Kniha Cost Prediction by Machine Learning Sevgi Zeynep Dogan Erdogmus

Cost Prediction by Machine Learning

Using Machine Learning Techniques for Early Cost Prediction of Structural Systems of Buildings

Jazyk: Angličtina
Vazba: Brožovaná
Dostupnost: U nakladatele na objednávku
Odesíláme za 17-27 dnů
1 407
It is desirable to predict construction costs in the §early design stage to make sure that target co...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2009
Stránek
124
EAN
9783639151749
Enbook ID
06823701
Hmotnost
201
Rozměry
150 x 220 x 7

Kompletní popis

It is desirable to predict construction costs in the §early design stage to make sure that target costs §are met. The book investigates the possibility of §predicting the cost of construction early in the §design phase by using machine learning techniques. §Therefore, artificial neural network (ANN) and case §based reasoning (CBR) prediction models were §developed in a spreadsheet-based format. An §investigation of the impacts of weight generation §methods on the ANN and CBR models was conducted. The §performance of the ANN model was enhanced by §experimenting with the weight generation methods of §simplex optimization, back propagation training, and §genetic algorithms while the CBR model was augmented §by feature counting, gradient descent, genetic §algorithms, decision tree methods of binary-dtree, §info-top and info-dtree. Cost data belonging to the §superstructure of low-rise residential buildings §were used to test these models. Both approaches were §found to be capable of providing high prediction §accuracy. A comparison of the ANN and CBR models was §made in terms of prediction accuracy, preprocessing §effort, explanatory value, improvement potentials §and ease of use.

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