FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3124169968> ?p ?o ?g. }

• W3124169968 endingPage "6" @default.
• W3124169968 startingPage "1" @default.
• W3124169968 abstract "Due to the continuous improvement of productivity, the transportation demand of freight volume is also increasing. It is difficult to organize freight transportation efficiently when the freight volume is quite large. Therefore, predicting the total amount of goods transported is essential in order to ensure efficient and orderly transportation. Aiming at optimizing the forecast of freight volume, this paper predicts the freight volume in Xi’an based on the Gray GM (1, 1) model and Markov forecasting model. Firstly, the Gray GM (1, 1) model is established based on related freight volume data of Xi’an from 2000 to 2008. Then, the corresponding time sequence and expression of restore value of Xi’an freight volume can be attained by determining parameters, so as to obtain the gray forecast values of Xi’an’s freight volume from 2009 to 2013. In combination with the Markov chain process, the random sequence state is divided into three categories. By determining the state transition probability matrix, the probability value of the sequence in each state and the predicted median value corresponding to each state can be obtained. Finally, the revised predicted values of the freight volume based on the Gray–Markov forecasting model in Xi’an from 2009 to 2013 are calculated. It is proved in theory and practice that the Gray–Markov forecasting model has high accuracy and can provide relevant policy bases for the traffic management department of Xi’an." @default.
• W3124169968 created "2021-02-01" @default.
• W3124169968 creator A5010347728 @default.
• W3124169968 creator A5031618586 @default.
• W3124169968 creator A5071371875 @default.
• W3124169968 creator A5072559250 @default.
• W3124169968 creator A5081290417 @default.
• W3124169968 creator A5089041117 @default.
• W3124169968 date "2021-01-18" @default.
• W3124169968 modified "2023-10-15" @default.
• W3124169968 title "Forecast of Freight Volume in Xi’an Based on Gray GM (1, 1) Model and Markov Forecasting Model" @default.
• W3124169968 cites W1979779792 @default.
• W3124169968 cites W1982052073 @default.
• W3124169968 cites W2001848173 @default.
• W3124169968 cites W2025689845 @default.
• W3124169968 cites W2036953951 @default.
• W3124169968 cites W2057707727 @default.
• W3124169968 cites W2068152552 @default.
• W3124169968 cites W2096095002 @default.
• W3124169968 cites W2134202645 @default.
• W3124169968 cites W2524215529 @default.
• W3124169968 cites W2555832335 @default.
• W3124169968 cites W2577895172 @default.
• W3124169968 cites W2737040173 @default.
• W3124169968 cites W2787511830 @default.
• W3124169968 cites W2802052880 @default.
• W3124169968 cites W2901295635 @default.
• W3124169968 cites W2952181846 @default.
• W3124169968 cites W2964216649 @default.
• W3124169968 cites W3088340182 @default.
• W3124169968 cites W3091966614 @default.
• W3124169968 cites W3094399461 @default.
• W3124169968 doi "https://doi.org/10.1155/2021/6686786" @default.
• W3124169968 hasPublicationYear "2021" @default.
• W3124169968 type Work @default.
• W3124169968 sameAs 3124169968 @default.
• W3124169968 citedByCount "9" @default.
• W3124169968 countsByYear W31241699682021 @default.
• W3124169968 countsByYear W31241699682022 @default.
• W3124169968 countsByYear W31241699682023 @default.
• W3124169968 crossrefType "journal-article" @default.
• W3124169968 hasAuthorship W3124169968A5010347728 @default.
• W3124169968 hasAuthorship W3124169968A5031618586 @default.
• W3124169968 hasAuthorship W3124169968A5071371875 @default.
• W3124169968 hasAuthorship W3124169968A5072559250 @default.
• W3124169968 hasAuthorship W3124169968A5081290417 @default.
• W3124169968 hasAuthorship W3124169968A5089041117 @default.
• W3124169968 hasBestOaLocation W31241699681 @default.
• W3124169968 hasConcept C105795698 @default.
• W3124169968 hasConcept C11413529 @default.
• W3124169968 hasConcept C121332964 @default.
• W3124169968 hasConcept C126838900 @default.
• W3124169968 hasConcept C159886148 @default.
• W3124169968 hasConcept C163836022 @default.
• W3124169968 hasConcept C166275286 @default.
• W3124169968 hasConcept C20556612 @default.
• W3124169968 hasConcept C2778112365 @default.
• W3124169968 hasConcept C3020136221 @default.
• W3124169968 hasConcept C33923547 @default.
• W3124169968 hasConcept C42475967 @default.
• W3124169968 hasConcept C54355233 @default.
• W3124169968 hasConcept C62520636 @default.
• W3124169968 hasConcept C71924100 @default.
• W3124169968 hasConcept C86803240 @default.
• W3124169968 hasConcept C98763669 @default.
• W3124169968 hasConceptScore W3124169968C105795698 @default.
• W3124169968 hasConceptScore W3124169968C11413529 @default.
• W3124169968 hasConceptScore W3124169968C121332964 @default.
• W3124169968 hasConceptScore W3124169968C126838900 @default.
• W3124169968 hasConceptScore W3124169968C159886148 @default.
• W3124169968 hasConceptScore W3124169968C163836022 @default.
• W3124169968 hasConceptScore W3124169968C166275286 @default.
• W3124169968 hasConceptScore W3124169968C20556612 @default.
• W3124169968 hasConceptScore W3124169968C2778112365 @default.
• W3124169968 hasConceptScore W3124169968C3020136221 @default.
• W3124169968 hasConceptScore W3124169968C33923547 @default.
• W3124169968 hasConceptScore W3124169968C42475967 @default.
• W3124169968 hasConceptScore W3124169968C54355233 @default.
• W3124169968 hasConceptScore W3124169968C62520636 @default.
• W3124169968 hasConceptScore W3124169968C71924100 @default.
• W3124169968 hasConceptScore W3124169968C86803240 @default.
• W3124169968 hasConceptScore W3124169968C98763669 @default.
• W3124169968 hasFunder F4320325627 @default.
• W3124169968 hasLocation W31241699681 @default.
• W3124169968 hasOpenAccess W3124169968 @default.
• W3124169968 hasPrimaryLocation W31241699681 @default.
• W3124169968 hasRelatedWork W1985664346 @default.
• W3124169968 hasRelatedWork W2152420694 @default.
• W3124169968 hasRelatedWork W2169575375 @default.
• W3124169968 hasRelatedWork W2347440206 @default.
• W3124169968 hasRelatedWork W2353781975 @default.
• W3124169968 hasRelatedWork W2356022153 @default.
• W3124169968 hasRelatedWork W2901259486 @default.
• W3124169968 hasRelatedWork W2963414935 @default.
• W3124169968 hasRelatedWork W3126873283 @default.
• W3124169968 hasRelatedWork W4289285260 @default.
• W3124169968 hasVolume "2021" @default.
• W3124169968 isParatext "false" @default.

• next