This research has provided a fuzzy-logic-based method to measure the buildings’ damage after earthquake. In this method, the damage level is obtained from the data reported by the trained staff and observations made over the visual parameters such as “structural components” and “non-structural components”. Considering the standard assessment form, the damages in each structure are graded from D1 (with no damage) to D0 (destruction). Therefore, this study aims to provide a report on the damage level in the range of D1 to D0. The present study checks the effects of the number and weight of fuzzy logic. Also, the influence of the values related to the membership functions on the overall damage level is evaluated by using the single-index weighted fuzzy rule and the damage level with the highest membership value are evaluated, while the rest of damages are also considered despite their low impact. A genetic algorithm has also been used for optimizing the weights related to the structure’s damage. The complied database covering more than 30 thousand buildings has been used for training and evaluating. Theoretical prediction obtained from the automated processing for assessment forms in each building is compared with the total level of damage (the observed damage) and the level of damage is determined by the observers. The results show that the theoretical assessment proportional to the observed values of 90% of the buildings is evaluated.
