PREDIKSI OPTIMASI DIMENSI BALOK KOLOM BANGUNAN MASJID DENGAN METODE ARTIFIAL NEURAL NETWORK

J. Prasetiawan
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Abstract

Indonesia is the confluence of three of the world's major plates, therefore a lot of plate activity occurs so that earthquake intensity often occurs. The earthquake resulted in many casualties, this is because many building structures do not meet the requirements of earthquake-resistant buildings. The structure of mosque buildings in Lombok has many towering mosque towers. Many mosque buildings in Lombok do not apply the earthquake-resistant building principle, namely strong column weak beam, so that the average mosque building collapses is the soft story type. The research method used to optimize the dimensions of the columnar beam in this study there are two methods, namely optimization using SAP 2000 and then optimization using Artificial Neural Network (ANN) modeling. The empirical equations obtained are three equations, namely the equation of a beam, a square column and a circle column. The percentage of error that occurs in the use of the empirical formula is 0.88%, so that the equation can be used to perform dimensional prediction calculations with different variations.
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用人工神经网络方法对清真寺建筑柱梁尺寸预测
印度尼西亚是世界三大板块的交汇处,因此板块活动频繁,地震强度经常发生。这次地震造成了许多人员伤亡,这是因为许多建筑物的结构不符合建筑物的抗震要求。龙目岛的清真寺建筑结构有许多高耸的清真寺塔。龙目岛的许多清真寺建筑不适用抗震建筑原则,即强柱弱梁,因此一般的清真寺建筑倒塌是软层类型。本研究采用的柱状梁尺寸优化的研究方法有两种,即采用SAP 2000进行优化,然后采用人工神经网络(ANN)建模进行优化。得到的经验方程为3个方程,即梁方程、方柱方程和圆柱方程。在使用经验公式时发生的误差百分比为0.88%,因此可以使用该方程进行不同变化的量纲预测计算。
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