Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks by Kang Xie, Yixian Yang, Ling Zhang, Maohua Jing, Yang Xin, Zhongxian Li

“…In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. …”
Get full text

Secure UAV-Based System to Detect Small Boats Using Neural Networks by Moisés Lodeiro-Santiago, Pino Caballero-Gil, Ricardo Aguasca-Colomo, Cándido Caballero-Gil

“…The proposal makes extensive use of emerging technologies like Unmanned Aerial Vehicles (UAV) combined with a top-performing algorithm from the field of artificial intelligence known as Deep Learning through Convolutional Neural Networks. The use of this algorithm improves current detection systems based on image processing through the application of filters thanks to the fact that the network learns to distinguish the aforementioned objects through patterns without depending on where they are located. …”
Get full text

Prediction of Later-Age Concrete Compressive Strength Using Feedforward Neural Network by Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran

“…In this investigation, an approach using a feedforward neural network (FNN) machine learning algorithm was proposed to predict the compressive strength of later-age concrete. …”
Get full text

Network Anomaly Detection Using Quantum Neural Networks on Noisy Quantum Computers by Alon Kukliansky, Marko Orescanin, Chad Bollmann, Theodore Huffmire

Subjects: Get full text

Antiperiodic Solutions to Impulsive Cohen-Grossberg Neural Networks with Delays on Time Scales by Yanqin Wang, Maoan Han

“…We use the method of coincidence degree and construct suitable Lyapunov functional to investigate the existence and global exponential stability of antiperiodic solutions of impulsive Cohen-Grossberg neural networks with delays on time scales. Our results are new even if the time scale T=R or Z. …”
Get full text

Respiratory disease detection in lung auscultation with convolutional neural networks and CVAE augmentation by D.V. Panaskin, S.H. Stirenko, D.S. Babko

Subjects: Get full text

AN APPROACH HYBRID RECURRENT NEURAL NETWORK AND RULE-BASE FOR INTRUSION DETECTION SYSTEM by Trần Thị Hương, Phạm Văn Hạnh

“…In this paper, we present a model based on the combination of recurrent neural networks and rule sets for the network intrusion detection problem. …”
Get full text

Horseshoe Chaos in a 3D Neural Network with Different Activation Functions by Fangyan Yang, Song Tang, Guilan Xu

“…This paper studies a small neural network with three neurons. First, the activation function takes the sign function. …”
Get full text

Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network by Kazuhiko Hiramoto, Taichi Matsuoka, Katsuaki Sunakoda

“…We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. …”
Get full text

New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type by Ozlem Faydasicok

“…This research work conducts an investigation of the stability issues of neutral-type Cohen–Grossberg neural network models possessing discrete time delays in states and discrete neutral delays in time derivatives of neuron states. …”
Get full text

On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network by Xinying Wu, Minggang Yang, Zishun Su, Xinxin Zhang

“…By measuring the cognitive complexity of the product, this research establishes the relationship between the complexity and aesthetics of the product using an artificial neural network. Hence the prediction of product beauty is achieved, which guides design decisions. …”
Get full text

GRAiCE: reconstructing terrestrial water storage anomalies with recurrent neural networks by Irene Palazzoli, Serena Ceola, Pierre Gentine

“…In this study, we develop GRAiCE, a set of four global monthly TWSA reconstructions from 1984 to 2021 at 0.5° spatial resolution, using Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) neural networks. Our models accurately reproduce GRACE/GRACE-FO observations at the global scale and effectively capture the impacts of climate extremes. …”
Get full text

Analysis of Local Macroeconomic Early-Warning Model Based on Competitive Neural Network by Xiaoxuan Wang, Jingjing Wang, Ying Zhang, Yixing Du

“…This article proposes a method of selecting macroeconomic early-warning indicators using self-organizing competitive neural networks and designs a macroeconomic nonlinear early warning model of self-organizing competitive neural networks; using fuzzy logic reasoning to introduce economic experts’ experience into macroeconomic early warning analysis, the system has the ability to deal with nonlinear and uncertain problems and realizes the intelligence of the early-warning process, uses the national macroeconomic indicator data from January 1997 to March 2008 for empirical analysis, and compares the self-organizing competitive neural network method with the traditional KL information method. …”
Get full text

Artificial Neural Network for the Clustering of Vibration Signals for Condition Monitoring of Rotating Machines by Eyere Emagbetere, Samson Uwatse, Omonzokpia Goerge Okoidigun

“…However, analysis of vibration signals using artificial neural network (ANN) is mostly via development of classification models, which cannot be suitably applied to several varied machine types and specifications. …”
Get full text

Forecast of Chemical Export Trade Based on PSO-BP Neural Network Model by Na Li, Meng Li

“…Although the traditional linear prediction method has the advantages of intuitiveness, simplicity, and strong interpretability, it is difficult to deal with the prediction problem of dynamic and complex nonlinear systems. The neural network is a nonlinear dynamic system, with strong nonlinear mapping ability, strong robustness, and fault tolerance. …”
Get full text

Retracted: Risk Prediction of Sports Events Based on Gray Neural Network Model by null Complexity

Get full text

The Application of Speech Synthesis Technology Based on Deep Neural Network in Intelligent Broadcasting by Jihong Yang

“…To improve the sound quality of speech synthesis technology in intelligent broadcasting, a deep neural network-based method is proposed. It also proved the effectiveness of the DNN discrimination s/u/v and completed the conversion of the HMM synthesis spectrum parameter to original speech. …”
Get full text

Recurrent neural networks with transient trajectory explain working memory encoding mechanisms by Chenghao Liu, Shuncheng Jia, Hongxing Liu, Xuanle Zhao, Chengyu T. Li, Bo Xu, Tielin Zhang

“…Even though many recurrent neural networks (RNNs) have been proposed to simulate WM, most networks are designed to match respective experimental observations and show either transient or persistent activities. …”
Get full text

Claim Amount Forecasting and Pricing of Automobile Insurance Based on the BP Neural Network by Wenguang Yu, Guofeng Guan, Jingchao Li, Qi Wang, Xiaohan Xie, Yu Zhang, Yujuan Huang, Xinliang Yu, Chaoran Cui

“…The BP neural network model is a hot issue in recent academic research, and it has been successfully applied to many other fields, but few researchers apply the BP neural network model to the field of automobile insurance. …”
Get full text

Exponential Convergence for Cellular Neural Networks with Time-Varying Delays in the Leakage Terms by Zhibin Chen, Junxia Meng

“…We consider a class of cellular neural networks with time-varying delays in the leakage terms. …”
Get full text