A Hybrid Case-based Model for Forecasting
نویسندگان
چکیده
An investigation is described into the application of artificial intelligence to forecasting in the domain of oceanography. A hybrid approach to forecasting the thermal structure of the water ahead of a moving vessel is presented that combines the ability of a case-based reasoning system for identifying previously encountered similar situations and the generalising ability of an artificial neural network to guide the adaptation stage of the case-based reasoning mechanism. The system has been successfully tested in real time in the Atlantic Ocean; the results obtained are presented and compared with those derived from other forecasting methods.
منابع مشابه
Forecasting Air Pollution Concentrations in Iran, Using a Hybrid Model
The present study aims at developing a forecasting model to predict the next year’s air pollution concentrations in the atmosphere of Iran. In this regard, it proposes the use of ARIMA, SVR, and TSVR, as well as hybrid ARIMA-SVR and ARIMA-TSVR models, which combined the autoregressive part of the autoregressive integrated moving average (ARIMA) model with the support vector regression technique...
متن کاملEvaluation of the Neuro-Fuzzy and Hybrid Wavelet-Neural Models Efficiency in River Flow Forecasting (Case Study: Mohmmad Abad Watershed)
One of the most important issues in watersheds management is rainfall-runoff hydrological process forecasting. Using new models in this field can contribute to proper management and planning. In addition, river flow forecasting, especially in flood conditions, will allow authorities to reduce the risk of flood damage. Considering the importance of river flow forecasting in water resources ma...
متن کاملUsing Social and Economic Indicators for Modeling, Sensitivity Analysis and Forecasting the Gasoline Demand in the Transportation Sector: An ANN Approach in case study for Tehran metropolis
Compared to the conventional methods, Artificial Neural Networks (ANN) are considered to be one of the reliable tools for modeling of complex phenomena such as demand. Aim of this study is to provide a model for gasoline demand in transportation section of Tehran metropolis through multilayered perceptron neural network and using the presented model in analyzing the sensitivity of the model to ...
متن کاملA hybrid computational intelligence model for foreign exchange rate forecasting
Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...
متن کاملForecasting Air Pollution Concentrations in Iran, Using a Hybrid Model
The present study aims at developing a forecasting model to predict the next year’s air pollution concentrations in the atmosphere of Iran. In this regard, it proposes the use of ARIMA, SVR, and TSVR, as well as hybrid ARIMA-SVR and ARIMA-TSVR models, which combined the autoregressive part of the autoregressive integrated moving average (ARIMA) model with the support vector regression technique...
متن کاملForecasting 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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Applied Artificial Intelligence
دوره 15 شماره
صفحات -
تاریخ انتشار 2001