## 1 Introduction  
In recent decades, novel materials were the subject of widespread research in order to reduce greenhouse emissions in civil engineering activities. Since its invention, geopolymer concrete (GPC) received considerable attention from researchers as an alternative for concrete using ordinary Portland cement (OPC) [1]. Geopolymer binder is made from two main compounds: (i) rich alumino-silicate materials such as meta-kaolin, fly ash, silica fume, slag, or red mud, and (ii) an activator of alkaline solutions such as sodium or potassium hydroxide and sodium or potassium silicate. Manufacturing OPC generally uses raw materials and releases carbon dioxide, whereas geopolymer binder uses waste by-product materials. Therefore, such green materials are an excellent alternative for sustainable development. Many researchers pointed out the advantages of GPC, including chemical resistance or resistance to acid attack [2], alkali-silica reactions [3; 4], corrosion of steel reinforcement [3; 5; 6], resistance to high temperatures and to fire [7; 8], resistance to freeze-thawing [9; 10], and efflorescence [11; 12]. However, such works were applied to a limited alumino-silicate compound in GPC, for instance, fly ash, blast-furnace slags, or meta-kaolin. Many other admixtures could also be investigated and used, such as steel slag [13]. Undeniably, slag from steel and iron plants is abundantly available as a waste product. This can be used as a cement additive, as well as in concrete admixtures [13]. Indeed, the utilization of steel slag for production of cement or GPC is available in the literature. As an example, ground granulated blast-furnace slag (GGBFS) was blended with fly ash to fabricate GPC [14]. Local steel slag was also used to replace natural crushed stone, as a substitute to coarse aggregate in GPC [15]. The compressive strength of such GPC ranged from 40 to 54 MPa which is about 6% higher than that of natural crushed stone. In order to obtain the desired mechanical properties, researchers have to find an appropriate selection of ingredients and mixture design. Such a process requires an important number of laboratory experiments which consume substantial effort, time, and man power, thereby increasing the cost of production. [PERSON] and [PERSON] [16; 17; 18; 19] proposed a method in order to determine an optimum mix design of fly-ash-based GPC by identifying the effects of salient factors that affect the properties of GPC in the fresh and hardened states. Furthermore, [PERSON] et al. [20] proposed a flow chart methodology based on nine steps to determine mix proportions to obtain GPC with a targeted 45 MPa compressive strength at 28 days. These studies only considered a limited number of ingredients or mix proportions. Therefore, it is still required to find a more efficient, robust method to establish a direct relationship between these factors and the corresponding mechanical properties. In recent years, artificial intelligence (AI)-based algorithms were widely used to solve very complex problems in engineering [21; 22; 23]. Such algorithms were extended and applied to many civil engineering applications including building materials, concrete, or mortar [24; 25]. Many works on the prediction of concrete properties were reported, including drying shrinkage [26; 27], concrete durability [28] or delivery [29], concrete workability using meta-kaolin along with fly ash [30], slump models [31; 32], concrete at high temperatures [33], concrete-based structures [34; 35], concrete permeability [36], and long-term effects of compounds on the mechanical behavior of GPC [37]. Most of these works focused on the use of artificial neural network algorithms (ANN) or fuzzy logic (FL) to predict the mechanical properties of typical type of concrete, such as high-performance concrete (HPC) or self-consolidating concrete (SCC).