Cargando…

A Method Based on GA-CNN-LSTM for Daily Tourist Flow Prediction at Scenic Spots

Accurate tourist flow prediction is key to ensuring the normal operation of popular scenic spots. However, one single model cannot effectively grasp the characteristics of the data and make accurate predictions because of the strong nonlinear characteristics of daily tourist flow data. Accordingly,...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lu, Wenxing, Rui, Haidong, Liang, Changyong, Jiang, Li, Zhao, Shuping, Li, Keqing
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838789/ https://www.ncbi.nlm.nih.gov/pubmed/33286035 http://dx.doi.org/10.3390/e22030261

Ejemplares similares

Analysis of the Construction of Big Data Platform in Scenic Spots to Increase the Number of Tourists: Taking Sports Group Performance as an Example
por: Yu, Lin, et al.
Publicado: (2022)

A multi-agent model of traffic simulation around urban scenic spots: From the perspective of tourist behaviors
por: Cheng, Jing, et al.
Publicado: (2023)

Analysis and Research on Audience Satisfaction of Performing Arts Projects in Tourist Scenic Spots Based on the ASCI Model and Big Data
por: Ding, Jiaran, et al.
Publicado: (2022)

Retracted: Analysis and Research on Audience Satisfaction of Performing Arts Projects in Tourist Scenic Spots Based on the ASCI Model and Big Data
por: Environmental and Public Health, Journal of
Publicado: (2023)

CNN-LSTM vs. LSTM-CNN to Predict Power Flow Direction: A Case Study of the High-Voltage Subnet of Northeast Germany
por: Aksan, Fachrizal, et al.
Publicado: (2023)

Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods
por: Mohammed Alsumaidaee, Yaseen Ahmed, et al.
Publicado: (2023)

Path planning of scenic spots based on improved A* algorithm
por: Wang, Xingdong, et al.
Publicado: (2022)

CNN-Bi-LSTM: A Complex Environment-Oriented Cattle Behavior Classification Network Based on the Fusion of CNN and Bi-LSTM
por: Gao, Guohong, et al.
Publicado: (2023)

The Evaluation Method of Low-Carbon Scenic Spots by Combining IBWM with B-DST and VIKOR in Fuzzy Environment
por: Liu, Aijun, et al.
Publicado: (2019)

TV Scenic Design
por: Millerson, Gerald
Publicado: (2013)

Scenic Automation Handbook
por: Conner, Gareth
Publicado: (2018)

Scenic art for the theatre
por: Crabtree, Susan, et al.
Publicado: (2012)

Collaborative Filtering Algorithm-Based Destination Recommendation and Marketing Model for Tourism Scenic Spots
por: Lin, Kejun, et al.
Publicado: (2022)

SWOT Approach for Audience Online Conversion Rate: An Applied Research on Scenic Spot Projects
por: Ding, Jiaran
Publicado: (2022)

Attention Based CNN-ConvLSTM for Pedestrian Attribute Recognition
por: Li, Yang, et al.
Publicado: (2020)

Utilizing CNN-LSTM techniques for the enhancement of medical systems
por: Rayan, Alanazi, et al.
Publicado: (2023)

Consumption Structure Optimization Strategy for Scenic Spots Using the Deep Learning Model under Digital Economy
por: Wang, Yi, et al.
Publicado: (2022)

A CNN-LSTM Car-Following Model Considering Generalization Ability
por: Qin, Pinpin, et al.
Publicado: (2023)

Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy TOPSIS: A Case Study from 30 Provinces, China
por: Liang, Xuedong, et al.
Publicado: (2017)

Aeroengine Working Condition Recognition Based on MsCNN-BiLSTM
por: Zheng, Jinsong, et al.
Publicado: (2022)

Scenic screening sites of Sussex
por: Repose, V
Publicado: (2000)

The Craft and Art of Scenic Design
por: Klingelhoefer, Robert
Publicado: (2016)

NLOS Identification in WLANs Using Deep LSTM with CNN Features
por: Nguyen, Viet-Hung, et al.
Publicado: (2018)

A Deep CNN-LSTM Framework for Fast Video Coding
por: Bouaafia, Soulef, et al.
Publicado: (2020)

CNN and LSTM-Based Emotion Charting Using Physiological Signals
por: Dar, Muhammad Najam, et al.
Publicado: (2020)

Predicting Geolocation of Tweets: Using Combination of CNN and BiLSTM
por: Mahajan, Rhea, et al.
Publicado: (2021)

ECG signal classification based on deep CNN and BiLSTM
por: Cheng, Jinyong, et al.
Publicado: (2021)

Intelligent automatic sleep staging model based on CNN and LSTM
por: Zhuang, Lan, et al.
Publicado: (2022)

The Evaluation on the Credit Risk of Enterprises with the CNN-LSTM-ATT Model
por: Zhang, Lei
Publicado: (2022)

Development of CNN-LSTM combinational architecture for COVID-19 detection
por: Narula, Abhinav, et al.
Publicado: (2022)

Research on DNA-Binding Protein Identification Method Based on LSTM-CNN Feature Fusion
por: Lu, Weizhong, et al.
Publicado: (2022)

MPMABP: A CNN and Bi-LSTM-Based Method for Predicting Multi-Activities of Bioactive Peptides
por: Li, You, et al.
Publicado: (2022)

Emotion Analysis Model of Microblog Comment Text Based on CNN-BiLSTM
por: Li, Aichuan, et al.
Publicado: (2022)

Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network
por: Zhu, Fei, et al.
Publicado: (2019)

Automatic Detection of Atrial Fibrillation Based on CNN-LSTM and Shortcut Connection
por: Ping, Yongjie, et al.
Publicado: (2020)

Classification of Mental Stress Using CNN-LSTM Algorithms with Electrocardiogram Signals
por: Kang, Mingu, et al.
Publicado: (2021)

CNN-LSTM-Based Prognostics of Bidirectional Converters for Electric Vehicles’ Machine
por: Rojas-Dueñas, Gabriel, et al.
Publicado: (2021)

Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models
por: Shoeibi, Afshin, et al.
Publicado: (2021)

Language Processing Model Construction and Simulation Based on Hybrid CNN and LSTM
por: Zhang, Shujing
Publicado: (2021)

A hybrid CNN-LSTM model for pre-miRNA classification
por: Tasdelen, Abdulkadir, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_nttitmjtr80nfh49373bd181v0