Predicting the cooling capacity of green buildings using probabilistic neural network models

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Authors

Publication Details

Journal
International Journal of Environment and Pollution
Published
2025-01-01
DOI
https://doi.org/10.1504/ijep.2025.10072094
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting the cooling capacity of green buildings using probabilistic neural network models

Hua Zheng, P. Jeremy Wang
International Journal of Environment and Pollution
Building Energy and Comfort Optimization
article

Predicting the cooling capacity of green buildings using probabilistic neural network models

Hua Zheng, P. Jeremy Wang
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Environment and PollutionVol. 1(1)
Sustainable cities and communities
Openalex Percentile: Top 85%
Building Energy and Comfort Optimization
DOIOpen Access PDFOpenAlex
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Predicting the cooling capacity of green buildings using probabilistic neural network models — Hua Zheng, P. Jeremy Wang · International Journal of Environment and Pollution (2025) | TGRS Research Map | TGRS