Application of the optimal fuzzy-based system on bearing capacity of concrete pile

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence ofseveral suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (𝐴𝑁𝐹𝐼𝑆) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (𝐹𝐻𝑂) and equilibrium optimizer (𝐸𝑂) with the 𝐴𝑁𝐹𝐼𝑆, referred to as 𝐴𝑁𝐹𝐼𝑆𝐹𝐻𝑂 and 𝐴𝑁𝐹𝐼𝑆𝐸𝑂 , respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that 𝐴𝑁𝐹𝐼𝑆𝐹𝐻𝑂 and 𝐴𝑁𝐹𝐼𝑆𝐸𝑂 both have amazing potential for precisely calculating pile bearing capacity. The 𝑅2 values obtained for 𝐴𝑁𝐹𝐼𝑆𝐹𝐻𝑂 were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the 𝐴𝑁𝐹𝐼𝑆𝐹𝐻𝑂 system had less uncertainty than the 𝐴𝑁𝐹𝐼𝑆𝐸𝑂 model. The research found that the 𝐴𝑁𝐹𝐼𝑆𝐹𝐻𝑂 model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.