Matches in SemOpenAlex for { <https://semopenalex.org/work/W2700371139> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W2700371139 abstract "Thailand is the world's largest exporter of cassava. The cassava prices fluctuate because of many factors such as the production cost, economic condition, and price intervention. Therefore, this research aims to propose a forecasting model of cassava price based on the 11-year data (from 2005 to 2015) obtained from the Thai Tapioca Starch Association and Office of Agricultural Economics. Various techniques were applied for the forecast such as Artificial Neural Network, Support Vector Machine, k-Nearest Neighbor and Hybrid Technique. The statistics used to determine the effectiveness of this model were Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE) and Mean Squared Error (MSE). The results of this research showed that Hybrid Technique demonstrated the lowest value of error followed by Artificial Neural Network, k-Nearest Neighbor and Support Vector Machine, respectively. Therefore, it could be concluded that using the Hybrid Technique to forecast the price of cassava was better than other techniques and generated the predicted price closest to the actual price." @default.
- W2700371139 created "2017-06-30" @default.
- W2700371139 creator A5028072729 @default.
- W2700371139 creator A5031990763 @default.
- W2700371139 date "2017-04-01" @default.
- W2700371139 modified "2023-09-23" @default.
- W2700371139 title "A hybrid forecasting model of cassava price based on artificial neural network with support vector machine technique" @default.
- W2700371139 cites W1563088657 @default.
- W2700371139 cites W1971568497 @default.
- W2700371139 cites W1978266801 @default.
- W2700371139 cites W1980836123 @default.
- W2700371139 cites W1992224998 @default.
- W2700371139 cites W2024359316 @default.
- W2700371139 cites W2025053102 @default.
- W2700371139 cites W2055485811 @default.
- W2700371139 cites W2059029210 @default.
- W2700371139 cites W2067562186 @default.
- W2700371139 cites W2130127304 @default.
- W2700371139 cites W2181800037 @default.
- W2700371139 cites W2339165479 @default.
- W2700371139 cites W2340519628 @default.
- W2700371139 cites W2465073537 @default.
- W2700371139 doi "https://doi.org/10.1109/infoman.2017.7950359" @default.
- W2700371139 hasPublicationYear "2017" @default.
- W2700371139 type Work @default.
- W2700371139 sameAs 2700371139 @default.
- W2700371139 citedByCount "1" @default.
- W2700371139 countsByYear W27003711392018 @default.
- W2700371139 crossrefType "proceedings-article" @default.
- W2700371139 hasAuthorship W2700371139A5028072729 @default.
- W2700371139 hasAuthorship W2700371139A5031990763 @default.
- W2700371139 hasConcept C105795698 @default.
- W2700371139 hasConcept C119857082 @default.
- W2700371139 hasConcept C12267149 @default.
- W2700371139 hasConcept C139945424 @default.
- W2700371139 hasConcept C150217764 @default.
- W2700371139 hasConcept C154945302 @default.
- W2700371139 hasConcept C33923547 @default.
- W2700371139 hasConcept C41008148 @default.
- W2700371139 hasConcept C50644808 @default.
- W2700371139 hasConceptScore W2700371139C105795698 @default.
- W2700371139 hasConceptScore W2700371139C119857082 @default.
- W2700371139 hasConceptScore W2700371139C12267149 @default.
- W2700371139 hasConceptScore W2700371139C139945424 @default.
- W2700371139 hasConceptScore W2700371139C150217764 @default.
- W2700371139 hasConceptScore W2700371139C154945302 @default.
- W2700371139 hasConceptScore W2700371139C33923547 @default.
- W2700371139 hasConceptScore W2700371139C41008148 @default.
- W2700371139 hasConceptScore W2700371139C50644808 @default.
- W2700371139 hasLocation W27003711391 @default.
- W2700371139 hasOpenAccess W2700371139 @default.
- W2700371139 hasPrimaryLocation W27003711391 @default.
- W2700371139 hasRelatedWork W110458838 @default.
- W2700371139 hasRelatedWork W2057044787 @default.
- W2700371139 hasRelatedWork W2077605650 @default.
- W2700371139 hasRelatedWork W2079678792 @default.
- W2700371139 hasRelatedWork W2097244900 @default.
- W2700371139 hasRelatedWork W2106538518 @default.
- W2700371139 hasRelatedWork W2378582484 @default.
- W2700371139 hasRelatedWork W2576572654 @default.
- W2700371139 hasRelatedWork W2783264455 @default.
- W2700371139 hasRelatedWork W2808471159 @default.
- W2700371139 hasRelatedWork W2894409315 @default.
- W2700371139 hasRelatedWork W2951507346 @default.
- W2700371139 hasRelatedWork W3006488856 @default.
- W2700371139 hasRelatedWork W3017691321 @default.
- W2700371139 hasRelatedWork W3035566149 @default.
- W2700371139 hasRelatedWork W3094425250 @default.
- W2700371139 hasRelatedWork W3127595472 @default.
- W2700371139 hasRelatedWork W3137354021 @default.
- W2700371139 hasRelatedWork W3138120386 @default.
- W2700371139 hasRelatedWork W3166302680 @default.
- W2700371139 isParatext "false" @default.
- W2700371139 isRetracted "false" @default.
- W2700371139 magId "2700371139" @default.
- W2700371139 workType "article" @default.