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Evaluation of statistical and machine learning models for time series prediction identifying the state-of-the-art and the best conditions for the use of each model
Evaluation of statistical and machine learning models for time series prediction identifying the state-of-the-art and the best conditions for the use of each model
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Evaluation of statistical and machine learning models for time series prediction identifying the state-of-the-art and the best conditions for the use of each model

Antonio Rafael Sabino Parmezan Vinícius M. A Souza; Gustavo Enrique de Almeida Prado Alves Batista

Information Sciences New York : Elsevier v. 484, p. 302-337, May 2019

New York 2019

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-2930914 )(Acessar)

2
Innovative ensemble system based on mixed frequency modeling for wind speed point and interval forecasting
Innovative ensemble system based on mixed frequency modeling for wind speed point and interval forecasting
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Innovative ensemble system based on mixed frequency modeling for wind speed point and interval forecasting

Yang, Wendong ; Hao, Mengying ; Hao, Yan

Information sciences, 2023-04, Vol.622, p.560-586 [Periódico revisado por pares]

Elsevier Inc

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3
Random vector functional link network for short-term electricity load demand forecasting
Random vector functional link network for short-term electricity load demand forecasting
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Random vector functional link network for short-term electricity load demand forecasting

Ren, Ye ; Suganthan, P.N. ; Srikanth, N. ; Amaratunga, Gehan

Information sciences, 2016-11, Vol.367-368, p.1078-1093 [Periódico revisado por pares]

Elsevier Inc

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4
Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models
Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models
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Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models

Purohit, Sourav Kumar ; Panigrahi, Sibarama

Information sciences, 2024-02, Vol.658, p.120021, Article 120021 [Periódico revisado por pares]

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5
FQTSFM: A fuzzy-quantum time series forecasting model
FQTSFM: A fuzzy-quantum time series forecasting model
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FQTSFM: A fuzzy-quantum time series forecasting model

Singh, Pritpal

Information sciences, 2021-08, Vol.566, p.57-79 [Periódico revisado por pares]

Elsevier Inc

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6
TFFS: A trainable federal fusion strategy for multistep time series forecasting
TFFS: A trainable federal fusion strategy for multistep time series forecasting
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TFFS: A trainable federal fusion strategy for multistep time series forecasting

Shao, Xiaorui ; Kim, Chang-Soo

Information sciences, 2024-09, Vol.679, p.121126, Article 121126 [Periódico revisado por pares]

Elsevier Inc

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7
Enhancing time series forecasting: A hierarchical transformer with probabilistic decomposition representation
Enhancing time series forecasting: A hierarchical transformer with probabilistic decomposition representation
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Enhancing time series forecasting: A hierarchical transformer with probabilistic decomposition representation

Tong, Junlong ; Xie, Liping ; Yang, Wankou ; Zhang, Kanjian ; Zhao, Junsheng

Information sciences, 2023-11, Vol.647, p.119410, Article 119410 [Periódico revisado por pares]

Elsevier Inc

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8
Information granules-based long-term forecasting of time series via BPNN under three-way decision framework
Information granules-based long-term forecasting of time series via BPNN under three-way decision framework
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Information granules-based long-term forecasting of time series via BPNN under three-way decision framework

Zhu, Chenglong ; Ma, Xueling ; Zhang, Chao ; Ding, Weiping ; Zhan, Jianming

Information sciences, 2023-07, Vol.634, p.696-715 [Periódico revisado por pares]

Elsevier Inc

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9
Improved dendritic learning: Activation function analysis
Improved dendritic learning: Activation function analysis
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Improved dendritic learning: Activation function analysis

Wang, Yizheng ; Yu, Yang ; Zhang, Tengfei ; Song, Keyu ; Wang, Yirui ; Gao, Shangce

Information sciences, 2024-09, Vol.679, p.121034, Article 121034 [Periódico revisado por pares]

Elsevier Inc

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10
A hybrid multi-resolution multi-objective ensemble model and its application for forecasting of daily PM2.5 concentrations
A hybrid multi-resolution multi-objective ensemble model and its application for forecasting of daily PM2.5 concentrations
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A hybrid multi-resolution multi-objective ensemble model and its application for forecasting of daily PM2.5 concentrations

Liu, Hui ; Duan, Zhu ; Chen, Chao

Information sciences, 2020-04, Vol.516, p.266-292 [Periódico revisado por pares]

Elsevier Inc

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Deste Autor:

  1. Parmezan, A
  2. Batista, G
  3. Souza, V

Neste Assunto:

  1. Computer Science
  2. Computer Science, Information Systems
  3. Science & Technology
  4. Technology
  5. Forecasting

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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