# An Integral Fuzzy Model to Evaluate Slab and Beam Bridges with a Preventive Approach
## 2 State of the Art
### Soft Computing Approach  
A soft computing approach using fuzzy logic has proven to be a good method to assess the condition of bridges, considering their complexity. This tool does not replace traditional methods but rather complements them by allowing a representation closer to human reasoning, facilitating gradual decisions in the assessment of bridge condition. This section examines various studies that have incorporated fuzzy logic into the bridge assessment process, highlighting both its key contributions and its limitations. In [11], a preventive methodology was proposed to assess the condition of concrete bridges using a Fuzzy Weighted Geometric Mean (FWGM) approach. The authors used information from visual inspections and subsequently evaluated the overall condition of the individual bridge elements. Each element was assigned a structural importance, which was multiplied by its rating. Finally, the products were summed to obtain an estimate of the bridge's overall condition. It is worth noting that the authors did not specify the regulatory document used to evaluate the bridge elements. On the other hand, a study conducted in the Philippines [12] developed a program for managing concrete bridges based on a systematic process that employs fuzzy logic. This work used data obtained from the SMART Bridge Project and was implemented using MATLAB 2024a software. The information was collected through sensors installed on the girders and piers, which, according to the authors and based on the National Bridge Elements (NBEs), are the key components of the bridge structure under study (however, other key components, like support devices and foundations, are not included in the study). The sensors captured data on the acceleration of the girders and piers, from which the overall condition of the bridge was determined. The study took a preventive approach, aiming to detect potential bridge damage early to facilitate timely maintenance measures. In the study conducted by [PERSON] et al. [13], a preventive method was developed based on Multi-Criteria Decision-Making (MCDM) techniques, specifically the Fuzzy Analytic Hierarchy Process (FAHP) and the VIKOR technique. Their objective was to prioritize the bridges within a road network that require more attention compared to others. The evaluation was based on a set of criteria hierarchized using FAHP, drawing on the opinions of 27 experts who were interviewed. However, these criteria assessed the bridge as a single entity, without thoroughly analyzing the condition of its individual components. It is worth noting that the authors did not specify the regulatory document used as the basis for selecting the evaluation criteria. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Manual** & **Approach** & **Evaluated Deterioration** & **Evaluation Criteria** & **Bridge Rating Type** \\ \hline Mexico [16] & Corrective. & Material and functional. & SIAP ratings. & Global. \\ \hline Colombia [17] & Corrective. & Material. & Personal. & Global. \\ \hline Ontario, Canada [4] & Corrective. & Material. & Does not present. & Individual. \\ \hline Costa Rica [18] & Corrective. & Material. & Does not present. & Individual. \\ \hline Peru [5] & Corrective. & Material and functional. & Personal. & Global. \\ \hline United States [3] & Corrective. & Material, functional and environmental. & PONTS \& CoRe systems. & Individual. \\ \hline Africa [6] & Corrective. & Material, functional and environmental. & DER ratings. & Individual. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: International bridge evaluation manuals analyzed. In the case of [PERSON] et al. [14], a predictive model with a preventive approach was proposed based on the fusion of three models: Least Squares Support Vector Machine (LSSVM), Fuzzy Logic (FL), and Differential Evolution (DE). The goal of the model was to predict the condition of bridges, assisting decision-makers in planning maintenance projects.