Research on the Cost Estimation Method of Construction Project  Based on RBF Artificial Neural Network

Mo, Jun-wen; Yin, Yi; Wu, Hailong

doi:10.12783/dtetr/icmeit2018/23488

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The closer the KMO statistic is to 1, the stronger the correlation between variables. This method is used to test the validity of survey results (Mo & Wu, 2018). The test results are shown in Table 2.…”

Section: Experimental Environmentmentioning

confidence: 99%

The Integrated Development of the Manufacturing and Service Industries Facing Human-Computer Interaction Based on Deep Learning

Zhou

2023

Journal of Organizational and End User Computing

View full text Add to dashboard Cite

With the rapid development of modern technology and the economy, the global value chain is also constantly evolving, and the links between various industries are becoming closer. With the continuous optimization of the international situation and the support of Chinese policies, the integrated development of manufacturing and service industries is the general trend. This study proposes to use human-computer interaction to conduct in-depth research and analysis of the development relationship, influencing factors, and evolution direction between manufacturing and service industries in the perspective of deep learning. Firstly, based on the current development status of the two industries, the influencing factors of mutual evolution are summarized, including environment, market, technology, and management. Secondly, the computer is used to construct the evolution models of the two major industries. The simulation verification and evolution feature extraction are carried out.

show abstract

Section: Experimental Environmentmentioning

confidence: 99%

The Integrated Development of the Manufacturing and Service Industries Facing Human-Computer Interaction Based on Deep Learning

Zhou

2023

Journal of Organizational and End User Computing

View full text Add to dashboard Cite

show abstract

“…In terms of housing construction engineering prediction [39], "people seek the non-linear relationship between the quota index and the actual construction and installation engineering cost of final settlement, so as to establish the RBF artificial neural network estimation model, and verify and analyze the results, providing a new idea and method for engineering cost estimation". In the MATLAB environment, the selected cost factors are taken as the input vector of the model training sample set, and the main cost indicators are taken as the output vector.…”

Section: Rbf Neural Networkmentioning

confidence: 99%

Application of Artificial Neural Network in Chemical Separation Process

Wang

Zhu

2022

AJOCS

View full text Add to dashboard Cite

The chemical separation process is a necessary unit operation to obtain qualified purity products. The design and operation control of the separation device are very important. Due to the numerous parameters that affect the separation efficiency and product purity, it is very difficult to optimize by traditional methods. Artificial neural network (ANN) has strong fault tolerance because of its self-learning, self-organization, self-adaptive and strong nonlinear function approximation ability. ANN can be used to map the complex nonlinear relationship between dependent variables and independent variables, and can be used for the design and control of chemical separation devices. This paper summarizes the characteristics of artificial neural network and several important artificial neural network models, and discusses the application of artificial neural network in different chemical separation processes.

show abstract

Research on the Cost Estimation Method of Construction Project Based on RBF Artificial Neural Network

Cited by 2 publications

References 0 publications

The Integrated Development of the Manufacturing and Service Industries Facing Human-Computer Interaction Based on Deep Learning

The Integrated Development of the Manufacturing and Service Industries Facing Human-Computer Interaction Based on Deep Learning

Application of Artificial Neural Network in Chemical Separation Process

Contact Info

Product

Resources

About