An Evolutionary Neuro-Fuzzy-Based Approach to Estimate the Compressive Strength of Eco-Friendly Concrete Containing Recycled Construction Wastes

There has been a significant increase in construction and demolition (C&D) waste due to the growth of cities need for new construction, raising concerns about impact on environment these wastes. By utilising recycled C&D waste, especially concretes used further environmental damage can be prevented. using concretes, energy consumption impacts concrete production reduced. The behaviour types laboratories extensively studied, but reliable methods estimating their based available data are required. Consequently, this research proposes hybrid intelligent system, Fuzzy Group Method Data Handling (GMDH)–Horse herd Optimisation Algorithm (HOA), predicting one most important parameters structure design, compressive strength. In order avoid uncertainty modelling process, crisp input values were converted (Fuzzification). Next, variables, group method handling is predict strength aggregate concrete. HOA algorithm newest metaheuristic algorithms being optimise GMDH structure. Several databases containing experimental mix design records mixture components gathered from published documents assess accuracy reliability proposed Fuzzy-based model. Compared other original approaches, model with optimiser outperformed them terms accuracy. A Monte Carlo simulation also employed analysis empirical, standalone, hybridised models demonstrate that evolutionary approach less than standalone when simulating