Guess the time of implementation of residential construction projects using neural networks ANN

AL-Zubaidi, Elaf Dheyaa Abdulridha; Yas, Ali Hashim; Abbas, Hayder Fadhil

doi:10.21533/pen.v7i3.680

Cited by 4 publications

(2 citation statements)

References 12 publications

(27 reference statements)

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“…Energy consumption is also a separate factor. Excessive operations applied while producing insulation material increase the cost as well as of residential construction project duration [92]. Therefore, the price of the material is increasing in the market.…”

Section: Resultsmentioning

confidence: 99%

Performances Study of Natural and Conventional Building Insulation Materials

Yıldız¹,

Duraković²,

Almisreb³

2021

International Journal on Advanced Science, Engineering and Information Technology

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This research aims to investigate the performances of thermal insulation materials using a comparative analysis. Particularly, the performances of natural insulation materials are compared with performances of non-renewables (petrochemical and inorganic), such as thermal conductivity, thermal diffusivity, global warming potential, and cost. In the past twenty years, the interest for the research on building energy demand reduction has been increased rapidly. Buildings were identified as a significant contributor to global energy consumption and global warming through the heating and air-conditioning systems. The literature observed that building energy demand takes up to 40% of the global energy consumption. Trends in addressing this issue are based on better thermal insulation of building envelope or using more energy-efficient materials. To carry out this research, the data were collected based on published research and comparatively analyzed. It was found that natural insulation materials have a significantly lower impact on global warming, longer useful lifetime, competitive thermal properties, better fire resistance, and favorable cost. Future trends and developments in reducing building energy demand would rely on sustainability. Sustainability is based on renewable natural resources, including renewable insulation materials, but if combined with significant participation of PCMs for latent heat energy storage, it will provide much better results. To get sustainable technologies applicable in full scale in the future, the overall problem has to be investigated, including user training and addressing the future workforce's challenges.

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Section: Resultsmentioning

confidence: 99%

Performances Study of Natural and Conventional Building Insulation Materials

Yıldız¹,

Duraković²,

Almisreb³

2021

International Journal on Advanced Science, Engineering and Information Technology

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“…Bhokha and Ogunlana [123] used a three-layered back-propagation-based ANN technique to predict the construction schedule at the predesign stage when very little project information is available. The application of an artificial neural network (ANN) to forecast the schedule of a residential construction project from the pre-design stage to completion was performed by Al-Zubaidi et al [124]. The linear regression and multilayer perceptron neural network model was developed by Petruseva et al [125] to predict the duration of a construction project using time and cost construction data of contracted and actual values.…”

Section: Sustainable Construction Managementmentioning

confidence: 99%

Artificial Neural Networks for Sustainable Development of the Construction Industry

et al. 2022

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Artificial Neural Networks (ANNs), the most popular and widely used Artificial Intelligence (AI) technology due to their proven accuracy and efficiency in control, estimation, optimization, decision making, forecasting, and many other applications, can be employed to achieve faster sustainable development of construction industry. The study presents state-of-the-art applications of ANNs to promote sustainability in the construction industry under three aspects of sustainable development, namely, environmental, economic, and social. The environmental aspect surveys ANNs’ applications in sustainable construction materials, energy management, material testing and control, infrastructure analysis and design, sustainable construction management, infrastructure functional performance, and sustainable maintenance management. The economic aspect covers financial management and construction productivity through ANN applications. The social aspect reviews society and human values and health and safety issues in the construction industry. The study demonstrates the wide range of interdisciplinary applications of ANN methods to support the sustainable development of the construction industry. It can be concluded that a holistic research approach with comprehensive input data from various phases of construction and segments of the construction industry is needed for the sustainable development of the construction industry. Further research is certainly needed to reduce the dependency of ANN applications on the input dataset. Research is also needed to apply ANNs in construction management, life cycle assessment of construction projects, and social aspects in relation to sustainability concerns of the construction industry.

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Schedule and Cost Forecasting Model for Nuclear Power Plant Projects

Karatas¹,

Al-Sharif²

2020

Construction Research Congress 2020

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Guess the time of implementation of residential construction projects using neural networks ANN

Cited by 4 publications

References 12 publications

Performances Study of Natural and Conventional Building Insulation Materials

Performances Study of Natural and Conventional Building Insulation Materials

Artificial Neural Networks for Sustainable Development of the Construction Industry

Schedule and Cost Forecasting Model for Nuclear Power Plant Projects

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