model the relationship between NOx emissions and operating parameters of a direct injection diesel engine. …”
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A DBN-Based Deep Neural Network Model with Multitask Learning for Online Air Quality Prediction by Jiangeng Li, Xingyang Shao, Rihui Sun

“…In this paper, for the purpose of improve prediction accuracy of air pollutant concentration, a deep neural network model with multitask learning (MTL-DBN-DNN), pretrained by a deep belief network (DBN), is proposed for forecasting of nonlinear systems and tested on the forecast of air quality time series. …”
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Predicting Nanobinder-Improved Unsaturated Soil Consistency Limits Using Genetic Programming and Artificial Neural Networks by Ahmed M. Ebid, Light I. Nwobia, Kennedy C. Onyelowe, Frank I. Aneke

“…Therefore, in this work, genetic programming (GP) and artificial neural network (ANN) have been used to predict the consistency limits, i.e., liquid limits, plastic limit, and plasticity index of unsaturated soil treated with a composite binder known as hybrid cement (HC) made from blending nanostructured quarry fines (NQF) and hydrated-lime-activated nanostructured rice husk ash (HANRHA). …”
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A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems by Yiming Jiang, Chenguang Yang, Hongbin Ma

“…Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC) and neural network (NN) control have been successfully used in various applications. …”
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