Zhang, C (2020) Development of a creative platform for multiple-purpose predictions in tourism. PhD thesis, Bath Spa University.
Abstract
This research aims to use the ideas and theories of Creative Computing to create a user-orientated and integrated predicting platform for tourism industry. In the process of rapid development of global tourism, there are many problems. The reason why this research chooses to study tourism prediction is that the analysis and resolution of many problems depend on the prediction of development trend. The main content of this research is to apply the idea and method of creative computing to tourism prediction. The tourism predicting platform established in this research is multi-functional and can meet the predicting requirements of users' sing or multiple targets. Seven prediction models were built and the corresponding algorithms were designed to achieve this. In the process of building models, each model involves innovation based on the idea of creative computing. Some models use new techniques such as machine learning and neural networks. Some models use new methods, such as Gray model, gravity model. Some models use new variables, such as political, cultural and social factors. These have not been done before. This research defines tourism multi-structured data with five dimensions: source, type, content, structure, and application value. And the content of multi-structured data is classified from three aspects: human basic needs, spiritual needs, and social connections. This research creates some new data collection rules and presentation rules. For example, physics rules, psychology rules, and knowledge combination rules for data collection. Colour psychology rules, pattern recognition rules for data presentation, etc. Through the case study, the results of the predictions established in this research are very close to the real data, indicating that the prediction accuracy is high, and the prediction platform is reliable. It also shows that the research results based on creative computing have good application values.
| Item Type: | Thesis (PhD) |
|---|---|
| Divisions: | Bath School of Design |
| Date Deposited: | 02 Aug 2021 18:15 |
| Last Modified: | 07 Jan 2022 19:43 |
| URI / Page ID: | https://researchspace.bathspa.ac.uk/id/eprint/14226 |
 |
Request a change to this item or report an issue |
 |
Update item (repository staff only) |
Tools
Tools
