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Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting
16 references·1 citing·38 second hopsampled
Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting (2018)Modeling a combined forecast algorithm ba…Seasonal SVR with FOA algorithm for single-step and multi-step ahead forecasting in monthly inbound tourist flow (2016)Seasonal SVR with FOA algorit…Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm (2014)Forecasting holiday daily tou…A meta-analysis of international tourism demand forecasting and implications for practice (2014)A meta-analysis of internatio…Forecasting tourism demand to Catalonia: Neural networks vs. time series models (2013)Forecasting tourism demand to…Forecasting of Hong Kong airport's passenger throughput (2013)Forecasting of Hong Kong airp…Developing a hybrid intelligent model for forecasting problems: Case study of tourism demand time series (2013)Developing a hybrid intellige…The adaptive fuzzy time series model with an application to Taiwan’s tourism demand (2011)The adaptive fuzzy time serie…Forecasting tourism demand based on empirical mode decomposition and neural network (2011)Forecasting tourism demand ba…SVR with hybrid chaotic genetic algorithms for tourism demand forecasting (2010)SVR with hybrid chaotic genet…Regularized least squares fuzzy support vector regression for financial time series forecasting (2007)Regularized least squares fuz…Constructing and applying an improved fuzzy time series model: Taking the tourism industry for example (2007)Constructing and applying an …A fractionally integrated autoregressive moving average approach to forecasting tourism demand (2007)A fractionally integrated aut…Support vector machine with adaptive parameters in financial time series forecasting (2003)Support vector machine with a…Predicting tourism demand using fuzzy time series and hybrid grey theory (2003)Predicting tourism demand usi…Forecasting Turkey's tourism revenues by ARMAX model (2003)Forecasting Turkey's tourism …Financial time series forecasting using support vector machines (2003)Financial time series forecas…A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting (2019)A review of research on touri…Book Review: Time Series Analysis: Forecasting and Control (1977)Application of support vector machines in financial time series forecasting (2001)Forecasting stock market movement direction with support vector machine (2004)Support vector regression with chaos-based firefly algorithm for stock market price forecasting (2012)Artificial intelligence and big data in tourism: a systematic literature review (2020)Control problems of grey systems (1982)Forecasting enrollments with fuzzy time series — Part I (1993)Forecasting enrollments based on fuzzy time series (1996)How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach (2015)Forecasting with artificial neural networks: (1998)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)BUSINESS RESEARCH METHODS (PHƯƠNG PHÁP NGHIÊN CỨU TRONG KINH DOANH) (2023)Trends and random walks in macroeconmic time series (1982)Tourism demand modelling and forecasting—A review of recent research (2007)Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series (2019)Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions (2022)An Almost Ideal Demand System (1980)Time series forecasting using a hybrid ARIMA and neural network model (2003)Another look at measures of forecast accuracy (2006)Bibliometric studies in tourism (2016)Forecasting tourism demand with composite search index (2016)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Testing for a Unit Root in Time Series Regression (1988)Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Forecasting temporal world recovery in air transport markets in the presence of large economic shocks: The case of COVID-19 (2020)A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)Designing a neural network for forecasting financial and economic time series (1996)Financial time series forecasting using independent component analysis and support vector regression (2009)Financial time series forecasting with multi-modality graph neural network (2021)New developments in tourism and hotel demand modeling and forecasting (2017)Forecasting tourist arrivals with machine learning and internet search index (2018)Tourism Demand and the COVID-19 Pandemic: An LSTM Approach (2020)Forecasting tourism recovery amid COVID-19 (2021)Forecasting: theory and practice (2022)
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References

  • 2003Financial time series forecasting using support vector machines1,746 cited
  • 2003Support vector machine with adaptive parameters in financial time series forecasting1,008 cited
  • 2014Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm293 cited
  • 2013Forecasting tourism demand to Catalonia: Neural networks vs. time series models270 cited
  • 2010SVR with hybrid chaotic genetic algorithms for tourism demand forecasting264 cited
  • 2014A meta-analysis of international tourism demand forecasting and implications for practice262 cited
  • 2011Forecasting tourism demand based on empirical mode decomposition and neural network217 cited
  • 2003Predicting tourism demand using fuzzy time series and hybrid grey theory201 cited
  • 2013Forecasting of Hong Kong airport's passenger throughput186 cited
  • 2007A fractionally integrated autoregressive moving average approach to forecasting tourism demand122 cited
  • 2013Developing a hybrid intelligent model for forecasting problems: Case study of tourism demand time series109 cited
  • 2007Regularized least squares fuzzy support vector regression for financial time series forecasting106 cited
  • 2003Forecasting Turkey's tourism revenues by ARMAX model85 cited
  • 2011The adaptive fuzzy time series model with an application to Taiwan’s tourism demand

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75 cited
  • 2007Constructing and applying an improved fuzzy time series model: Taking the tourism industry for example69 cited
  • 2016Seasonal SVR with FOA algorithm for single-step and multi-step ahead forecasting in monthly inbound tourist flow68 cited
  • Cited by

    • 2019A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting551 cited