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      OPTIMIZATION OF BUILDING MATERIAL SELECTION FOR ENERGY SAVING IN COMMERCIAL BUILDINGS IN DIFFERENT CLIMATIC CONDITIONS

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          ABSTRACT

          Most engineers predict future building energy consumption via simulation programs in the pre-design phase. In this process, many simulation steps have to be repeated to predict building energy consumption. The authors in this article proposed another way to select optimal building materials for saving commercial building energy in the U.S. using soft computing methods.

          To achieve the research goal, reliable public data that is provided by the U.S. Energy Information Administration was used. The data contain numerous energyrelated characteristics of buildings including gas, electricity, types of materials, and climate conditions of 6,700 commercial buildings located in the U.S. This study utilized two methods to find out optimal building materials for saving energy. First, the Principle Component Analysis was used to determine which building characteristics among over 400 characteristics have the greatest impact on gas and electricity consumption. Second, Association Rule Mining was used to extract combinations of optimal building materials. Since a building consists of a combination of various materials, energy simulation should predict for multiple factors rather than a single factor. The use of these methods would greatly reduce resources, such as limited budget and time, during the simulation process.

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          Climate change and human health: present and future risks.

          There is near unanimous scientific consensus that greenhouse gas emissions generated by human activity will change Earth's climate. The recent (globally averaged) warming by 0.5 degrees C is partly attributable to such anthropogenic emissions. Climate change will affect human health in many ways-mostly adversely. Here, we summarise the epidemiological evidence of how climate variations and trends affect various health outcomes. We assess the little evidence there is that recent global warming has already affected some health outcomes. We review the published estimates of future health effects of climate change over coming decades. Research so far has mostly focused on thermal stress, extreme weather events, and infectious diseases, with some attention to estimates of future regional food yields and hunger prevalence. An emerging broader approach addresses a wider spectrum of health risks due to the social, demographic, and economic disruptions of climate change. Evidence and anticipation of adverse health effects will strengthen the case for pre-emptive policies, and will also guide priorities for planned adaptive strategies.
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            A decision tree method for building energy demand modeling

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              A review on modeling and simulation of building energy systems

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                Author and article information

                Journal
                jgrb
                Journal of Green Building
                College Publishing
                1943-4618
                1552-6100
                Summer 2022
                10 October 2022
                : 17
                : 3
                : 89-106
                Author notes
                [1.]

                Department of Construction Management and Interior Design, Ball State University, Applied Technology Building, Muncie, Indiana, 47306, United States of America

                [3.]

                Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

                2. * Corresponding author—e-mail: jjson@ 123456bsu.edu
                Article
                jgb.17.3.89
                10.3992/jgb.17.3.89
                acff3cde-77bd-4752-9e78-fc4e54c3df06
                History
                Page count
                Pages: 18
                Categories
                RESEARCH ARTICLES

                Urban design & Planning,Civil engineering,Environmental management, Policy & Planning,Architecture,Environmental engineering
                green building materials,data mining,building energy consumption

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