Prediction of soil types from existing borehole data using genetic algorithm: A case of Metro Manila - Sumagaysay, Izzhar Christian P. (Animo Repository, 2021)
A Genetic Algorithm (GA) is an optimization algorithm following the concept of survival of the fittest wherein fitter individuals have higher chances of surviving and passing their genes to their offspring. With the absence of a soil reference map of Metro Manila, GA was implemented to predict the soil layers in given grid intervals. The fitness of a prospect soil layer also referred to as an individual, is evaluated by two variables: the likeness of the soil layer with surrounding boreholes, and the distance between the boreholes considered and the grid point. The GA was deployed from 40 meters below sea level up to 100 meters above sea level, on a grid with 2km intervals placed on Metro Manila. Due to the large number of boreholes collected on the study area and adjacent provinces, a program was created on LabVIEW, a graphical programming software, for fast processing and compiling. The results were compiled and visualized in excel and plotted in AutoCAD. Results showed rock layers on the central plateau in the cities of Quezon, San Juan, Mandaluyong, and Makati. A mixture of sand and clays were observed for coastal lowlands in the western Metro Manila on the cities of Manila and Pasay. Silt deposits were also present in the southern part of this area. Alluvial deposits resulted in clay and silt deposits in the area of Marikina Valley. Overall, the GA program proved to be a good tool for predicting soil types as the results agreed with existing published works.