Results 21 to 30 of about 13,673 (195)
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2018 Günümüzde trafik kontrolsistemlerinin verimli çalışabilmesi için kısa dönemli trafiğin tahmin edilmesigerekli olmaktadır. Bu çalışmada, Kırıkkale İl sınırlarındaki (D-200, E88) karayoluna ait kısadönemli trafik tahmin modellerinin geliştirilmesi için ...
Erdem Doğan
doaj +1 more source
Regression-SARIMA modelling of daily peak electricity demand in South Africa
Journal of Energy in Southern Africa, 2017 In this paper, seasonal autoregressive integrated moving average (SARIMA) and regression with SARIMA errors (regression-SARIMA) models are developed to predict daily peak electricity demand in South Africa using data for the period 1996 to 2009.
Delson Chikobvu, Caston Sigauke
doaj +1 more source
Open Geosciences, 2022 Vietnam’s economy with agriculture and aquaculture still account for roughly 26% of the country’s gross domestic product, and nearly 70% of the Vietnamese population lives in rural areas; therefore, agriculture and aquaculture land use play a crucial ...
Wang YuRen, Giang Nguyen Hong
doaj +1 more source
JTAM (Jurnal Teori dan Aplikasi Matematika), 2022 From year to year, the number of ship passengers at Semayang Port, Balikpapan city tends to fluctuate. It also doubles in certain months and repeats every year. Sea transportation companies need to make forecasts in order to implement policies related to
Multiningsih Multiningsih +2 more
doaj +1 more source
Semi-automated simultaneous predictor selection for regression-SARIMA models [PDF]
Statistics and Computing, 2020 AbstractDeciding which predictors to use plays an integral role in deriving statistical models in a wide range of applications. Motivated by the challenges of predicting events across a telecommunications network, we propose a semi-automated, joint model-fitting and predictor selection procedure for linear regression models.
Aaron P. Lowther +3 more
openaire +3 more sources
Barekeng, 2022 Changes in extreme rainfall can cause disasters or losses for the wider community, so information about future rainfall is also needed. Rainfall is included in the category of time series data.
Ririn Amelia +3 more
doaj +1 more source
PSO based Neural Networks vs. Traditional Statistical Models for Seasonal Time Series Forecasting
, 2013 Seasonality is a distinctive characteristic which is often observed in many practical time series. Artificial Neural Networks (ANNs) are a class of promising models for efficiently recognizing and forecasting seasonal patterns.
Adhikari, Ratnadip +2 more
core +1 more source
Modeling and forecasting electricity spot prices: A functional data perspective [PDF]
, 2013 Classical time series models have serious difficulties in modeling and forecasting the enormous fluctuations of electricity spot prices. Markov regime switch models belong to the most often used models in the electricity literature.
Liebl, Dominik
core +3 more sources
Hybrid Machine Learning Models for Forecasting Surgical Case Volumes at a Hospital
AI, 2021 Recent developments in machine learning and deep learning have led to the use of multiple algorithms to make better predictions. Surgical units in hospitals allocate their resources for day surgeries based on the number of elective patients, which is ...
Agaraoli Aravazhi
doaj +1 more source
Pifu-xingbing zhenliaoxue zazhi[Objective] To construct a combination model integrating seasonal autoregressive integrated moving average (SARIMA) and generalized regression neural network (GRNN) to provide a new methodological approach for predicting the incidence trend of syphilis ...
CHEN Haiyan, ZHOU Luojing
doaj +1 more source