Optimal Design and Modeling of Sustainable Buildings Based on Multivariate Fuzzy Logic

Abstract

The exemplary design of green buildings incorporates multiple correlated parameters that should be optimally selected and updated to ensure effective energy management and sustainable impact of building architecture on the ecosystem. In this paper, the adaptive modeling and development of such sustainable buildings with several unpredictable and qualitative attributes is implemented with multiple-input multiple-output (MIMO) fuzzy control system. The outputs of the proposed fuzzy corroborated sustainable building paradigm comprise of specific characteristics employed for assessing the optimal performance, viz. energy efficiency, user satisfaction, resources optimization, and environment quality. These diverse system criteria measured using the proposed fuzzy optimization model are plotted against their actual theoretical values for each data case. Furthermore, the sample dataset for the proposed sustainable building model is validated through simulation results in terms of mean absolute error and logarithmic quotient error in the estimation of various fuzzy output variables evolving with the dataset size.

A Fuzzy Logic Concept for Predicting the Seasonal Thermal Performance of Building Envelopes Based on Structural and Geographical Parameters

“…The inherent uncertainty contained in the results of energy audits for real-life structures has been expressed successfully with help of fuzzy set theory in many studies focusing on assessing the energy performance of buildings [11][12][13]. Fuzzy logic has also been successfully employed for the energy management of buildings, as seen in [14][15][16][17][18]. It should be noted that the use of fuzzy set theory is quite common in solving engineering problems which are more theoretical than the basic fuzzy logic control applications [19][20][21].…”

Engineering and Sustainable Challenges: Latest Advances in Computing and Systemic Tools

“…However, low-impact alternatives can be adapted to existing urban areas, which can address a range of issues that affect the population. For example, such alternatives can provide food locally, extend the useful life of sewage and drainage systems by capturing and reusing water, mitigate floods, reduce travel times in urban areas, and reduce the adverse effects of heat islands, among other benefits [22][23][24][25][26]. Multi-objective optimization models are also used to achieve more sustainable urban growth, seeking economically feasible solutions that can be adapted on an increasingly larger scale [27].…”