Holt–Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data

Pan

Mathematical Problems in Engineering

et al. 2018

Probability of spare parts sufficiency is crucial in the process of the normal operation of businesses, especially for the airline company. However, higher support sufficiency could inevitably lead to the increase of inventory cost of spare parts and restrict a company's efficiency. Therefore, it is important for businesses to reduce material cost on the premise of normal operation in order to accurately predict spare parts requirements based on reasonable models. The purpose of this paper is to solve problems with the evaluation of spare parts prediction models and to improve efficiency of company. Firstly, this paper summarizes a series of prediction models of spare parts requirements and applies the grey comprehensive correlation degree to rank the models. Secondly, the method of association rules mining is used to discover the association relationships between the types of spare parts and the prediction models. Finally, a case study in aviation is given to demonstrate the feasibility of the methodology, and optimal prediction models are recommended for aircraft spare parts. In accordance with the association relationships, the applicable prediction model can be provided in terms of different types of spare parts. This model will greatly enhance the work efficiency of spare parts prediction and improve the prediction tasks for the aircraft companies.

Section: Analysis Of Alternative Prediction Modelsmentioning

confidence: 99%

Method of Spare Parts Prediction Models Evaluation Based on Grey Comprehensive Correlation Degree and Association Rules Mining: A Case Study in Aviation

Pan

Mathematical Problems in Engineering

et al. 2018

“…Accurate estimates of initial conditions can result in better forecasting accuracy [1]. Recently, some researches have proposed maximum likelihood estimation for estimation of smoothing parameters and starting values [9,10], as well as other optimization methods [7,11,12]. In this research, new heuristic rules to estimate initial conditions for the Holt-Winters multiplicative method are introduced.…”

Section: Introductionmentioning

confidence: 99%

“…In [7], Bermudez, et al state: "Forecasting competitions have reported the surprising forecasting accuracy of Holt-Winters methods which were obtained with minimal effort in computation and model identification." However, standard exponential smoothing methods are commonly fitted in two steps.…”

Section: Introductionmentioning

confidence: 99%

New Estimation Rules for Unknown Parameters on Holt-Winters Multiplicative Method

Hansun

2017

J. Math. Fund. Sci.

Abstract. The Holt-Winters method is a well-known forecasting method used in time-series analysis to forecast future data when a trend and seasonal pattern is detected. There are two variations, i.e. the additive and the multiplicative method. Prior study by Vercher, et al. in [1] has shown that choosing the initial conditions is very important in exponential smoothing models, including the Holt-Winters method. Accurate estimates of initial conditions can result in better forecasting results. In this research, we propose new estimation rules for initial conditions for the Holt-Winters multiplicative method. The estimation rules were derived from the original initial conditions combined with the weighted moving average method. From the experimental results it was found that the new approach of the Holt-Winters multiplicative method can outperform the original Holt-Winters multiplicative method.

“…Bermudez, Segura and Vercher (2007) argued that the additive Holt-Winters model was inappropriate if the seasonal components or the error variance depend on the level of the series, but it could also be useful after an adequate data transformation for the UK air passenger data. In the study of Witt, Newbound and Watkins (1992) showed that the exponential smoothing generates method forecasts with lower error magnitudes than other modeling methods for Las Vegas arrivals data.…”

Section: Introductionmentioning

confidence: 99%

Tourist Arrivals in Sri Lanka: A Comparative Study of Holt- Winter’s versus Box- Jenkin’s Modeling Methods

Gnanapragasam

2018

OUSL Jnl

Tourism is one of the vastly growing and largest industries in the world. Contribution of tourism to Sri Lanka's total foreign exchange earnings in 2016 amounted to 14.2%. After the civil strife in Sri Lanka, tourist arrivals continue to grow annually. Therefore, the post-conflict tourist arrivals were considered for this study. Forecasting is an essential analytical tool in tourism policy and planning. In all the regions at all times, there is no specific model that outperforms other models regularly. Therefore, the objective of this study is to compare Holt-Winter's and Box-Jenkin's methods of modeling the tourist arrivals and to recommend a better method to forecast the future tourist arrivals in Sri Lanka. Appropriate tests were applied in modeling exercises for both methods. The results demonstrate that, during June 2009 to June 2017, nearly 10.5 million of tourists had visited the island. Both models are adequate for forecasting tourist arrivals. However, based on the forecasting accuracy measures of the model, the Box-Jenkin's method outperforms the Holt-Winter's method. The Box-Jenkin's model gives approximately 90% forecasting accuracy and therefore it is recommended to forecast the tourist arrivals in Sri Lanka. S. R. GnanapragasamAccordingly, around 1.15 million of tourists arrived in Sri Lanka in the second half of the year 2017, and it is about 5.7% increase compared to the same period in 2016. Further, over 235,000 tourists arrived in December 2017, which was the highest monthly arrival in the history of Sri Lanka tourism so far.