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A fuzzy KNN-based model for significant wave height prediction in large lakes

100%

Nikoo M. R., Kerachian R., Alizadeh M. R.

Oceanologia

2018

tom 60

nr 2

Using support vector regression to predict direct runoff, base flow and total flow in a mountainous watershed with limited data in Uttaranchal, India

100%

Adamowski J.

Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation

2013

tom 45

nr 1

In the ecologically sensitive Himalayan region, land transformations and utilization of natural resources have modified water flow patterns. To ascertain future sustainable water supply it is necessary to predict water flow from the watersheds as affected by rainfall and morphological parameters. Although such predictions may be made using available process-based models, in mountainous and hilly areas it is extremely difficult to determine the numerous parameters needed to run such models, thus limiting their applicability. Artificial intelligence (AI) based models are a possible alternative in such circumstances. In this study an AI technique, support vector machines (SVM), was used for modeling the rainfall-runoff relationship from three hilly watersheds in the state of Uttaranchal, India. Different SVM models were developed to predict direct runoff, base flow, and total flow based on the daily rainfall, runoff, and morphological parameters collected from each watershed. The results confirm the potential of SVM models in the prediction of runoff, base flow, and total flow in hilly areas.

Ograniczanie wyników

1 Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation

1 Oceanologia

1 Adamowski J.

1 Alizadeh M. R.

1 Kerachian R.

1 Nikoo M. R.

1 2018

1 2013

Wyniki wyszukiwania

A fuzzy KNN-based model for significant wave height prediction in large lakes

Using support vector regression to predict direct runoff, base flow and total flow in a mountainous watershed with limited data in Uttaranchal, India