Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting
By Coskun Hamzaçebi, Diyar Akay, Fevzi Kutay. 2009
227 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Tugrul U. Daim
- V. Menon
- Erkam Güresen
- Gülgün Kayakutlu
- Saman Haratizadeh
- Ehsan Hoseinzade
- Prodromos Konstandinos Chourmouziadis
- D. Chatzoglou
In Management Science and Operations Research
- Tugrul U. Daim
- V. Menon
- Erkam Güresen
- Gülgün Kayakutlu
- Saman Haratizadeh
- Ehsan Hoseinzade
- Prodromos Konstandinos Chourmouziadis
- D. Chatzoglou
Citations in the corpus
- NSE Stock Market Prediction Using Deep-Learning Models (2018, methodology): “A time series is a set of data measured over time to acquire the status of some activity [6].”
- A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting (2016, unknown): “The study by [29] compared between the direct and the recursive strategies using the concept of grey relational analysis.”
- Using artificial neural network models in stock market index prediction (2011, background): “Hamzacebi, Akay, and Kutay (2009) compaired ARIMA and ANN and conclude that direct forecast with ANN is better and noted that before generalizing the conclusion other researchs should be done.”