Minimizing energy consumption is a key issue from both an environmental and economic perspectives for railways systems; however, it is also important to reduce infrastructure construction costs. In the present work, an artificial neural network (ANN) was trained to estimate the energy consumption of a metropolitan railway line. This ANN was used to test hypothetical vertical alignments scenarios, proving that symmetric vertical sinusoid alignments (SVSA) can reduce energy consumption by up to 18.4% compared with a flat alignment. Finally, we analyzed the impact of SVSA application on infrastructure construction costs, considering different scenarios based on top–down excavation methods. When balancing reduction in energy consumption against infrastructure construction costs between SVSA and flat alignment, the extra construction costs due to SVSA have a return period of 25–300 years compared with a flat alignment, depending on the soil type and construction method used. Symmetric vertical sinusoid alignment layouts are thus suitable for scattered or soft soils, up to compacted intermediate geomaterials.

中文翻译：

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对称垂直正弦曲线对基础设施建设成本的影响：使用人工神经网络优化都会铁路的能耗

从铁路系统的环境和经济角度来看，最大限度地降低能耗是一个关键问题。但是，降低基础设施建设成本也很重要。在目前的工作中，训练了人工神经网络（ANN）来估算都市铁路线的能耗。该ANN用于测试假设的垂直对齐方案，证明与垂直对齐相比，对称垂直正弦对齐（SVSA）最多可减少能耗18.4％。最后，我们基于自上而下的开挖方法，考虑了不同方案，分析了SVSA应用对基础设施建设成本的影响。当在SVSA和平面布置之间的能耗减少与基础设施建设成本之间取得平衡时，SVSA带来的额外建设成本与平整相比有25-300年的回收期，具体取决于所使用的土壤类型和施工方法。因此，对称的垂直正弦曲线对齐布局适用于散布或软土，直至压实的中间土工材料。