Cost Estimation for Modernization of Metro Terminal Stations using ANN Technique

A. Khalil
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Abstract

The current situation of Cairo metro stations, especially terminal stations and its surrounding areas, has bad financial revenue and bad effect on environment. It is a major factor in increasing of noise, traffic jam and air pollution, in addition to, spreading of street vendors, collecting of random parking around these terminal stations. Thus, this paper proposed a methodology helping to apply multilateral investments in metro terminal stations for getting extra profits and decreasing the bad environmental effect of terminal stations and its surrounding areas. Hence, Helwan-Metro station on line 1 has been considered as a case study. Number of passengers at peak time, their ages, and their destinations, have been considered by making a field survey and a questionnaire. After collecting data and finalizing the surveying questionnaire, primary studies were done to modify and introduce a new proposal for Helwan-Metro station. The initial cost of the proposed project is predicted by using Artificial Neural Network technique using Just NN software. The investment feasibility achieved by consideration of Life Cycle Cost analysis and calculation of Net Present Value (NPV) of the proposed project.
基于人工神经网络技术的地铁终点站现代化成本估算
开罗地铁车站,尤其是终点站及其周边地区的现状,不仅财政收入不佳,而且对环境的影响也很严重。这是一个主要因素,噪音增加,交通堵塞和空气污染,此外,摊贩的蔓延,收集随机停车在这些终点站周围。因此,本文提出了一种有助于在地铁终点站应用多边投资的方法,以获得额外的利润,并减少终点站及其周边地区的不良环境影响。因此,1号线赫尔湾地铁站被认为是一个案例研究。通过实地调查和问卷调查,考虑了高峰时段的乘客人数、年龄和目的地。在收集数据和完成调查问卷后,对赫尔万地铁站的新方案进行了初步研究。采用人工神经网络技术,利用Just NN软件对拟建工程的初始成本进行预测。通过对拟投资项目的全生命周期成本分析和净现值(NPV)计算,得出投资的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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