Using generalized regression neural network (GRNN) for mechanical strength prediction of lightweight mortar

• Main Authors: Razavi, S.V., Jumaat, Mohd Zamin, Ahmed, E.S.H., Mohammadi, P.
• Format: Article
• Published: 2012
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/5868/; http://www.scopus.com/inward/record.url?eid=2-s2.0-84869817201&partnerID=40&md5=5d688640273b8baa43d9c863e49eab7f
• Institution: Universiti Malaya

In this paper, the mechanical strength of different lightweight mortars made with 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 and 100 percentage of scoria instead of sand and 0.55 water-cement ratio and 350 kg/m3 cement content is investigated. The experimental resul...