Results 31 to 40 of about 17,777,604 (295)

Forecasting Randomly Distributed Zero-Inflated Time Series

Folia Oeconomica Stetinensia, 2017
The main aim of the article is to propose a forecasting procedure that could be useful in the case of randomly distributed zero-inflated time series.
Doszyń Mariusz
doaj   +1 more source

Unilateral boundary time series forecasting

Frontiers in Big Data
Time series forecasting is an essential tool across numerous domains, yet traditional models often falter when faced with unilateral boundary conditions, where data is systematically overestimated or underestimated. This paper introduces a novel approach
Chao-Min Chang, Cheng-Te Li, Shou-De Lin
doaj   +1 more source

Time Series Forecastability Measures

CoRR
This paper proposes using two metrics to quantify the forecastability of time series prior to model development: the spectral predictability score and the largest Lyapunov exponent. Unlike traditional model evaluation metrics, these measures assess the inherent forecastability characteristics of the data before any forecast attempts.
Rui Wang, Steven Klee, Alexis Roos
openaire   +3 more sources

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

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

Robust Multi-Dimensional Time Series Forecasting

Entropy
Large-scale and high-dimensional time series data are widely generated in modern applications such as intelligent transportation and environmental monitoring. However, such data contains much noise, outliers, and missing values due to interference during
Chen Shen, Yong He, Jin Qin
doaj   +1 more source

Bridging the Loneliness Gap: Depression, Connectivity, and Isolation in Pediatric Oncology Patients and Their Peers

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld, Scott H. Maurer, Michelle D. Watkinson, John Nury, Elise Barberis, Molly C. Mack   +5 more
wiley   +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

HUTFormer: Hierarchical U-Net transformer for long-term traffic forecasting

Communications in Transportation Research
Traffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential component of intelligent transportation.
Zezhi Shao, Fei Wang, Tao Sun, Chengqing Yu, Yuchen Fang, Guangyin Jin, Zhulin An, Yang Liu, Xiaobo Qu, Yongjun Xu   +9 more
doaj   +1 more source

A Seasonal Autoregressive Integrated Moving Average (SARIMA) Model to Forecasting Tourist Arrival in the Philippines: A Case Study in Moalboal, Cebu (Philippines)

Recoletos Multidisciplinary Research Journal, 2020
Forecasting plays a critical part in implementing effective tourism management strategies. However, the role of tourism forecasting is not extensively studied in the Philippines, which is a key tourism destination in Southeast Asia.
Severina P. Velos, Marivel B. Go, Glynne P. Bate, Elvira B. Joyohoy   +3 more
doaj   +1 more source