Short-term time series algebraic forecasting with mixed smoothing

被引：12

作者：

Palivonaite, Rita ^{[1
]}

Lukoseviciute, Kristina ^{[1
]}

Ragulskis, Minvydas ^{[1
]}

机构：

[1] Kaunas Univ Technol, Res Grp Math & Numer Anal Dynam Syst, LT-51368 Kaunas, Lithuania

来源：

NEUROCOMPUTING | 2016年 / 171卷

关键词：

Time series prediction; Smoothing; Evolutionary algorithms; GENETIC ALGORITHM; NEURAL-NETWORKS; ELECTRICITY; OPTIMIZATION; MODEL;

D O I：

10.1016/j.neucom.2015.07.018

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Short-term time series algebraic prediction technique with mixed smoothing is presented in this paper. Evolutionary algorithms are employed for the identification of a near-optimal algebraic skeleton from the available data. Direct algebraic predictions are conciliated by internal errors of interpolation and external differences from the moving average. Computational experiments with real world time series are used to demonstrate the effectiveness of the proposed forecasting algorithm. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：854 / 865

页数：12

共 50 条

[1] Short-term time series algebraic forecasting with internal smoothing
[J]. Ragulskis, M. (minvydas.ragulskis@ktu.lt), 1600, Elsevier B.V., Netherlands (127):
[2] Short-term time series algebraic forecasting with internal smoothing
Palivonaite, Rita
Ragulskis, Minvydas
[J]. NEUROCOMPUTING, 2014, 127 : 161 - 171
[3] Chebyshev Interpolation with Internal Smoothing for Short-term Time Series Forecasting
Landauskas, Mantas
Lukoseviciute, Kristina
Lu, Guangqing
Ragulskis, Minvydas
[J]. INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2017), 2018, 1978
[4] Short-term time series forecasting based on the identification of skeleton algebraic sequences
Ragulskis, Minvydas
Lukoseviciute, Kristina
Navickas, Zenonas
Palivonaite, Rita
[J]. NEUROCOMPUTING, 2011, 74 (10) : 1735 - 1747
[5] A New Approach for Short-term Time Series Forecasting
Fan, Henghai
Wu, Shuai
Chen, Ning
Gao, Bo
Xu, Yiming
[J]. 2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2019), 2019, 646
[6] Short-term load forecasting using time series clustering
Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Lisbon, Portugal
不详
不详
[J]. Optim. Eng., 2022, 4 (2293-2314):
[7] Short-term load forecasting using time series clustering
Ana Martins
João Lagarto
Hiren Canacsinh
Francisco Reis
Margarida G. M. S. Cardoso
[J]. Optimization and Engineering, 2022, 23 : 2293 - 2314
[8] Short-term Electricity Load Forecasting with Time Series Analysis
Hung Nguyen
Hansen, Christian K.
[J]. 2017 IEEE INTERNATIONAL CONFERENCE ON PROGNOSTICS AND HEALTH MANAGEMENT (ICPHM), 2017, : 214 - 221
[9] THE TIME-SERIES APPROACH TO SHORT-TERM LOAD FORECASTING
HAGAN, MT
BEHR, SM
[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1987, 2 (03) : 785 - 791
[10] Short-term load forecasting using a chaotic time series
Michanos, SP
Tsakoumis, AC
Fessas, P
Vladov, SS
Mladenov, VM
[J]. SCS 2003: INTERNATIONAL SYMPOSIUM ON SIGNALS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS, 2003, : 437 - 440

← 1 2 3 4 5 →