## 1 Introduction  
Every year, a massive proportion of construction and demolished waste (C&DW) is produced all around the world. For instance, the USA produces around 250 million tons [1], China produces almost two billion tons [2], and the European Union is responsible for about 900 million tons of C&DW [3]. Using C&DWs as recycled aggregate has two benefits. First, it reduces the amount of C&DW that needs to be disposed. Second, it reduces the demand for regular aggregate. Recycled aggregate as an environmental alternative in concrete projects is a promising environmental solution to reduce the carbon footprint of construction projects. Sourced from C&DW, it comes with varying properties depending on the type of the structure being demolished/built. As in some buildings, the dominant material used might be timber, concrete, or steel which ultimately changes the portion of recycled aggregate. The properties of aggregates vary a lot depending on their source and the manufacturing process. The influence of these two factors, i.e., the source and the process, is mainly on the porosity, water absorption, and saturated surface dried ratio, all of which significantly affect the final performance of concrete, made with these aggregates [3]. In most of the cases, a poor mechanical performance results after using recycled aggregate in concrete and that is the major reason behind the lack of tendency from the consumer's perspective in using more of this environmental alternative [4; 5; 6; 7]. As the amount of recycled aggregate that used in concrete increases, the elastic modulus, compressive strength and density of the concrete decrease [8; 9; 10; 11]. However, the use of recycled aggregate is allowed in specific amounts in some standards [8]. On the other hand, in case of service life and durability, there are some studies that showed these properties of concrete with recycled aggregate are not as good as those of conventional concrete [12; 13] while others concluded that concrete with recycled aggregate has better durability than conventional concrete [14]. While there is no commercial approach for the use of high-quality recycled aggregate, the consumers can still be motivated to use more of recycled aggregate upon the availability of more data. Artificial intelligence and data mining techniques have proven to be solutions to provide the end users with a reliable information in regards to the mechanical properties of concrete. Recently, predictive models based on artificial intelligence methods have been used to forecast the mechanical properties of concrete and predict the effect of changes in its mixture design on its behavior [15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57]. For instance, [PERSON] and [PERSON] [37], has used M5P three model to estimate mechanical properties of concrete containing used foundry sand. Their results show that the M5P three model has an acceptable performance to predict the properties of concrete. [PERSON] et al. [23] have developed a model by hybridizing beetle antennae search (BAS) and multi-output least square support vector regression (MOLSSVR) to predict concrete's compressive strength (CS) and permeability coefficient of pervious. The outcomes of this research indicated that their proposed model performs better than support vector regression (SVR), MOLSSVR, logistic regression, and modified ANN with firefly algorithm. In another research, [PERSON] et al. [54] used chi-square automatic interaction detection, M5P tree model, MSrule, and random forest to forecast mechanical properties of roller-compacted concrete pavement. It was observed that the predicted values of random forest had lower errors and higher correlation in comparison with other models. [PERSON] et al. [40] developed a hybrid ANN with multi-objective salp swarm algorithm to estimate CS of concrete with ground granulated blast furnace slag.