TY  - JOUR
T1  - Estimation of Time and Cost in Prefabrication Construction AID of ANN with SSO
AU - Ashok Manikandan, S. AU - Pazhani, K.C. 
JO  - Asian Journal of Information Technology
VL  - 16
IS  - 8
SP  - 650
EP  - 659
PY  - 2017
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2017.650.659
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2017.650.659
KW  - Prefabrication technology
KW  -construction
KW  -Enterprise Resource Planning (ERP)
KW  -Artificial Neural Network (ANN)
KW  -Social Spider Optimization (SSO)
KW  -India
AB  - Prefabrication technology (prefab is the practice of assembling components of a structure in a factory
or other manufacturing siteand then transporting the assembled components to the construction site where the
structure is to be located. The term is used to differentiate between the process of the conventional
construction practice, i.e., transporting the basic materials to the construction site. Cost and time savings
emerge to be the chief benefits which makes us adopt the new technique. The objective of the research is to
enclose an Artificial Neural Network (ANN) with the aid of optimization techniques. In order to predict the time
and cost performance parameters of the prefabrication technology process the ANN is utilized. There are
different types of optimization techniques such as Grey Wolf Optimization (GWO), Harmony Search (HS) and
Social Spider Optimization (SSO) algorithm which are utilized to arrive at the optimal weight of the ANN process.
The optimum results demonstrate the attained error values between the output of the experimental values and
the predicted values which are closely equal to zero in the designed network. It is gathered from the results that,
the minimum error of time performance and cost performance is 81.2 and 76.28% determined by the ANN as
attained by the Social Spider Optimization (SSO) algorithm.
ER  -