Artificial neural network for outlining and predicting environmental sustainable parameters

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

RAHBAR MORTEZA; MAHDAVINEJAD MOHAMMAD JAVAD; BEMANIAN MOHAMADREZA; DAVAIE MARKAZI AMIR HOSSEIN

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF SUSTAINABLE ARCHITECTURE AND URBAN DESIGN Year:2020 | Volume:7 | Issue:2 Page(s): 169-182

Download Full-Text

Persian Verion

View:

1,055

Download:

Cites:

Information Journal Paper

Title

Artificial neural network for outlining and predicting environmental sustainable parameters

Author(s)

RAHBAR MORTEZA | MAHDAVINEJAD MOHAMMAD JAVAD | BEMANIAN MOHAMADREZA | DAVAIE MARKAZI AMIR HOSSEIN | Issue Writer Certificate

Keywords

Artificial intelligence (AI) Artificial Neural Network (ANN)

Contemporary architecture

Data-driven method

High-performance architecture

Abstract

This research is to study the capabilities of artificial neural network (ANN) for predicting solar radiance in an urban context in order to materialize the concept of High-performance architecture. Literature review of the research implies that artificial intelligence (AI) is going to be a new emerging tool to contribute to High-performance architecture, as well as a way of thinking for a significant paradigm shift in environmental sustainability. In the first step, a rule-based method is applied to generate the dataset. In the next step, three different ANN models with different architectures are defined. These models are trained with the generated dataset and regarding the defined algorithm architecture, different results are predicted. The results indicate the precision of each model in predicting the amount of received solar radiation in a new sample location. Finally, these results are compared and the best ANN architecture is selected. The proposed model in this research could be generalized to other similar simulations and it has two main applications. First, it could predict the target parameter instantly without intensive computation. Secondly, it could fit a function for simulating a sustainable parameter only with the given input and output dataset and without needing to know any specific rules for the simulation. The results conclude that AI might be introduced as a comprehensive methodology for sustainable design in Contemporary architecture. However, the research shows capability of ANN for outlining and predicting environmental sustainable parameters particularly.

Cites

No record.

References

No record.

Cite

APA: Copy

RAHBAR, MORTEZA, MAHDAVINEJAD, MOHAMMAD JAVAD, BEMANIAN, MOHAMADREZA, & DAVAIE MARKAZI, AMIR HOSSEIN. (2020). Artificial neural network for outlining and predicting environmental sustainable parameters. JOURNAL OF SUSTAINABLE ARCHITECTURE AND URBAN DESIGN, 7(2 ), 169-182. SID. https://sid.ir/paper/265562/en

Vancouver: Copy

RAHBAR MORTEZA, MAHDAVINEJAD MOHAMMAD JAVAD, BEMANIAN MOHAMADREZA, DAVAIE MARKAZI AMIR HOSSEIN. Artificial neural network for outlining and predicting environmental sustainable parameters. JOURNAL OF SUSTAINABLE ARCHITECTURE AND URBAN DESIGN[Internet]. 2020;7(2 ):169-182. Available from: https://sid.ir/paper/265562/en

IEEE: Copy

MORTEZA RAHBAR, MOHAMMAD JAVAD MAHDAVINEJAD, MOHAMADREZA BEMANIAN, and AMIR HOSSEIN DAVAIE MARKAZI, “Artificial neural network for outlining and predicting environmental sustainable parameters,” JOURNAL OF SUSTAINABLE ARCHITECTURE AND URBAN DESIGN, vol. 7, no. 2 , pp. 169–182, 2020, [Online]. Available: https://sid.ir/paper/265562/en

Related Journal Papers