PENGGUNAAN PARTICLE SWARM OPTIMIZATION (PSO) PADA K-MEANS UNTUK PENGELOMPOKAN JENIS FLUIDA MINYAK BUMI
Daftar Isi:
- One of the handling in overcoming the problem of decreasing petroleum production is the Enhanced Oil Recovery (EOR) process, where the EOR stage required determining the right type of fluid to be injected into the oil well as an effort to increase petroleum production. Clustering is one way to solve this problem. This research applies Particle Swarm Optimization (PSO) in determining the centroid to be used in the process of clustering using KMeans algorithm. The clustering results compared with PT. Eonchemical Putra well test report to determine the accuracy of the combination between Particle Swarm Optimization and K-Means methods it showed an average accuracy value of 84% with the best PSO parameter configuration on particle is 25, iteration is 100, the value of C1 is 1.5, C2 is 1.5 and w is 0.8.