by
Bozokalfa, Gökhan.
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"Ann" artifical neural networks and fuzzy logic models for cooling load prediction/ Bozokalfa
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İnayet, Mehmet Göktuğ, author.
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satisfying the energy demand of a building for heating-cooling operations. This feature of energy piles
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by
Ouedraogo, Kiswendsida Elias, author.
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cooling load. The study revealed that the borehole efficiency is 37%. Also, it enhanced the solar fraction
by
Özcan, Zeynep, author.
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the reserved area is not sufficient to meet the cooling load, the cooling process was excluded
by
Yenigün, Onur, author.
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heat load can be kept under an allowable temperature limit. Vascular channels in which coolant fluid
by
Kanargı, Ömer Buğra.
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conditions, the performances of the VSC control algorithms are evaluated under transient cooling load
by
Yıldız, Yusuf.
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coefficient of the glazing based on the orientation have the most influence on annual cooling load of low-rise
by
Gediz, Gamze.
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Program.Additionally, energy storage method is recommended for the cooling plant, which will meet the cooling load
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