[HTML][HTML] A basic review of fuzzy logic applications in hydrology and water resources
In recent years, fuzzy logic has emerged as a powerful technique in the analysis of
hydrologic components and decision making in water resources. Problems related to …
hydrologic components and decision making in water resources. Problems related to …
Watershed modeling and its applications: A state-of-the-art review
EB Daniel, JV Camp, EJ LeBoeuf… - The Open Hydrology …, 2011 - benthamopen.com
Advances in the understanding of physical, chemical, and biological processes influencing
water quality, coupled with improvements in the collection and analysis of hydrologic data …
water quality, coupled with improvements in the collection and analysis of hydrologic data …
Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base …
O Kisi - Hydrological sciences journal, 2005 - Taylor & Francis
The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the
streamflow–suspended sediment relationship are investigated. The NF and NN models are …
streamflow–suspended sediment relationship are investigated. The NF and NN models are …
[LIVRE][B] Rainfall-runoff modelling: the primer
KJ Beven - 2012 - books.google.com
Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and
authoritative text, first published in 2001. The book provides both a primer for the novice and …
authoritative text, first published in 2001. The book provides both a primer for the novice and …
A neuro-fuzzy computing technique for modeling hydrological time series
Intelligent computing tools such as artificial neural network (ANN) and fuzzy logic
approaches are proven to be efficient when applied individually to a variety of problems …
approaches are proven to be efficient when applied individually to a variety of problems …
Improving real time flood forecasting using fuzzy inference system
In order to improve the real time forecasting of foods, this paper proposes a modified Takagi
Sugeno (T–S) fuzzy inference system termed as threshold subtractive clustering based …
Sugeno (T–S) fuzzy inference system termed as threshold subtractive clustering based …
Short‐term flood forecasting with a neurofuzzy model
This study explores the potential of the neurofuzzy computing paradigm to model the rainfall‐
runoff process for forecasting the river flow of Kolar basin in India. The neurofuzzy computing …
runoff process for forecasting the river flow of Kolar basin in India. The neurofuzzy computing …
Cascaded-ANFIS to simulate nonlinear rainfall–runoff relationship
Hydrologic models require atmospheric, dynamic and static models to simulate river flow
from catchments. Thus the accuracy of hydrologic modelling highly depends on the data …
from catchments. Thus the accuracy of hydrologic modelling highly depends on the data …
A comparative study on prediction of monthly streamflow using hybrid ANFIS-PSO approaches
Monthly prediction of streamflow is a fundamental and complex hydrological phenomenon.
Accurate streamflow prediction helps in water resources planning, design, and …
Accurate streamflow prediction helps in water resources planning, design, and …
Artificial intelligence models for prediction of monthly rainfall without climatic data for meteorological stations in Ethiopia
Global climate change is affecting water resources and other aspects of life in many
countries. Rainfall is the most significant climate element affecting the livelihood and well …
countries. Rainfall is the most significant climate element affecting the livelihood and well …