The analysis of ecological security and tourist satisfaction of ice-and-snow tourism under deep learning and the Internet of Things

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: May 10, 2024

Abstract This paper aims to propose a prediction method based on Deep Learning (DL) and Internet of Things (IoT) technology, focusing the ecological security tourist satisfaction Ice-and-Snow Tourism (IST) solve practical problems in this field. Accurate predictions IST have been achieved by collecting analyzing environment behavior data combining with DL models, such as convolutional recurrent neural networks. The experimental results show that proposed has significant advantages performance indicators, accuracy, F1 score, Mean Squared Error (MSE), correlation coefficient. Compared other similar methods, improves accuracy 3.2%, score 0.03, MSE 0.006, coefficient 0.06. These emphasize important role IoT technology predicting IST.

Language: Английский

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Multi-dimensional perceptual recognition of tourist destination using deep learning model and geographic information system

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0318846 - e0318846

Published: Feb. 7, 2025

Perceptual recognition of tourist destinations is vital in representing the destination image, supporting management decision-making, and promoting tourism recommendations. However, previous studies on perception have limitations regarding accuracy completeness related to research methods. This study addresses these by proposing an efficient strategy achieve precise perceptual while ensuring integrity user-generated content (UGC) data dimensions. We integrated various types UGC data, including images, texts, spatiotemporal information, create a comprehensive dataset. Then, we adopted improved Inception V3 model, bidirectional long short-term memory network (BiLSTM) model with multi-head attention, geographic information system (GIS) technology recognize basic feature from dataset, such as content, sentiment, dimensions achieving over 97%. Finally, progressive dimension combination method was proposed visualize analyze multiple perceptions. An experimental case demonstrated strategy’s effectiveness, focusing tourists’ perceptions Datong, China. Experimental results show that approach feasible for studying perception. Content perception, sentiment Datong’s spatial temporal characteristics were recognized analyzed efficiently. offers valuable guidance reference framework selecting methods technical routes

Language: Английский

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How do different ski resort attributes affect skiers' positive sentiments? Evidence from China

Journal of Destination Marketing & Management, Journal Year: 2025, Volume and Issue: 36, P. 100998 - 100998

Published: March 12, 2025

Language: Английский

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Enhancement of Harbin ice and snow tourism destination competitiveness: A large-scale data study based on sentiment analysis and Latent Dirichlet Allocation

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(3), P. e0319435 - e0319435

Published: March 21, 2025

In recent years, the ice and snow tourism industry has exhibited a concurrent state of vigorous expansion intense rivalry. Strengthening competitiveness is paramount significance for attaining dominant position in market. Thus, this study endeavors to dissect multi-dimensional determinants destinations from demand perspective establish an evaluation framework. Leveraging 48,420 tourist reviews sourced ten highly reputed attractions Harbin, text features were extracted via application Term Frequency - Inverse Document (TF-IDF). Subsequently, Latent Dirichlet Allocation (LDA) topic model was deployed precisely extract key themes. The sentiment inclination gauged by SnowNLP. Eventually, Importance Performance (IPA) utilized analyze strengths weaknesses competitiveness. outcomes are as follows: (1) Seven prominent themes, namely activities, environment, resources, historical cultural aspects, cost performance, service, experience, recognized potent driving forces. (2) Tourists manifested positive emotions high degree approval. (3) score Harbin destination determined be 0.64, with activities constituting advantage, whereas resources environment necessitating enhancement. This transcends constraints traditional supply-side-centered research. Innovatively, integrated into system, thereby augmenting connotations model. Based on LDA clustering results, analysis conducted, enhancing accuracy portraying tourists’ inner experiences. Concrete forward-looking strategic recommendations proffered destinations, furnishing theoretical practical guidance high-quality progression tourism.

