Obiekt
Tytuł: A rainfall forecasting method using machine learning models and its application to the Fukuoka city case
Współtwórca:
Cordón, Oskar - ed. ; Kazienko, Przemysław - ed.
Podtytuł:
Hybrid and Ensemble Methods in Machine Learning
Tytuł publikacji grupowej:
Abstract:
In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. ; A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid multi-model method is proposed and compared with its constituent models. The models include the artificial neural network, multivariate adaptive regression splines, the k-nearest neighbour, and radial basis support vector regression. ; Each of these methods is applied to model the daily and monthly rainfall, coupled with a pre-processing technique including moving average and principal component analysis. ; In the first stage of the hybrid method, sub-models from each of the above methods are constructed with different parameter settings. In the second stage, the sub-models are ranked with a variable selection technique and the higher ranked models are selected based on the leave-one-out cross-validation error. The forecasting of the hybrid model is performed by the weighted combination of the finally selected models.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, Volume 22, Number 4 (2012) ; kliknij tutaj, żeby przejść
Jezyk:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Jednostki organizacyjne > Wydział Informatyki, Elektrotechniki i Automatyki
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Typy utworów > Artykuły
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2012)
Data ostatniej modyfikacji:
2021-10-14
Data dodania obiektu:
2021-09-15
Liczba wyświetleń treści obiektu:
166
Wszystkie dostępne wersje tego obiektu:
https://zbc.uz.zgora.pl/publication/65812
Wyświetl opis w formacie RDF:
Wyświetl opis w formacie OAI-PMH:
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| Nazwa wydania | Data |
|---|---|
| A rainfall forecasting method using machine learning models and its application to the Fukuoka city case | 2021-10-14 |
