- Home
-
Board
- Editorial Board
- Apply For Reviewer
-
Research Publishing Standards
- Guidelines
- Peer Review Policy
- Short Guide to New Editors
- Retraction Guidelines
- Research Institute
- Recommendations for the Board of Directors
- Editor Research Audit and Service Assessments
- Guidelines for Journals Publishers
- Code of Conduct for Journal Publishers
- Commandment in Social Media
- Suggestions
- Authorship Disputes
- Rights and Responsibilities
- Editors Home
- Visibility
- Information
- Apply for Editorial
- About
- Call for Paper
- Research Community
-
Journals
- Computer Science
-
Medical Research
- A: Neurology & Nervous System
- B: Pharma, Drug Discovery, Toxicology & Medicine
- C: Microbiology & Pathology
- D: Radiology, Diagnostic Imaging and Instrumentation
- E: Gynecology & Obstetrics
- F: Diseasescancer, ophthalmology & pediatric
- G: Veterinary Science & Veterinary Medicine
- H: Orthopedic & Musculoskeletal System
- I: Surgeries & Cardiovascular System
- J: Dentistry & Otolaryngology
- K: Interdisciplinary
- L:Nutrition and Food Science
- Engineering
- Science Frontier Research
- Management
-
Human-Social Science
- A: Arts & Humanities psychology, public administration, library sciences, sports, arts, media, music
- B: Geography, Environmental Science & Disaster Management
- C: Sociology & Culture
- D: History, Archaeology & Anthropology
- E: Economics
- F: Political Science
- G: Linguistics & Education
- H: Interdisciplinary
-
Fellow
-
Support
Account
×
Regional Estimation of Flood Quantile at Ungauged Sites
Basri Badyalina, Ani Shabri, Nur Amalina Mat Jan
Volume 16 Issue 4
Global Journal of Science Frontier Researc
Volume 16 Issue 4
Global Journal of Science Frontier Researc
In this study, Linear Regression (LR) is performance is investigated with and without implementation of Topological Kriging (TK). The aims of this study to determine the used of TK can improve the performance of LR by grouping the basin which have similar hydrology characteristics. Then LR only model the relationship inside the regions. The result show that LR based TK is more reliable in term of estimation accuracy.
