## 4 Conclusions  
In this study, an ANN model was developed to predict the q\({}_{u}\) of clayey soil reinforced with basalt fibers and to determine the optimal fiber length and ratio that provide the greatest increase in q\({}_{u}\). For this purpose, previously published data from experimental studies involving bentonite, a highly plastic clay, were utilized. The q\({}_{u}\) values were obtained from mixtures of bentonite reinforced with basalt fibers at varying lengths (6 mm and 12 mm) and proportions (1%, 2%, 3%, 4%, and 5%). The q\({}_{u}\) values obtained after the experimental study were evaluated using the ANN. The compressive strength values predicted by the ANN closely matched the experimental results, demonstrating the effectiveness of the ANN in evaluating compressive strength performance.  
The ANN methodology enables the quick estimation of q\({}_{u}\) for known mixing ratios at different curing ages without the need for preliminary experiments. This capability not only streamlines the evaluation process, but also enhances efficiency and reliability in predicting material performance. As a result, the adoption of ANNs in this context offers substantial  
Figure 6: Five-fold-cross-validation response plot.  
advantages in terms of time savings, cost reduction, and labor efficiency. ANNs' scalability, adaptability to complex patterns, and suitability for larger data volumes make them a preferred choice for the model presented in this paper. These advantages will also support potential future research extensions. Ultimately, this study aimed to provide a practical tool for engineers and researchers in the field, fostering more informed decision-making and optimizing resource utilization in geotechnical engineering.  
It should be noted that although the optimum basalt fiber ratio and length values obtained from this study can be used for high-plasticity clays used in experimental studies, it will not be appropriate to use them for clays with different engineering properties. The database on this subject can be enriched with new studies to be conducted by changing the basalt fiber contribution ratios and fiber length values in clays with different properties. Similarly, the development of the study is also possible by increasing the number of fiber-reinforced soil series, changing the soil-fiber mixture ratios, or changing the water ratio used in the preparation of the mixtures. In addition, since the success rate of artificial intelligence will increase in parallel with the increase in the number of input data, more experimental results mean more accurate predictions. In addition, deep network architectures can be used to increase the prediction performance obtained as a result of different mixtures used. This study has shown that considering the decrease in soils with suitable geotechnical properties in parallel with the increase in population and structures, the use of basalt fiber, which is sustainable and environmentally friendly and whose raw material is abundant and naturally available in nature, will provide significant gains in soil reinforcement applications.  
[PERSON], [PERSON] and [PERSON] wrote the main manuscript text and prepared all figures and tables. All authors have read and agreed to the published version of the manuscript.  
This study was financially supported by the Scientific Research Projects Coordination Unit of Firat University (FUBAP) under project number MF.24.98.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.  
The authors declare no conflicts of interest.