[HTML][HTML] Comparative analysis of RSM, ANN and ANFIS and the mechanistic modeling in eriochrome black-T dye adsorption using modified clay
The application of artificial neural network (ANN), response surface methodology (RSM),
and adaptive neuro-fuzzy inference system (ANFIS) in modeling the uptake of Eriochrome …
and adaptive neuro-fuzzy inference system (ANFIS) in modeling the uptake of Eriochrome …
The global water cycle budget: A chronological review
Like civilization and technology, our understanding of the global water cycle has been
continuously evolving, and we have adapted our quantification methods to better exploit …
continuously evolving, and we have adapted our quantification methods to better exploit …
Selection of classification techniques for land use/land cover change investigation
The concerns over land use/land cover (LULC) change have emerged on the global stage
due to the realisation that changes occurring on the land surface also influence climate …
due to the realisation that changes occurring on the land surface also influence climate …
A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States
Accurate and reliable suspended sediment load (SSL) prediction models are necessary for
planning and management of water resource structures. More recently, soft computing …
planning and management of water resource structures. More recently, soft computing …
Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting
RJ Abrahart, F Anctil, P Coulibaly… - Progress in …, 2012 - journals.sagepub.com
This paper traces two decades of neural network rainfall-runoff and streamflow modelling,
collectively termed 'river forecasting'. The field is now firmly established and the research …
collectively termed 'river forecasting'. The field is now firmly established and the research …
Assessment of different methods for estimation of missing data in precipitation studies
The outcome of data analysis depends on the quality and completeness of data. This paper
considers various techniques for filling in missing precipitation data. To assess suitability of …
considers various techniques for filling in missing precipitation data. To assess suitability of …
Flood flow forecasting using ANN, ANFIS and regression models
M Rezaeianzadeh, H Tabari, A Arabi Yazdi… - Neural Computing and …, 2014 - Springer
Flood prediction is an important for the design, planning and management of water
resources systems. This study presents the use of artificial neural networks (ANN), adaptive …
resources systems. This study presents the use of artificial neural networks (ANN), adaptive …
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 …
Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) …
YJ Wong, SK Arumugasamy, CH Chung… - Environmental …, 2020 - Springer
Presence of copper within water bodies deteriorates human health and degrades natural
environment. This heavy metal in water is treated using a promising biochar derived from …
environment. This heavy metal in water is treated using a promising biochar derived from …
ANFIS, ANN, and RSM modeling of moisture content reduction of cocoyam slices
The capability of response surface methodology (RSM), artificial neural network (ANN), and
adaptive neuro‐fuzzy inference systems (ANFIS) in modeling and predicting moisture …
adaptive neuro‐fuzzy inference systems (ANFIS) in modeling and predicting moisture …