Results 11 to 20 of about 93,376 (303)

Forecasting Techniques for Univariate Time Series Data: Analysis and Practical Applications by Category

Computer Sciences & Mathematics Forum
Effective forecasting is vital in various domains as it supports informed decision-making and risk mitigation. This paper aims to improve the selection of appropriate forecasting methods for univariate time series.
Leonard Dervishi, Antonios Raptakis, Gerald Bieber   +2 more
doaj   +2 more sources

Improving forecasting by estimating time series structural components across multiple frequencies [PDF]

, 2014
Identifying the appropriate time series model to achieve good forecasting accuracy is a challenging task. We propose a novel algorithm that aims to mitigate the importance of model selection, while increasing accuracy.
Trapero Arenas, J.R, Trapero, Juan R., Trapero, Juan Ramon, Kourentzes, Nikos, Petropoulos, Fotios, Kourentzes, Nikolaos,, Trapero, Juan R.,, Kourentzes, Nikolaos, Petropoulos, Fotios,   +8 more
core   +1 more source

Financial time series forecasting methods [PDF]

ITM Web of Conferences
The paper presents the development of time series forecasting algorithms based on the Integrated Autoregressive Moving Average Model (ARIMA) and the Fourier Expansion model.
Zinenko Anna, Stupina Alena
doaj   +1 more source

A Time Series Forecasting Method

ITM Web of Conferences, 2017
This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally.
Wang Zhao-Yu, Lin Yu-Chun, Lee Shie-Jue, Lai Chih-Chin   +3 more
doaj   +1 more source

Forecasting Time Series with Boot.EXPOS Procedure

Revstat Statistical Journal, 2009
To forecast future values of a time series is one of the main goals in times series analysis. Many forecasting methods have been developed and its performance evaluated.
Clara Cordeiro , M. Manuela Neves
doaj   +1 more source

Entanglement-Structured LSTM Boosts Chaotic Time Series Forecasting

Entropy, 2021
Traditional machine-learning methods are inefficient in capturing chaos in nonlinear dynamical systems, especially when the time difference Δt between consecutive steps is so large that the extracted time series looks apparently random.
Xiangyi Meng, Tong Yang
doaj   +1 more source

Time Series Forecasting With Volatility Activation Function

IEEE Access, 2022
Time series forecasting is the method of predicting future values of a model by reviewing its past data. Various models like traditional approaches, statistical methods, moving average, ARIMA, RNN’s, or XGBoost may also be applied.
Furkan Kayim, Atinc Yilmaz
doaj   +1 more source

Time series forecasting by means of evolutionary algorithms [PDF]

, 2007
IEEE International Parallel and Distributed Processing Symposium. Long Beach, CA, 26-30 March 2007Many physical and artificial phenomena can be described by time series. The prediction of such phenomenon could be as complex as interesting. There are many
Pedro Isasi Vinuela, Luque, Cristóbal, Jose Maria Valls Ferran, Valls, José M., Cristobal Luque, Isasi, Pedro   +5 more
core   +1 more source

Probabilistic-Based Forecasting Method For Time Series Datasets

Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2023
In this paper, a new probabilistic technique (a variant of Multiple Model Particle Filter-MMPF) will be used to predict time-series datasets. At first, the reliable performance of our method is proved using a virtual random scenario containing sixty ...
Abdullatif Baba
doaj   +1 more source

ShoTS Forecasting: Short Time Series Forecasting for Management Research

, 2022
We present a novel method for forecasting with limited information, that is for forecasting short time series. Our method is simple and intuitive; it relates to the most fundamental forecasting benchmark and is straightforward to implement.
Thomakos, D, Wood, G, Papagiannakis, G, Ioakimidis, M   +3 more
core   +1 more source