Use of Artificial Neural Network in Design of Fly Ash Blended Cement Concrete Mixes

Abstract

Cement concrete is the most important construction material which is non-homogeneous in nature. Its strength depends on properties of its many constituent materials are diverse in nature. It is important to fix up exact proportions of these materials beforehand so that needed strength in concrete is obtained later on. Sufficient time is needed to check it by making trial mixes of concrete after fixing up the proportions by theoretical calculations and testing these trial mixes after 28 days. In this duration concreting work may be held up in the absence of a final approved mix in terms of quantities of various constituents of concrete. Use of artificial neural networks (ANNs) for the checking of design composition of fly ash blended cement concrete mixes which were designed as per Indian standard guidelines has been made. Prediction of strength of such mixes at a later date by ANN has also been explored in this study. Prediction results of ANNs come close to experimental values and reinforce the utility of ANNs in the area of use of civil engineering materials for improving efficiency in construction

Forecasting Construction Cost Index through Artificial Intelligence

“…The time series method predicts future values based on past data trends using time as the independent variable [18]. It consists of methods that recognize the fundamental setting of the information and make precise estimates.…”

“…Quantitative methods use computational techniques such as ANN, which simulates human brain learning to yield reliable results with manageable inputs. Various researchers in construction have used ANN for cost estimation, such as predicting highway construction cost increments, tender prices, and cash flow forecasting [17,18]. ANN is suitable for long-term index prediction as it is not solely reliant on past data.…”