Turbid of Water By Using Fuzzy C- Means and Hard K- Means
In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected from the Ministry of Planning on the water turbidity of...
Saved in:
| Main Authors: | Rand Muhaned Fawzi, Iden Hassan Alkanani |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad, College of Science for Women
2020-09-01
|
| Series: | مجلة بغداد للعلوم |
| Subjects: | |
| Online Access: | http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3474 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
APPLICATION OF K-MEANS AND FUZZY C-MEANS ALGORITHMS TO DETERMINE FLOOD VULNERABILITY CLUSTERS (CASE STUDY: KUTAI KARTANEGARA REGENCY)
by: Desi Nurjanah, et al.
Published: (2024-05-01) -
Comparison of Clustering Algorithms: Fuzzy C-Means, K-Means, and DBSCAN for House Classification Based on Specifications and Price
by: Dhendy Mardiansyah Putra, et al.
Published: (2024-11-01) -
IMPLEMENTATION OF FUZZY C-MEANS AND FUZZY POSSIBILISTIC C-MEANS ALGORITHMS ON POVERTY DATA IN INDONESIA
by: Dian Kurniasari, et al.
Published: (2024-07-01) -
Benchmarking validity indices for evolutionary K-means clustering performance
by: Abiodun M. Ikotun, et al.
Published: (2025-07-01) -
IMPLEMENTATION OF K-MEANS AND FUZZY C-MEANS CLUSTERING FOR MAPPING TODDLER STUNTING CASES IN GUNUNGKIDUL DISTRICT
by: Bintang Wira Mahardika, et al.
Published: (2024-10-01)