A Hyperparameters automatic optimization method of time graph convolution network model for traffic prediction

2021 ◽  
Author(s):  
Lei Chen ◽  
Lulu Bei ◽  
Yuan An ◽  
Kailiang Zhang ◽  
Ping Cui
Keyword(s):  
Network Model ◽  
Optimization Method ◽  
Traffic Prediction ◽  
Time Graph ◽  
Automatic Optimization

scholarly journals Attention based multi-component spatiotemporal cross-domain neural network model for wireless cellular network traffic prediction

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Qingtian Zeng ◽  
Qiang Sun ◽  
Geng Chen ◽  
Hua Duan
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Network Traffic ◽  
Cellular Network ◽  
Critical Issue ◽  
Traffic Prediction ◽  
Weekly Cycle ◽  
Cross Domain ◽  
Cellular Traffic

AbstractWireless cellular traffic prediction is a critical issue for researchers and practitioners in the 5G/B5G field. However, it is very challenging since the wireless cellular traffic usually shows high nonlinearities and complex patterns. Most existing wireless cellular traffic prediction methods lack the abilities of modeling the dynamic spatial–temporal correlations of wireless cellular traffic data, thus cannot yield satisfactory prediction results. In order to improve the accuracy of 5G/B5G cellular network traffic prediction, an attention-based multi-component spatiotemporal cross-domain neural network model (att-MCSTCNet) is proposed, which uses Conv-LSTM or Conv-GRU for neighbor data, daily cycle data, and weekly cycle data modeling, and then assigns different weights to the three kinds of feature data through the attention layer, improves their feature extraction ability, and suppresses the feature information that interferes with the prediction time. Finally, the model is combined with timestamp feature embedding, multiple cross-domain data fusion, and jointly with other models to assist the model in traffic prediction. Experimental results show that compared with the existing models, the prediction performance of the proposed model is better. Among them, the RMSE performance of the att-MCSTCNet (Conv-LSTM) model on Sms, Call, and Internet datasets is improved by 13.70 ~ 54.96%, 10.50 ~ 28.15%, and 35.85 ~ 100.23%, respectively, compared with other existing models. The RMSE performance of the att-MCSTCNet (Conv-GRU) model on Sms, Call, and Internet datasets is about 14.56 ~ 55.82%, 12.24 ~ 29.89%, and 38.79 ~ 103.17% higher than other existing models, respectively.

scholarly journals Contribution to image restoration using a neural network model

2002 ◽  
Vol Volume 1, 2002 ◽  
Author(s):  
Karim Achour ◽  
Nadia Zenati ◽  
Oualid Djekoune
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Network Model ◽  
Neural Network Model ◽  
Hopfield Neural Network ◽  
Optimization Method ◽  
Nous Proposons ◽  
International Audience ◽  
High Level

International audience The reduction of the blur and the noise is an important task in image processing. Indeed, these two types of degradation are some undesirable components during some high level treatments. In this paper, we propose an optimization method based on neural network model for the regularized image restoration. We used in this application a modified Hopfield neural network. We propose two algorithms using the modified Hopfield neural network with two updating modes : the algorithm with a sequential updates and the algorithm with the n-simultaneous updates. The quality of the obtained result attests the efficiency of the proposed method when applied on several images degraded with blur and noise. La réduction du bruit et du flou est une tâche très importante en traitement d'images. En effet, ces deux types de dégradations sont des composantes indésirables lors des traitements de haut niveau. Dans cet article, nous proposons une méthode d'optimisation basée sur les réseaux de neurones pour résoudre le problème de restauration d'images floues-bruitées. Le réseau de neurones utilisé est le réseau de « Hopfield ». Nous proposons deux algorithmes utilisant deux modes de mise à jour: Un algorithme avec un mode de mise à jour séquentiel et un algorithme avec un mode de mise à jour n-simultanée. L'efficacité de la méthode mise en œuvre a été testée sur divers types d'images dégradées.

scholarly journals A New Approach for Automatic Optimization of Complex Fracture Network in Shale Reservoirs

