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Green Roof Optimization Using Multi Objective Optimization with Genetic Programming Based Artificial Neural Network | IEEE Conference Publication | IEEE Xplore

Green Roof Optimization Using Multi Objective Optimization with Genetic Programming Based Artificial Neural Network


Abstract:

In recent years, the greenhouse gases are rising increasingly and the extreme usage of vestige energy resources helped in the green spaces development including green roo...Show More

Abstract:

In recent years, the greenhouse gases are rising increasingly and the extreme usage of vestige energy resources helped in the green spaces development including green roof systems, which is an important focus in urban areas. In existing, green roof designs are optimized with different methods such as Fuzzy framework-based optimization. However, the framework is a single object based optimization so, the framework struggle to handle multi conflict objects. To overcome this issue, Multi Objective Optimization with Genetic Programming based Artificial Neural Network (MOO-GPANN) is proposed to optimize the green roof design. Initially, the input data is taken from NYC Green Roof Footprints (NYC-GRF) dataset and further processed into feature extraction with fuzzy if-then rule. Then, the optimal features are selected by using Multi Objective Optimization (MOO) based on ranking diversity. Finally, the prediction done by using Genetic Programming based Artificial Neural Network (GPANN). From the results, the proposed MOO-GPANN model gave better results than existing Adaptive Neuro-Fuzzy Inference System (ANFIS) by providing results for the objective functions including energy consumption (PMV), Heating Load (HL), Cooling Load (CL) and comfort levels (CFL) respectively.
Date of Conference: 22-23 November 2024
Date Added to IEEE Xplore: 05 February 2025
ISBN Information:
Conference Location: Kalaburagi, India

I. Introduction

In recent days, green roof systems are involving the integration of vegetation on building rooftops, which gained significant attention as a sustainable solution to urban environmental challenges [1]. These systems suggest multiple benefits, including improved energy efficiency, storm water management, and enhanced biodiversity in urban areas. By absorbing rainwater, green roofs reduce runoff, lowering the risk of flooding and reducing the burden on urban drainage systems. Additionally, plants help insulate buildings, that reducing heating and cooling demands, which leads to significant energy savings and a decrease in urban heat island effects [2]. Green roofs also provide aesthetic value and contribute to the well-being of urban residents by creating green spaces in otherwise built-up areas. As cities continue to grow and face environmental challenges, optimizing the design of green roof systems which focuses in architectural and environmental research. Optimization involves selecting suitable plant species, designing appropriate substrate layers, and considering factors through climate, building structure, and maintenance needs [3]. Advances in materials, engineering, and plant science are crucial for developing efficient, cost-effective green roofs that implemented on a larger scale in urban planning. Selecting appropriate plant species that flourish in diverse climate conditions while requiring minimal maintenance. Structural considerations are critical, as green roofs add weight to buildings and designed to support the load [4].

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References

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