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Utilization of Genetic Programming to Establish Demand Forecast in Taiwan International Flights

机译:基因编程利用在台湾国际航班中建立需求预测

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Accurately prediction is the most important way to cost down for airlines. The study was focused on build up forecast model of five Taiwan international flights included Bali, Bang Kong, Ho Chi Minh City, Kuala Lumpur, and Singapore. Genetic programming was adopted to establish simulation models, and Mean Absolute Percent Error (MAPE) also was used to evaluate the performance of those models. The ten years of historical passenger's data was collected and analysis, and finally the demand forecast of five flights in 2010 would be conducted. The validations MAPE of models were lower than 10% expect Bali flights. Based on experience of traditional statistic method included linear regression and time series, the ability of Genetic programming models were excellent. The forecast error of Bali flights were 11% and it may be caused by a series accident. On the basis of above results, Genetic programming could be the feasible approach for prediction of five flights in Taiwan. In addition, the passengers to Singapore would substantially increase in 2010-2011, and the issue is worthy to further study for airlines and government.
机译:准确预测是为航空公司降低的最重要方式。该研究专注于五大台湾国际航班的建立预测模型包括巴厘岛,班康,胡志明市,吉隆坡和新加坡。采用遗传编程来建立模拟模型,并且平均值百分比误差(MAPE)也用于评估这些模型的性能。收集和分析了十年的历史旅客数据,最后将进行2010年五次航班的需求预测。 Mape Mape Mape的验证低于10%,期望巴厘岛航班。基于传统统计方法的经验包括线性回归和时间序列,遗传编程模型的能力优异。巴厘岛航班的预测误差为11%,可能是由串联事故引起的。在上述结果的基础上,遗传编程可能是台湾五次航班预测的可行方法。此外,乘客到新加坡将大幅增加2010 - 2011年,而且该问题值得进一步研究航空公司和政府。

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