Genetic Algorithms Application in Urban Morphology Generation

elzeni, mostafa; elmokadem, ashraf; Badawy, Nancy Mahmoud

doi:10.21608/pserj.2021.87367.1129

Cited by 6 publications

(2 citation statements)

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“…Subsequently, 21 st -century advancements brought along the Fourth Industrial Revolution, and the focus has shifted to big data and AI applications (Abo El-Einen et al, 2015;Arfanuzzaman, 2021;Megahed, 2017;Megahed et al, 2022). As a multidisciplinary phenomenon, AI can be used for forecasting power demand and generation, optimizing the maintenance and use of energy assets, gaining a better understanding of energy usage patterns, and making systems more stable and efficient (Elzeni et al, 2021;Hassan et al, 2022;Williams, 1983). AI can also lighten the load on humans by partially automating decision-making, scheduling, and controlling multiple devices (Ahmad et al, 2022;Antonopoulos et al, 2020;Chan et al, 2020;Chan and Zhang, 2019;Megahed, 2015).…”

Section: Ai Technology and Applicationsmentioning

confidence: 99%

Improvingurban Energyresiliencewith an Integrative Framework Based on Machine Learningmethods

Hassan

Megahed²

2022

A&J

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Introduction:Climate change and global warming are among the greatest challenges facing the world today. A newconcept, known as urban resilience, has been developed in response. There are various approaches to urban resilience. Among them, is the urban energy resilience (UER) approach, which poses a considerable challenge. Machine learning (ML), as an application of artificial intelligence (AI), provides powerful and affordable computing resources, large-scale datamining, advanced algorithms, and real-timemonitoring. However, veryfewstudies have investigated howsuch aspectscan be integrated into urban resilience in general, and UER in particular. Purpose of the study: The study develops an integrative framework that can improve UER, based on ML methods. Methodology: We carried out a bibliometric analysisand a systematic review of UER in accordance with AI concepts, models, and applications. Results:The findings of this study were used to create an integrative framework, based on three hierarchical phases, which effectively addressed the main capabilities of UER, identified its priorities, and shed light on how ML can benefit UER as a whole. Novelty:The framework developed in this study also offers insights in integrating ML methods into UER as strategically as possible, especially in the context of climate change and urban energy systems. This framework can serve as reference for specialistsand decision-makers aiming to expand AI and ML applications to optimize UER.

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Section: Ai Technology and Applicationsmentioning

confidence: 99%

Improvingurban Energyresiliencewith an Integrative Framework Based on Machine Learningmethods

Hassan

Megahed²

2022

A&J

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“…The building and construction industry consumes 30 to 40 % of all primary energy worldwide. Building integrated photovoltaic (BIPV) systems and green facades are significant advancements in achieving sustainable building design and energy efficiency for buildings, and enhance the changed nature of cities [4,[7][8][9] In the energy field, Egypt receives 3450 hours of solar radiation annually, making photovoltaic (PV) electricity generation the most practical option [10]. Also, Diverse designs of BIPV products have become available on the market in recent years, including silicon-based solar cells, thin films, dye-sensitized solar cells, and organic solar cells, which support a wide range of architectural integration options and can be used on various types of buildings to produce better technical and aesthetic effects [11][12][13][14] On the other hand, a green facade is a key strategy to reduce air and surface temperatures [15], which increases cooling demands in summer.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Performance of Indoor daylighting, and Thermal Performance in Residential Buildings Using Productive Façades

Nashaat

2023

Port-Said Engineering Research Journal

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Productive Facade (PF) is a multi-functional system used in sustainable and productive cities, it is the integration of farming and Photovoltaics PV cells in façade design. Conversely, buildings could play a serious role in energy and food production while transforming cities from consumers to producers. Therefore, this paper reviews the current literature to propose a design strategy for PF. Then, the paper introduces a comparative study between different alternatives of PF in residential buildings in arid desert hot climate. The study evaluates the performance of façade designs depending on PF. The alternatives are the base case, which lacked PV or farming, design 1, which has vertical farming and PV louvers, and design 2, which has a double-skin façade with inner farming and PV. Then, a comparison between measurements of the three alternative models is undertaken to understand how to adjust PF to improve interior daylighting, thermal comfort, energy generation, and food production. The findings confirm that applying PF improves the daylighting and solar heating performance inside a residential building. Especially, design 2 is more efficient than other alternatives and decreases building energy consumption.

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Layout optimization and multi-scenarios for land use: An empirical study of production-living-ecological space in the Lanzhou-Xining City Cluster, China

Yang

Chen

Qiao

et al. 2022

Ecological Indicators

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Genetic Algorithms Application in Urban Morphology Generation

Cited by 6 publications

References 0 publications

Improvingurban Energyresiliencewith an Integrative Framework Based on Machine Learningmethods

Improvingurban Energyresiliencewith an Integrative Framework Based on Machine Learningmethods

Investigating the Performance of Indoor daylighting, and Thermal Performance in Residential Buildings Using Productive Façades

Layout optimization and multi-scenarios for land use: An empirical study of production-living-ecological space in the Lanzhou-Xining City Cluster, China

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