In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. In the scope of the present study, 66 real RC buildings with four to ten storeys were subjected to performance analysis according to 23 parameters including concrete compressive strength thought to be effective on the performance of RC buildings. In addition, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). Thus, an output performance data group was created for the analyzed buildings, in accordance with the input data. Thanks to the ANN-based fast evaluation algorithm mentioned above and developed within the scope of the proposed project study, it will be possible to make an economic and rapid evaluation of four to ten-storey RC buildings in Turkey with great accuracy (about 80%). In the second step of the paper, concrete compressive strength has not been included to ANN-based algorithms and then the prediction accuracy of ANN has been found about 74%.Bu ?aly?mada mevcut betonarme (BA) yapylaryn performanslarynyn de?erlendirilmesi i?in yapay zeka tabanly analitik bir y?ntem geli?tirilmi?tir. ?aly?mada BA bina performansyny etkiledi?i dü?ünülen i?erisinde binanyn beton basyn? dayanymy da olan 23 parametreye g?re kat sayylary 4 ile 10 arasynda de?i?en 66 BA binanyn performans analizi yapylarak ilgili binalaryn olasy deprem durumunda TDY-2007'de belirtilen 4 kademeli performans seviyeleri bulunmu?tur. B?ylece ??zümü yapylan binalar i?in girdi verilerine ba?ly bir ?ykty performans veri grubu olu?turulmu?tur. Bu ?aly?mada geli?tirilen yapay zeka tabanly s?z konusu hyzly de?erlendirme algoritmasy sayesinde ülkemizdeki 4 ve 10 katly mevcut BA binalaryn, ?ok kysa bir sürede ve ekonomik bir ?ekilde de?erlendirilmesi yakla?yk %80 do?ruluk oranynda yapylmy?tyr. ?aly?manyn ikinci kysmynda ise yapay zeka tabanly algoritma verilerine beton parametresi dahil edilmemi? algoritma bu ?ekilde e?itilip test edilmi?tir. Beton parametresi olmaksyzyn elde edilen do?ruluk orany yakla?yk %74 oranynda bulunmu?tur.
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机译：在这项研究中，已开发了一种基于人工智能（基于ANN）的分析方法来分析钢筋混凝土（RC）建筑物的地震性能。在本研究的范围内，根据23个参数（包括对混凝土的抗压强度有效的混凝土抗压强度），对66栋4到10层的真实RC建筑物进行了性能分析。此外，这些建筑物在地震情况下可能表现出的性能水平是根据《土耳其地震法规-2007》（TEC-2007）中指定的4级性能水平确定的。因此，根据输入数据为分析的建筑物创建了输出性能数据组。由于上述基于ANN的快速评估算法并在拟议的项目研究范围内开发，因此可以对土耳其的四至十层RC建筑进行经济，快速的评估，准确性很高（约80％ ）。在本文的第二步中，基于ANN的算法未包含混凝土抗压强度，因此发现ANN的预测准确度约为74％。在Yapay zeka tabanly analitik bir y？ntem geli？tirilmi？tir中。 ？aly？mada BA bina performansyny etkiledi？idü？ünüleni？erisinde binanyn beton basyn吗？ Dayanymy da olan 23 parametreye g？re katsayylary 4 ile 10 arasynda de？i？en 66 BA binanyn performans analizi yapylarak ilgili binalaryn olasy deprem durumunda TDY-2007'de belirtilen 4 kademeli performans seviyeleri bulunmu？tur。 B？ylece ??zümüyapylan binalar i？在girdi verilerine ba？ly bir？ykty performans veri grubu olu？turulmu？tur中。 bu？aly？mada geli？tirilen yapay zeka tabanly s？z konusu hyzly de？erlendirme algoritmasy sayesindeülkemizdeki4到10 katly mevcut BA binalaryn，？ok kysa birsüredeve ekonomiky吗？ekildede？ ruluk oranynda yapylmy？tyr。 aly？manyn ikinci kysmynda ise yapay zeka tabanly algoritma verilerine beton parametresi dahil edilmemi吗？ algoritma bu？ekilde e？itilip测试edilmi？tir。 Beton parametresi olmaksyzyn elde edilen do？ruluk orany yakla？yk％74 oranynda bulunmu？tur。
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