# A Consensus-Based Likert-LMPP Model for Evaluating the Earthquake Resistance of Existing Buildings
## 2 Related Studies
A two-stage model architecture was developed: the first involved collecting ex pert advice for knowledge acquisition and the second involved building fuzzy rules to evaluate buildings. A total of nine input parameters were used, including ring balk, floor block, column, foundation, wall cracks, wall cover and floor cover, Tombak Layar, digital elevation model, peak ground acceleration, and distance from the fault. There were three categories of building damage hazards: slight, moderate, or severe [32]. [PERSON] and [PERSON] developed an RVS methodology based on an interval type-2 FL system to prioritize vulnerable buildings for detailed assessment while covering uncertainties and minimizing their effects [33]. Building vulnerability could be estimated using the proposed Damage Index, which combines inputs such as the number of stories, the age of a building, irregularities in the plan, irregularities in the vertical plane, quality of the building, and peak ground velocity with a single output variable, and the applicability of the proposed method was examined using a database of reinforced concrete building damage after an earthquake. Building damage states were divided into \"None\", \"Low\", \"Moderate\", \"Severe\", and \"Collapse\" [34]. The study by [PERSON] et al. [33] examined how fuzzy earthquake risk assessments could be used to prioritize retrofitting buildings. A building's risk was assessed by evaluating several risk factors, including (1) building vulnerability determined by the RVS method based on FEMA 154 [35] and FEMA 155 [36], (2) seismic intensity of the site determined by peak ground acceleration, and (3) building occupancy (nine types) representing the significance of the building weighted by the Analytical Hierarchy Process. Utilizing a fuzzy rule-based model, the total risk scores were calculated by integrating the building importance and damageability scores [33]. Many studies have also used multi-criteria decision-making (MCDM) in seismic assessments [5; 37; 38; 39; 40; 41]. The objective is to assess the severity of damage and analyze the correlation between observed damage levels and damage indices derived from various MCDM techniques. [PERSON], [PERSON], et al. applied several MCDM methods including the Weighed Sum Method (WSM), the Weighed Product Method (WPM), the Analytical Hierarchy Process (AHP), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [39]. To perform the MCDM method, several seismic parameters are used, including seismic zone, type of building, vertical irregularity, plan irregularity, pre-code, post-benchmark, and code details, soil type, number of stories, and appearance of building quality. The WSM and WPM methods achieved the highest accuracy among all MCDM methods followed by TOPSIS, while the AHP method performed worst [37]. It has been suggested by [PERSON], [PERSON], et al. that damage classifications may vary with a larger amount of data, so the results can be improved as a result [39]. More precise identification may be possible with the application of sophisticated MCDM techniques like ELECTRE, PROMOTHEE, and several hybrid techniques [37]. An innovative GIS (geographic information system)-based model has been developed by [PERSON] et al. using a modified combination of AHP, TOPSIS, and fuzzy sets theory to handle one of the important uncertainties in an incomplete data set, which is the vagueness of the existing knowledge about the factors affecting seismic vulnerability [5].