## 1 Introduction  
Among the high-performance concrete (HPC) used in structural engineering, high-strength concrete (HSC) has received the most significant attention. The HSC is used in several structural engineering projects and is mostly considered at a compressive strength of \(>\)60 MPa due to the benefits it offers [1]. Despite the lack of a clear difference between HSC and normal-strength concrete (NSC), several approaches and studies have determined varying ranges of compressive strength (CS) for differentiating NSC from HSC [2]. This study, however, followed the ACI 363R-10, which described HSC as concrete with CS of \(>\)40 MPa [3]. HSC has significant benefits, which have boosted its implementation in construction activity globally. Such advantages include its improved physicochemical properties such as CS, long-term durability, and stiffness. HSC attracts great interest due to the economic usefulness associated with it as it helps in reducing geometrical sections and gain in structures. Thus, HSC is preferred over NSC for economic, aesthetic, and technical purposes [4]. Practically, HSC is known to be brittle [4] as studies have shown sudden cracking and traversing aggregate particles in HSC, which produces fracture planes that are relatively smooth [5]. As with NSC, these cracks do not cover whole aggregate particles. Concrete shear strength is significantly reduced by smooth fracture surfaces by reducing the aggregate interlock contribution at the shear fracture planes. For a reinforced concrete (RC) beam without transverse reinforcement, its failure mechanism can be considered as the generation of three internal forces that contribute to shear resistance. These internal forces include the concretes' contribution in the compression region (\(V_{c}\)), the shear contribution due to the dowel action of longitudinal rebars (\(V_{d}\)), and the shear contribution due to the aggregate interlock (\(V_{a}\)). Consequently, the overall shear resistance is the summation of all these internal forces. Components \(V_{a}\) and \(V_{d}\) are ineffective if the diagonal crack opening is excessive. As a result, all the shear on the section will be on component \(V_{c}\), leading to beam collapse as the concrete is crushed in compression [6]. The shear capacity of beams is mainly influenced by the aggregate interlocking mechanism; thus, the beams' ultimate load capacity under shear is influenced by this mechanism [7; 8]. As per [9], \(V_{a}\) for beams of CS ranging between 26 and 49 MPa accounts for 33% to 50% of the overall shear resistance of such beams. However, \(V_{a}\) seems not to contribute significantly towards shear at higher concrete strengths as evidenced by the smooth fracture planes and straight cracks, which do not cover the whole aggregates as earlier mentioned. Similarly, [10] suggested taking \(V_{a}\) as zero for concrete with CS of \(>\)62 MPa. Based on the existing literature on RC shear slender beams without web reinforcement, it is evident that no common rational theory exists to explain the collaboration between the three internal forces that contribute to shear resistance, particularly for HSC [11]. It appears that the precise estimation of shear capacity of HCS slender RC beam in the absence of shear stirrups is an open topic in research communities of structural engineering [12; 13]. The relationship between the intricate modeling variable has a remarkable influence on the shear capacity of HSC slender beams without stirrups. As such, the regression-based models are not considered ideal for such an application [14]. The existing stochasticity or nonlinearity in the experimental database initiates a very complex regression problem that needs a sophisticated modeling approach to mimic its actual internal mechanism. Artificial intelligence (AI) models have found wide application in solving different problems in civil engineering due to their interesting features, such as their auto-search and adaptation capability when finding multi-variable interrelationships [15; 16; 17; 18; 19; 20].