SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Improving the forecasting accuracy of air passenger and air cargo demand: the application of back-propagation neural networks
16 references·3 citing·37 second hop
Improving the forecasting accuracy of air passenger and air cargo demand: the application of back-propagation neural networks (2012)Improving the forecasting accuracy of air…Tourism demand modelling and forecasting—A review of recent research (2007)Tourism demand modelling and …Gravity models for airline passenger volume estimation (2007)Gravity models for airline pa…International air network structures and air traffic density of world cities (2006)International air network str…The Airport Business (2005)The Airport BusinessFactors influencing cargo airlines’ choice of airport: An international survey (2005)Factors influencing cargo air…International urban systems and air passenger and cargo flows: some calculations (2004)International urban systems a…Choice of air cargo transshipment airport: an application to air cargo traffic to/from Northeast Asia (2004)Choice of air cargo transship…Analysis of an international air-cargo hub: the case of Hong Kong (2003)Analysis of an international …A comparison of three different approaches to tourist arrival forecasting (2003)A comparison of three differe…Price elasticities of demand for passenger air travel: a meta-analysis (2002)Price elasticities of demand …Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting (2000)Back-propagation learning in …A neural network model to forecast Japanese demand for travel to Hong Kong (1999)A neural network model to for…Improved grey prediction models for the trans‐pacific air passenger market (1998)Improved grey prediction mode…A demand model for scheduled airline services on international European routes (1997)A demand model for scheduled …Neural networks for financial forecasting (1995)Neural networks for financial…Industrial and business forecasting methods (1982)Industrial and business forec…Закономірності зміни параметрів функціонування системи міжміських пасажирських перевезень (2022)Закономірності зміни параметр…Global cargo gravitation model: airports matter for forecasts (2021)Global cargo gravitation mode…Air passenger forecasting using Neural Granger causal Google trend queries (2021)Air passenger forecasting usi…Forecasting tourism demand: A review of empirical research (1995)Earthquake devastation and recovery in tourism: the Taiwan case (2002)Designing an artificial neural network for forecasting tourism time series (2005)Effects of user-provided photos on hotel review helpfulness: An analytical approach with deep leaning (2017)Transportation demand analysis (1983)Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework (2009)The gravity model and trade flows: Recent developments in econometric modeling and empirical evidence (2017)Forecasting temporal world recovery in air transport markets in the presence of large economic shocks: The case of COVID-19 (2020)Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Forecasting Economic Time Series (2000)Social Media in Tourism and Hospitality: A Literature Review (2013)Progress and prospects for event tourism research (2015)Big data in tourism research: A literature review (2018)Time Series Analysis: Forecasting and Control. (1978)Analysis of international tourist arrivals in China: The role of World Heritage Sites (2009)Time series analysis forecasting and control (2009)Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm (2014)World Cities in a World-System (1997)Mapping world city networks through airline flows: context, relevance, and problems (2008)Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis (2018)How regional economic integration influence on urban land use efficiency? A case study of Wuhan metropolitan area, China (2019)The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950-1988 (1991)Concepts of Price Elasticities of Transport Demand and Recent Empirical Estimates: An Interpretative Survey (2005)Tourists' Perception of International Air Travel's Impact on the Global Climate and Potential Climate Change Policies (2007)High-speed rail and air transport competition: Game engineering as tool for cost-benefit analysis (2010)Consumer behaviour and demand response of tourists to climate change (2011)Decision support and expert systems (1993)Neural network forecasting of Canadian GDP growth (2001)Investment using technical analysis and fuzzy logic (2002)An empirical methodology for developing stockmarket trading systems using artificial neural networks (2008)Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention (2002)Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil (2011)Using the R-MAPE index as a resistant measure of forecast accuracy (2013)An application of DEA to measure the efficiency of Spanish airports prior to privatization (2001)Inefficiencies and scale economies of European airport operations (2003)Airport capacity and congestion when carriers have market power (2006)
this work references cited by second hop

References

  • 2007Tourism demand modelling and forecasting—A review of recent research1,419 cited
  • 1982Industrial and business forecasting methods515 cited
  • 2002Price elasticities of demand for passenger air travel: a meta-analysis357 cited
  • 2000Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting344 cited
  • 2003A comparison of three different approaches to tourist arrival forecasting322 cited
  • 1999A neural network model to forecast Japanese demand for travel to Hong Kong309 cited
  • 2007Gravity models for airline passenger volume estimation297 cited
  • 2005The Airport Business272 cited
  • 1995Neural networks for financial forecasting229 cited
  • 2004International urban systems and air passenger and cargo flows: some calculations172 cited
  • 1997A demand model for scheduled airline services on international European routes134 cited
  • 1998Improved grey prediction models for the trans‐pacific air passenger market120 cited
  • 2003Analysis of an international air-cargo hub: the case of Hong Kong119 cited
  • 2004Choice of air cargo transshipment airport: an application to air cargo traffic to/from Northeast Asia105 cited
  • 2006International air network structures and air traffic density of world cities

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

104 cited
  • 2005Factors influencing cargo airlines’ choice of airport: An international survey83 cited
  • Cited by

    • 2021Air passenger forecasting using Neural Granger causal Google trend queries35 cited
    • 2021Global cargo gravitation model: airports matter for forecasts17 cited
    • 2022Закономірності зміни параметрів функціонування системи міжміських пасажирських перевезень5 cited