**2. Data Collection**

To predict the compressive strength (CS) of RHA, mathematical models are developed using a dataset of 192 data points from the vast literature review and existing studies on machine learning [12,13,35–39]. These data were collected through google Scopus. The constituents of concrete include RHA, OPC, aggregates, super plasticizer (SP), and water. The type of cement and curing methodology used in all the mixes is same. The CS of cubic specimens is converted into CS of cylinders by using 0.8 as a factor (as per BS 1881: Part 120:1983). The only output parameter in this study is compressive strength. The input parameters consist of main variables such as percentage of SP, curing age (CA), quantity of water used (W), amount of OPC (OPCP), quantity of aggregates (AGG), and amount of RHA (RHAP). Moreover, the description of collected data and its statistics are given in Table 3.


