Blockchain based Automated Construction Model Accuracy Prediction using DeepQ Decision Tree

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Blockchain services and operations by using node level
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Published: Feb 6, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i1.6060
Keywords:
Blockchain Technology, Chain Codes, Deep Learning, Decision Tree, Accuracy

Main Article Content

L. Megaan Leo
Professor , Department of ECE, Sathyabama institute of science and technology, Chennai, Tamilnadu, India
A. Jerrin Simla
Assistant professor, Department of CSE, Panimalar Engineering College, Chennai, Tamilnadu, India
J. Chenni Kumaran
Associate Professor, Division of Spatial Informatics, Department of CSE,Saveetha School of Engineering, Saveetha Institute of Medical and Technical Science, Chennai, Tamilnadu, India
AG. Noorul Julalha
Assistant Professor, Department of CSE, Rajalakshmi Institute of Technology, Chennai, , Tamilnadu, India
R. Bhavani
Assistant Professor ,Department of IT, St Joseph College of Engineering , Chennai, Tamilnadu, India

Abstract

A growth of Industry 4.0 standards are increasing day by day. Various research application and problem statements are coming to create multiple automation environments. Blockchain technology is the important evolution to produce dynamic and avoid intermediate middleware processing systems. In this paper we propose a blockchain based automated construction modelling and analysis system. Here we check the efficiency of the system by using collaboration, transparency, workflow and reliable data model. DeepQ based classification and prediction method is used to measure the accuracy index.  Decision tree algorithm is used to divide the process model and generate the chain codes. 1500 trained dataset and 750 dataset is taken from Revit construction model set and apply blockchain codes to process the dataset. The simulations are taken effectively and reach the accuracy as 96%.

Article Details

How to Cite
Leo, L. M. ., Simla, A. J. ., Kumaran, J. C. ., Julalha, A. N. ., & Bhavani, R. . (2023). Blockchain based Automated Construction Model Accuracy Prediction using DeepQ Decision Tree. International Journal on Recent and Innovation Trends in Computing and Communication, 11(1), 133–138. https://doi.org/10.17762/ijritcc.v11i1.6060
Issue
Vol. 11 No. 1 (2023): January (2023) Issue
Section
Articles

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