Matches in SemOpenAlex for { <https://semopenalex.org/work/W2185453397> ?p ?o ?g. }
Showing items 1 to 86 of
86
with 100 items per page.
- W2185453397 abstract "How to improve forecasting accuracy such as sales, shipping is one of the critical success factor in supply chain management. There are many researches made on this. In this paper, a hybrid method is introduced and plural methods are compared. Focusing that the equation of exponential smoothing method(ESM) is equivalent to (1,1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Generally, smoothing constant is selected arbitrarily. But in this paper, we utilize above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate smoothing constants. Thus theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removing by the combination of linear and 2 nd order non-linear function and 3 rd order non-linear function is executed to the manufacturer’s data of sanitary materials. The weights for these functions are set 0.5 for two patterns at first and then varied by 0.01 increment for three patterns and optimal weights are searched. Genetic Algorithm is utilized to search the optimal weight for the weighting parameters of linear and non-linear function. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases." @default.
- W2185453397 created "2016-06-24" @default.
- W2185453397 creator A5007397145 @default.
- W2185453397 creator A5026173185 @default.
- W2185453397 creator A5050042714 @default.
- W2185453397 date "2014-01-01" @default.
- W2185453397 modified "2023-09-26" @default.
- W2185453397 title "Improvement of Forecasting Accuracy by the Utilization of Genetic Algorithm with an Application to the Sanitary Materials Data" @default.
- W2185453397 cites W1584142387 @default.
- W2185453397 cites W2003274998 @default.
- W2185453397 cites W2042105013 @default.
- W2185453397 cites W2079110222 @default.
- W2185453397 cites W2128071598 @default.
- W2185453397 cites W2155805504 @default.
- W2185453397 cites W2160874022 @default.
- W2185453397 cites W2167036165 @default.
- W2185453397 cites W2904250082 @default.
- W2185453397 hasPublicationYear "2014" @default.
- W2185453397 type Work @default.
- W2185453397 sameAs 2185453397 @default.
- W2185453397 citedByCount "0" @default.
- W2185453397 crossrefType "journal-article" @default.
- W2185453397 hasAuthorship W2185453397A5007397145 @default.
- W2185453397 hasAuthorship W2185453397A5026173185 @default.
- W2185453397 hasAuthorship W2185453397A5050042714 @default.
- W2185453397 hasConcept C105795698 @default.
- W2185453397 hasConcept C11413529 @default.
- W2185453397 hasConcept C126255220 @default.
- W2185453397 hasConcept C126838900 @default.
- W2185453397 hasConcept C133710760 @default.
- W2185453397 hasConcept C14036430 @default.
- W2185453397 hasConcept C175706884 @default.
- W2185453397 hasConcept C183115368 @default.
- W2185453397 hasConcept C199360897 @default.
- W2185453397 hasConcept C2777027219 @default.
- W2185453397 hasConcept C28826006 @default.
- W2185453397 hasConcept C33923547 @default.
- W2185453397 hasConcept C3770464 @default.
- W2185453397 hasConcept C41008148 @default.
- W2185453397 hasConcept C71924100 @default.
- W2185453397 hasConcept C78458016 @default.
- W2185453397 hasConcept C86803240 @default.
- W2185453397 hasConceptScore W2185453397C105795698 @default.
- W2185453397 hasConceptScore W2185453397C11413529 @default.
- W2185453397 hasConceptScore W2185453397C126255220 @default.
- W2185453397 hasConceptScore W2185453397C126838900 @default.
- W2185453397 hasConceptScore W2185453397C133710760 @default.
- W2185453397 hasConceptScore W2185453397C14036430 @default.
- W2185453397 hasConceptScore W2185453397C175706884 @default.
- W2185453397 hasConceptScore W2185453397C183115368 @default.
- W2185453397 hasConceptScore W2185453397C199360897 @default.
- W2185453397 hasConceptScore W2185453397C2777027219 @default.
- W2185453397 hasConceptScore W2185453397C28826006 @default.
- W2185453397 hasConceptScore W2185453397C33923547 @default.
- W2185453397 hasConceptScore W2185453397C3770464 @default.
- W2185453397 hasConceptScore W2185453397C41008148 @default.
- W2185453397 hasConceptScore W2185453397C71924100 @default.
- W2185453397 hasConceptScore W2185453397C78458016 @default.
- W2185453397 hasConceptScore W2185453397C86803240 @default.
- W2185453397 hasLocation W21854533971 @default.
- W2185453397 hasOpenAccess W2185453397 @default.
- W2185453397 hasPrimaryLocation W21854533971 @default.
- W2185453397 hasRelatedWork W1526361298 @default.
- W2185453397 hasRelatedWork W2083746309 @default.
- W2185453397 hasRelatedWork W2093101924 @default.
- W2185453397 hasRelatedWork W2122117940 @default.
- W2185453397 hasRelatedWork W2155805504 @default.
- W2185453397 hasRelatedWork W2181348349 @default.
- W2185453397 hasRelatedWork W2184529183 @default.
- W2185453397 hasRelatedWork W2188548944 @default.
- W2185453397 hasRelatedWork W2188668002 @default.
- W2185453397 hasRelatedWork W2232659155 @default.
- W2185453397 hasRelatedWork W2338287478 @default.
- W2185453397 hasRelatedWork W2368363977 @default.
- W2185453397 hasRelatedWork W2793177886 @default.
- W2185453397 hasRelatedWork W2098625974 @default.
- W2185453397 hasRelatedWork W2113330557 @default.
- W2185453397 hasRelatedWork W2181455990 @default.
- W2185453397 hasRelatedWork W2185918925 @default.
- W2185453397 hasRelatedWork W2187096556 @default.
- W2185453397 hasRelatedWork W2958574317 @default.
- W2185453397 hasRelatedWork W2992974486 @default.
- W2185453397 isParatext "false" @default.
- W2185453397 isRetracted "false" @default.
- W2185453397 magId "2185453397" @default.
- W2185453397 workType "article" @default.