基于神经网络的轻质原材料砌块抗压强度预测

D. Acevedo, T. Torres, Z.L.Y. Gomez
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引用次数: 4

摘要

本文提出了一个神经模型来预测使用轻质原材料固化长达28天的建筑块的抗压强度。原材料的组合对于开发具有特定性能和可接受的机械强度的低成本建筑模块至关重要。该模型避免了测试新的建筑材料混合物,并提供了以低成本设计新组件的新选择
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Compressive Strength Prediction of Building Blocks from Lightweight Raw Materials: A Neural Network Approach
This paper presents a neural model to predict the compressive strength of building blocks using lightweight raw materials cured up to 28 days. The combination of raw materials is crucial to develop low cost building blocks with specific properties and acceptable mechanical strength. The model avoids testing a new mixture of building materials and provides new alternatives to design new components at low cost
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