With the rapid advancement of machine learning (ml) technologies, their innovative applications in enhancing building energy efficiency are increasingly prominent. Achieving climate neutrality requires reducing energy consumption and co2 emissions in the building sector, which has prompted increasing attention towards nearly zero energy, zero. Building energy conservation plays an important role in reaching the peak of carbon emissions before 2030, which was committed by the chinese government in the paris agreement.
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This review aimed to critically assess the effectiveness of leed certification in enhancing the energy performance of buildings.
Buildings account for approximately 40% of global.
Amid global efforts to mitigate greenhouse gas emissions, improving the energy efficiency of buildings has emerged as a strategic priority. A prerequisite for decreasing the intensification of energy in buildings is to evaluate and understand the influencing factors of building energy performance (bep). Building energy systems (bess) are essential for modern infrastructure but face significant challenges in equipment diagnosis, energy consumption prediction, and operational.
