title: An activity-based cost estimation model using artifi-cial neural networks for the shipbuilding industry in Egypt
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: ÐÐ¾Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¾ÑÐµÐ½ÐºÐ¸ Ð·Ð°ÑÑÐ°Ñ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð° Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÑÐ´Ð¾ÑÑÑÐ¾Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¾ÑÑÐ°ÑÐ»Ð¸ ÐÐ³Ð¸Ð¿ÑÐ°
Creators: name: Mohamed, Marvan
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2018
Subjects: Ð¡ÑÐ´Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ
ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÑÐµÐ½Ð¾Ð¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°Ð½Ð¸Ðµ
ÐÐ³Ð¸Ð¿ÐµÑ

description: Global competition in the shipbuilding industry is continuously increasing and this has made companies working in this sector striving to achieve competitive ad-vantage. There are various factors can contribute to helping companies to obtain competitive advantage such as skilled labor, marketing strategies, high technology and cost management. Shipbuilding cost estimation is considered an essential element of shipbuilding cost management and also it is one of the fields where it is possible to gain a com-petitive advantage. With reliable methods which can cope with the increasing com-plexity of designs and the high demands in terms of quick and accurate customer responses, companies in the shipbuilding industry will be able to be more competitive. The method presented in this thesis is an Activity-Based cost estimation model ("ABC").This thesis is concerned with the development of an Activity Based Costing (ABC) system for the application in the shipbuilding industry. It involves the application of Artificial Neural Networks (ANNs) using back-propagation training algorithm with the intention of determining costs more accurately. In this research work, a new neural network model was set for establishing a relationship between cost of the activities and the indirect costs. The proposed neural network has been trained using back propagation training algorithm and was applied on the data of twenty-two different ships have been produced by different shipyards and then five new different ships were added to generate estimated cost and eventually the results have been compared with the actual cost of those five new ships.
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