Hybrid multi-model forecasting system: A case study on display market

نویسندگان

  • Chen-Chun Lin
  • Chun-Ling Lin
  • Joseph Z. Shyu
چکیده

Keywords: Hybrid multi-model forecasting system Prediction Display markets Mean square error (MSE) Mean absolute percentage error (MAPE) Average square root error (ASRE) a b s t r a c t This paper provides a novel hybrid multi-model forecasting system, with a special focus on the changing regional market demand in the display markets. Through an intensive case study of the ups and downs of the display industry, this paper examines the panel makers suffered from low panel price and unstable market demand, then they have changed to react to the rapid demand in the market or have lower panel stock for keeping supply and demand more balanced. In addition, this paper suggests a co-evolution forecasting process of sales and market factor. It can automatically apply various combinations of both linear and nonlinear models, and which alternatives deliver the lowest statistical error and produce a good estimate for the prediction of markets. Moreover, this article shows how the system is modeled and its accuracy is proved by means of experimental results; and judged by 3 evaluation criteria, including the mean square error (MSE), the mean absolute percentage error (MAPE), and the average square root error (ASRE) were used as the performance criteria to automatically select the optimal forecasting model. Finally, the results showed that the proposed system had considerably better predictive performance than previous and individual models. To summarize, the proposed system can reduce the user's effort for easier obtaining the desired forecasting results and create high quality forecasts. The flat-panel display (FPD) is a landmark sector all over the world in terms of technology innovation. This market is growing based on the competitiveness of three major technologies: thin-film transistor-liquid crystal displays (TFT-LCD), plasma display panels (PDP) and organic light-emitting diodes (OLED). TFT-LCD has the largest market share. This technology dominates the market, as it can be used in different types of applications, ranging from small devices including mobile phones to large applications including televisions. However, TFT-LCD manufacture has high risk and low affixa-tion. Because high-risk industry where failure for market estimation can lead to the elimination of an enterprise and where a timely, large-scale investment is essential; industry where large companies that should have the capacity to mobilize large capital are fully equipped with necessary parts and materials. Research on flat panel displays (FPD), which started in the 1960s, has finally reached the commercialization stage in the form of large …

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Forecasting Stock Price using Hybrid Model based on Wavelet Transform in Tehran and New York Stock Market

Forecasting financial markets is an important issue in finance area and research studies. On one hand, the importance of prediction, and on the other hand, its complexity, have led to huge number of researches which have proposed many forecasting methods in this area. In this study, we propose a hybrid model including Wavelet Transform, ARMA-GARCH and Artificial Neural Network (ANN) for single-...

متن کامل

Application of a New Hybrid Method for Day-Ahead Energy Price Forecasting in Iranian Electricity Market

Abstract- In a typical competitive electricity market, a large number of short-term and long-term contracts are set on basis of energy price by an Independent System Operator (ISO). Under such circumstances, accurate electricity price forecasting can play a significant role in improving the more reasonable bidding strategies adopted by the electricity market participants. So, they cannot only r...

متن کامل

An Improved Hybrid Model with Automated Lag Selection to Forecast Stock Market

Objective: In general, financial time series such as stock indexes have nonlinear, mutable and noisy behavior. Structural and statistical models and machine learning-based models are often unable to accurately predict series with such a behavior. Accordingly, the aim of the present study is to present a new hybrid model using the advantages of the GMDH method and Non-dominated Sorting Genetic A...

متن کامل

Nonlinear Model Improves Stock Return Out of Sample Forecasting (Case Study: United State Stock Market)

Improving out-of-sample forecasting is one of the main issues in financial research. Previous studies have achieved this objective by increasing the number of input variables or changing the kind of input variables. Changing the forecasting model is another possible approach to improve out-of-sample forecasting. Most researches have focused on linear models, while few have studied nonlinear mod...

متن کامل

Flood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique

Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Knowl.-Based Syst.

دوره 71  شماره 

صفحات  -

تاریخ انتشار 2014