FORECASTING SYSTEM FOR PASSENGER, AIRPLANE, LUGGAGE AND CARGO, USING ARTIFICIAL INTELLIGENCE METHOD - BACKPROPAGATION NEURAL NETWORK AT JUANDA INTERNATIONAL AIRPORT

Lady Silk Moonlight, A. S. Prabowo
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引用次数: 2

Abstract

Juanda International Airport is the third busiest airport, after Soekarno Hatta International Airport and Ngurah Rai International Airport. Because the number of Airplane, passengers, luggage and cargo at Juanda International Airport is increasing every year, it is important to improve infrastructure facilities and services, and all facilities at Juanda Airport. In this research, it was designed and built a forecasting system for Airplane, passenger, luggage and cargo. This research is expected to be a consideration in increasing the readiness of infrastructure and services, and all facilities at Juanda Airport. In addition, this system is also expected to be one of the decision supporting system for the management. This system uses one of the Artificial Intelligent methods, Backpropagation Artificial Neural Network. It is known in previous research that Backpropagation is a method of artificial neural networks with the best performance in pattern recognition, or forecasting. The forecasting system has two main processes, the training process and the forecasting process.
利用人工智能方法——反向传播神经网络,对旅客、飞机、行李和货物进行预报
朱安达国际机场是第三繁忙的机场,仅次于苏加诺哈达国际机场和Ngurah Rai国际机场。由于朱安达国际机场的飞机、乘客、行李和货物数量每年都在增加,因此改善基础设施和服务以及朱安达机场的所有设施非常重要。在本研究中,设计并构建了飞机、旅客、行李和货物的预测系统。这项研究预计将成为提高基础设施和服务以及朱安达机场所有设施准备程度的一个考虑因素。此外,本系统还有望成为企业管理层的决策支持系统之一。本系统采用了一种人工智能方法——反向传播人工神经网络。在以往的研究中,反向传播是人工神经网络在模式识别或预测中表现最好的一种方法。预测系统主要有两个过程:训练过程和预测过程。
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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