The application of ANN systems is growing rapidly in the financial and manufacturing sectors. Neural network systems offer several advantages over traditional methods for the prediction of construction projects' cost and duration. Therefore, a neural network that can help project estimators to decide the preliminary cost of a highway construction project is proposed here. Effective cost estimating depends heavily on experience. Accurate preliminary cost estimates should lead to a better construction market, better informed and confident client, efficient control, and a better return on investment
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The application of ANN systems is growing rapidly in the financial and manufacturing sectors. Neural network systems offer several advantages over traditional methods for the prediction of construction projects' cost and duration. Therefore, a neural network that can help project estimators to decide the preliminary cost of a highway construction project is proposed here. Effective cost estimating depends heavily on experience. Accurate preliminary cost estimates should lead to a better construction market, better informed and confident client, efficient control, and a better return on investment
Assist Prof. Dr. Faiq M. SarhanPh.D. Civil engineering, Construction Management, Baghdad University–Iraq.Reviewer scientifically supported in the KSCE Journal of Civil EngineeringEditorial Board Member of Civil Engineering and Urban Planning: An International Journal.Member of PMI(Project Management Institute)Professional trainer of MS-Project
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The application of ANN systems is growing rapidly in the financial and manufacturing sectors. Neural network systems offer several advantages over traditional methods for the prediction of construction projects' cost and duration. Therefore, a neural network that can help project estimators to decide the preliminary cost of a highway construction project is proposed here. Effective cost estimating depends heavily on experience. Accurate preliminary cost estimates should lead to a better construction market, better informed and confident client, efficient control, and a better return on investment 288 pp. Englisch. N° de réf. du vendeur 9783659546082
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The application of ANN systems is growing rapidly in the financial and manufacturing sectors. Neural network systems offer several advantages over traditional methods for the prediction of construction projects' cost and duration. Therefore, a neural network that can help project estimators to decide the preliminary cost of a highway construction project is proposed here. Effective cost estimating depends heavily on experience. Accurate preliminary cost estimates should lead to a better construction market, better informed and confident client, efficient control, and a better return on investmentVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 288 pp. Englisch. N° de réf. du vendeur 9783659546082
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The application of ANN systems is growing rapidly in the financial and manufacturing sectors. Neural network systems offer several advantages over traditional methods for the prediction of construction projects' cost and duration. Therefore, a neural network that can help project estimators to decide the preliminary cost of a highway construction project is proposed here. Effective cost estimating depends heavily on experience. Accurate preliminary cost estimates should lead to a better construction market, better informed and confident client, efficient control, and a better return on investment. N° de réf. du vendeur 9783659546082
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Taschenbuch. Etat : Neu. Project Management and Artificial Neural Networks | Fundamental and Application | Faiq M. Sarhan Alzwainy (u. a.) | Taschenbuch | 288 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659546082 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 104914576
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