Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285167352> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W4285167352 endingPage "308" @default.
- W4285167352 startingPage "289" @default.
- W4285167352 abstract "This paper attempts to develop a more appropriate hybrid wavelet modified GMDH model and its comparative study with statistical ARIMA model for the Malaysia monthly crude palm oil (CPO) price forecasting. The complex data of monthly CPO price has decomposed by using discrete wavelet analysis into different sub series in such a way that error criteria is minimized. The new input of monthly CPO price data obtained from the wavelet analysis is linked to the modified GMDH model. The importance of modified GMDH neural network that has been used different transfer functions simultaneously into GMDH and has given the best fit for modeling in comparison with conventional GMDH model. Real time series data of monthly CPO price for the period of 37 years are collected from Malaysian Palm Oil Board (MPOB). The performance of hybrid GMDH type neural network, individual GMDH model and statistical ARIMA model are determined by using mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), correlation coefficient (R) and coefficient of determination (R2). The result of hybrid GMDH neural network have shown an improvement over ARIMA model with 25.35%, 19.16% and 22.50% reduction in MAE, RMSE and MAPE values respectively. The obtained results of the comparison show that the hybrid wavelet-modified GMDH model has performed better result than the ARIMA model and individual GMDH neural network. The hybrid wavelet modified GMDH neural network technique is imperative to the field of forecasting as it can be used in different forecasting applications." @default.
- W4285167352 created "2022-07-14" @default.
- W4285167352 creator A5073126307 @default.
- W4285167352 creator A5084201282 @default.
- W4285167352 date "2022-01-01" @default.
- W4285167352 modified "2023-09-29" @default.
- W4285167352 title "Crude Palm Oil Price Forecasting: Comparative Study of Hybrid GMDH Neural Network and ARIMA Model" @default.
- W4285167352 cites W1506414135 @default.
- W4285167352 cites W1566890033 @default.
- W4285167352 cites W1629264386 @default.
- W4285167352 cites W1967891383 @default.
- W4285167352 cites W1977870224 @default.
- W4285167352 cites W1998329781 @default.
- W4285167352 cites W2004191436 @default.
- W4285167352 cites W2014554825 @default.
- W4285167352 cites W2026938221 @default.
- W4285167352 cites W2028247574 @default.
- W4285167352 cites W2058945048 @default.
- W4285167352 cites W2062783952 @default.
- W4285167352 cites W2068265637 @default.
- W4285167352 cites W2070034048 @default.
- W4285167352 cites W2072911459 @default.
- W4285167352 cites W2073819050 @default.
- W4285167352 cites W2136250054 @default.
- W4285167352 cites W2169382242 @default.
- W4285167352 cites W2470292068 @default.
- W4285167352 cites W2514555135 @default.
- W4285167352 cites W2544706998 @default.
- W4285167352 cites W2615325070 @default.
- W4285167352 cites W2772887720 @default.
- W4285167352 cites W2786998717 @default.
- W4285167352 cites W2890247021 @default.
- W4285167352 cites W2893012359 @default.
- W4285167352 cites W2903544035 @default.
- W4285167352 cites W2914369972 @default.
- W4285167352 cites W2940510029 @default.
- W4285167352 cites W2978237237 @default.
- W4285167352 cites W3030931820 @default.
- W4285167352 cites W4249810380 @default.
- W4285167352 cites W4300009529 @default.
- W4285167352 doi "https://doi.org/10.1007/978-981-16-8903-1_27" @default.
- W4285167352 hasPublicationYear "2022" @default.
- W4285167352 type Work @default.
- W4285167352 citedByCount "0" @default.
- W4285167352 crossrefType "book-chapter" @default.
- W4285167352 hasAuthorship W4285167352A5073126307 @default.
- W4285167352 hasAuthorship W4285167352A5084201282 @default.
- W4285167352 hasConcept C105795698 @default.
- W4285167352 hasConcept C119857082 @default.
- W4285167352 hasConcept C122383733 @default.
- W4285167352 hasConcept C13926793 @default.
- W4285167352 hasConcept C139945424 @default.
- W4285167352 hasConcept C150217764 @default.
- W4285167352 hasConcept C151406439 @default.
- W4285167352 hasConcept C154945302 @default.
- W4285167352 hasConcept C24338571 @default.
- W4285167352 hasConcept C33923547 @default.
- W4285167352 hasConcept C41008148 @default.
- W4285167352 hasConcept C47432892 @default.
- W4285167352 hasConcept C50644808 @default.
- W4285167352 hasConceptScore W4285167352C105795698 @default.
- W4285167352 hasConceptScore W4285167352C119857082 @default.
- W4285167352 hasConceptScore W4285167352C122383733 @default.
- W4285167352 hasConceptScore W4285167352C13926793 @default.
- W4285167352 hasConceptScore W4285167352C139945424 @default.
- W4285167352 hasConceptScore W4285167352C150217764 @default.
- W4285167352 hasConceptScore W4285167352C151406439 @default.
- W4285167352 hasConceptScore W4285167352C154945302 @default.
- W4285167352 hasConceptScore W4285167352C24338571 @default.
- W4285167352 hasConceptScore W4285167352C33923547 @default.
- W4285167352 hasConceptScore W4285167352C41008148 @default.
- W4285167352 hasConceptScore W4285167352C47432892 @default.
- W4285167352 hasConceptScore W4285167352C50644808 @default.
- W4285167352 hasLocation W42851673521 @default.
- W4285167352 hasOpenAccess W4285167352 @default.
- W4285167352 hasPrimaryLocation W42851673521 @default.
- W4285167352 hasRelatedWork W2111480483 @default.
- W4285167352 hasRelatedWork W2305568609 @default.
- W4285167352 hasRelatedWork W2322108555 @default.
- W4285167352 hasRelatedWork W2541571801 @default.
- W4285167352 hasRelatedWork W2952279496 @default.
- W4285167352 hasRelatedWork W2963766945 @default.
- W4285167352 hasRelatedWork W3036816126 @default.
- W4285167352 hasRelatedWork W3080840844 @default.
- W4285167352 hasRelatedWork W3111566463 @default.
- W4285167352 hasRelatedWork W4280626000 @default.
- W4285167352 isParatext "false" @default.
- W4285167352 isRetracted "false" @default.
- W4285167352 workType "book-chapter" @default.