IncGraph: An Improved Distributed Incremental Graph Computing Model and Framework based on Spark GraphX

2021 ◽  
pp. 1-1
Author(s):  
Zhuo Tang ◽  
Mengsi He ◽  
Zhongming Fu ◽  
Li Yang
Keyword(s):  
Computing Model ◽  
Graph Computing

D2Graph: An Efficient and Unified Out-of-Core Graph Computing Model

2021 ◽  
Author(s):  
Baoke Li ◽  
Cong Cao ◽  
Yuhai Lu ◽  
Yanbing Liu ◽  
Baohui Li ◽  
...  
Keyword(s):  
Computing Model ◽  
Graph Computing

Distributed implementation of the graphs clusterization goodness metrics calculation using mapreduce and vertex-oriented graph processing model

2020 ◽  
pp. 31-35
Author(s):  
I.G. Danilov ◽  
S.I. Rodzin
Keyword(s):  
Clustering Algorithm ◽  
Oriented Graph ◽  
Graph Processing ◽  
Distributed Clustering ◽  
Large Graphs ◽  
Computing Model ◽  
Calculation Algorithms ◽  
Distributed Implementation ◽  
Graph Computing

Goal. Research of the implementation features of the graph clusterization goodness metrics using the vertexoriented graph computing model and MapReduce. Materials and methods. The basic concepts of graph theory were used to define the goodness metrics, and the MapReduce with a vertex-oriented graph-computational approach were used to develop the goodness metrics calculation algorithms. Results. Distributed algorithms for calculating graph clustering goodness metrics are proposed and tested. Conclusion. The results can be used to analyze the quality of the partitioning of large graphs that obtained using an arbitrary distributed clustering algorithm.

Urban Railway Bridge Fast Evaluation Based on Cloud Computing

2011 ◽  
Vol 71-78 ◽  
pp. 4501-4505
Author(s):  
Ming Chen ◽  
Wan Zhou
Keyword(s):  
Neural Networks ◽  
Cloud Computing ◽  
Model Updating ◽  
Condition Assessment ◽  
Fe Model ◽  
Railway Bridge ◽  
Fast Evaluation ◽  
Railway Bridges ◽  
Computing Model ◽  
Bridge Condition Assessment

Although modern bridge are carefully designed and well constructed, damage may occur in them due to unexpected causes. Currently, many different techniques have been proposed and investigated in bridge condition assessment. However, evaluation efficiency of condition assessment has not been paid much attention by the researchers. A fast evaluation of the urban railway bridge condition based on the cloud computing is presented. In this paper dynamic FE model and Artificial neural networks technique is applied to model updating. The cloud computing model provides the basis for fast analyses. It was found that when applied to the actually railway bridges, the proposed method provided results similar to those obtained by experts, but can improve efficiency of bridge

scholarly journals Soft computing model for students’ evaluation in educational institute

2021 ◽  
Vol 1913 (1) ◽  
pp. 012137
Author(s):  
O K Chaudhari ◽  
Rajshri Gupta ◽  
T A Thakre
Keyword(s):  
Soft Computing ◽  
Computing Model ◽  
Educational Institute

Soft computing model for predicting the wear resistance of friction stir processed aluminum alloy AA5083

2021 ◽  
Author(s):  
K. Santhosh Kumar ◽  
R. Vaira Vignesh ◽  
G. Ajith Kumar ◽  
A. Abiram ◽  
R. Padmanaban
Keyword(s):  
Wear Resistance ◽  
Aluminum Alloy ◽  
Soft Computing ◽  
Friction Stir ◽  
Computing Model

Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things

2021 ◽  
Vol 68 ◽  
pp. 102779
Author(s):  
Khalid Haseeb ◽  
Ikram Ud Din ◽  
Ahmad Almogren ◽  
Imran Ahmed ◽  
Mohsen Guizani
Keyword(s):  
Internet Of Things ◽  
Sustainable Cities ◽  
Computing Model

Modelling of municipal solid waste gasification using an optimised ensemble soft computing model

Fuel ◽  
2021 ◽  
Vol 289 ◽  
pp. 119903
Author(s):  
Navid Kardani ◽  
Annan Zhou ◽  
Majidreza Nazem ◽  
Xiaoshan Lin
Keyword(s):  
Municipal Solid Waste ◽  
Solid Waste ◽  
Soft Computing ◽  
Computing Model ◽  
Waste Gasification
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