Lithosphere ◽  
2021 ◽  
Vol 2021 (Special 1) ◽  
Author(s):  
Haibo Wang ◽  
Tong Zhou ◽  
Fengxia Li
Keyword(s):  
Shale Gas ◽  
Flow Model ◽  
Optimization Method ◽  
Fracture Network ◽  
Gas Reservoirs ◽  
Fracture Length ◽  
Complex Fracture ◽  
Shale Gas Reservoirs ◽  
Automatic Optimization ◽  
Complex Fracture Network

Abstract Shale gas reservoirs have gradually become the main source for oil and gas production. The automatic optimization technology of complex fracture network in fractured horizontal wells is the key technology to realize the efficient development of shale gas reservoirs. In this paper, based on the flow model of shale gas reservoirs, the porosity/permeability of the matrix system and natural fracture system is characterized. The fracture network morphology is finely characterized by the fracture network expansion calculation method, and the flow model was proposed and solved. On this basis, the influence of matrix permeability, matrix porosity, fracture permeability, fracture porosity, and fracture length on the production of shale gas reservoirs is studied. The optimal design of fracture length and fracture location was carried, and the automatic optimization method of complex fracture network parameters based on simultaneous perturbation stochastic approximation (SPSA) was proposed. The method was applied in a shale gas reservoir, and the results showed that the proposed automatic optimization method of the complex fracture network in shale gas reservoirs can automatically optimize the parameters such as fracture location and fracture length and obtain the optimal fracture network distribution matching with geological conditions.

An Event-based Optimization Method for Building Evacuation with Queuing Network Model

2021 ◽  
Author(s):  
Yuandong Zhang ◽  
Zhanbo Xu ◽  
Jiang Wu ◽  
Xiaohong Guan
Keyword(s):  
Network Model ◽  
Optimization Method ◽  
Queuing Network ◽  
Building Evacuation ◽  
Event Based

Inverse Analysis of Forming Processes Based on FORGE Environment

2014 ◽  
Vol 611-612 ◽  
pp. 1494-1502 ◽  
Author(s):  
Stephane Marie ◽  
Richard Ducloux ◽  
Patrice Lasne ◽  
Julien Barlier ◽  
Lionel Fourment
Keyword(s):  
Inverse Analysis ◽  
Optimization Problems ◽  
Three Dimensional ◽  
Optimization Method ◽  
Transfer Coefficients ◽  
Support Design ◽  
Finite Element Software ◽  
Automatic Optimization ◽  
Dimensional Simulation ◽  
Constitutive Parameters

In the field of materials forming processes, the use of simulation coupled with optimization is a powerful numerical tool to support design in industry and research. The finite element software Forge®, a reference in the field of the two-dimensional and three-dimensional simulation of forging processes, has been coupled to an automatic optimization engine. The optimization method is based on meta-model assisted evolutionary algorithm. It allows solving complex optimization problems quickly. This paper is dedicated to a specific application of optimization, inverse analysis. In a first stage, a range of reverse analysis applications are considered such as material rheological and tribological characterization, identification of heat transfer coefficients and, finally, the estimation of Time Temperature Transformation curves based on existing Continuous Cooling Transformation diagrams for steel quenching simulation. In a second part, a novel inverse analysis application is presented in the field of cold sheet forming, the identification of the material anisotropic constitutive parameters that allow matching with the final shape of the component after stamping. The advanced numerical methods used in this kind of complex simulations are described along with the obtained optimization results. This article shows that automatic optimization coupled with Forge® can solve many inverse analysis problems and is a valuable tool for supporting development and design of metals forming processes.

AN AUTOMATIC OPTIMIZATION METHOD FOR NUCLEAR PIPING LAYOUT AND MECHANICAL ANALYSIS

2019 ◽  
Vol 2019.27 (0) ◽  
pp. 1387
Author(s):  
Xiaoming Bai ◽  
Rui Zhang ◽  
Liangang Zheng ◽  
Xifeng Lu ◽  
Kaikai Shi ◽  
...  
Keyword(s):  
Optimization Method ◽  
Mechanical Analysis ◽  
Automatic Optimization
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