What is it about?
This paper presents the proposal of an approach to the estimation of construction costs of sports fields which is based on neural networks. The general applicability of artificial neural networks in the formulated problem with cost estimation is investigated. An applicability of multilayer perceptron networks is confirmed by the results of the initial training of a set of various artificial neural networks. Moreover, one network was tailored for mapping a relationship between the total cost of construction works and the selected cost predictors which are characteristic of sports fields. Its prediction quality and accuracy were assessed positively. The research results legitimatize the proposed approach.
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Why is it important?
The results presented in this paper are part of a broad research, in which the authors participate, aiming to develop tools for fast cost estimates, dedicated to the construction industry. The main aim of this paper is to present the results of the investigations on the applicability of artificial neural networks (ANNs) in the problem of estimating the total cost of construction works in the case of sports fields as specific facilities. The authors propose herein a new approach based on ANNs for estimating construction costs of sports fields.
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This page is a summary of: ANN Based Approach for Estimation of Construction Costs of Sports Fields, Complexity, January 2018, Hindawi Publishing Corporation, DOI: 10.1155/2018/7952434.
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