Language: Английский

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Evaluating the Snow Cover Service Value on the Qinghai–Tibet Plateau

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(14), P. 2600 - 2600

Published: July 16, 2024

The Snow Cover Service Value (SCSV) is an important component of the ecological assets Qinghai–Tibet Plateau (QTP). Exploring SCSVs on QTP key to maintaining functions climate regulators and Asian water towers, it also theoretical basis for security barrier areas. Using multi-source data such as daily monthly observation sets related statistical yearbooks, evaluation framework was constructed first time. results showed that average annual SCSV from 2001 2020 6.99 trillion yuan, regulation value 5.81 which most SCSV. Inner Basin, Brahmaputra Yangtze Basin had highest SCSVs, while Yellow lowest unit SCSV, where vulnerable area snow cover resources QTP, significantly correlated with rainfall. correlation between temperature in Indus Ganges Basins significant. freshwater supply Tarim found be able reach 30% whole year June, would necessary pay attention risk flooding caused by snowmelt during melting period. Finally, this paper discussed strategies protection development each basin based spatial distribution characteristics, seasonal variation influencing factors SCSVs. research can provide reference rational allocation QTP.

Language: Английский

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Assessing the Perceived Benefits of Mega-Events during COVID-19: The Case of the Beijing 2022 Winter Olympic Games

Published: Aug. 14, 2024

Mega sporting events play a pivotal role in enabling host cities to stimulate urban regeneration and improvement. Numerous studies have examined the impact of mega from various perspectives; however, regarding residents’ perceptions such events, particularly context global pandemic, are lacking. Therefore, this study perceived benefits Beijing 2022 Winter Olympic Games on city image, satisfaction, loyalty. Data were collected 868 local residents Zhangjiakou, venues for Olympics. For data analysis, structural equation modelling was conducted using IBM SPSS 29.0 AMOS 29.0. The findings revealed significant economic, environmental, tourism contrast no sociocultural benefits. Additionally, image significantly influenced satisfaction exceptional situations as COVID-19 should focus developing resources long-term perspective.

Language: Английский

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The Ecological Safety Assessment and Brand Communication of Ice-Snow Tourism Under the Internet of Things and Deep Learning

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 128235 - 128244

Published: Jan. 1, 2023

In the current context of global climate change and threats to ecological environment, ice snow tourism destinations face significant challenges in security protection. The urgent question how scientifically assess status order formulate effective management protection strategies needs be addressed. is not only related preservation natural environment but also directly affects sustainable development brand image these destinations. Therefore, effectively communicating while protecting ecology has become an issue. Emerging technologies like Internet Things (IoT) deep learning hold great potential remote sensing processing data analysis can provide tools methods address above-mentioned issues. this study focuses on exploring application IoT assessment communication destinations, providing more grounded decision support for Taking destination Area C as a case study, first analyzes applications DL safety assessment. Subsequently, by utilizing DeeplabV3+ model land type classification combining Drive-Pressure-State-Impact-Response (DPSIR) Environment-Economy-Society (EES) model, DPSIR-EES constructed results indicate that, classification, overall accuracy reaches 91.56%, Kappa coefficient 0.862, significantly surpassing traditional methods, thereby demonstrating its superiority classification. reveals that remains stable between 0.88 0.89. Tourism spatial density one influencing factors safety, with obstacle factor 0.31, indicating significance economic safety. Finally, based aforementioned analysis, approaches shaping are proposed. This holds important practical better environmental enhancing value.

Language: Английский

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Perceived differences in coastal tourism image under tourist experience-IPA analysis based on UGC data of 12 coastal cities

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(8), P. e0299431 - e0299431

Published: Aug. 22, 2024

The destination image perceived by tourists is crucial to coastal tourism market positioning and marketing. This paper utilizes tourists’ Internet-generated content from 2017–2021, adopts the jieba text analysis method identify cognitive, emotional, overall of tourism, divides constituent elements into four main classes 20 subclasses through clustering method, explores perception with help IPA model. study found that: 1) commonality cognitive “ocean” in 12 cities outstanding, but internal characteristics are obvious, pay more attention Bohai Rim southern areas, Shanghai, Ningbo Hangzhou show strong correlation; 2) Tourists’ emotional destinations dominated positive attitudes, a high overlap adjectives representing emotions, heat differences different cities; 3) can be divided three circles, including “traditional core-characteristic structure-peripheral perception”, there obvious social semantic network each city; 4) Tourists satisfied components image, construction optimized environment. Based on this, process development, it necessary focus creating distinctive diversified values, focusing experience needs, improving quality facilities services, promoting high-quality development tourism.

Language: Английский

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