Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
116
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 258 publications
(116 citation statements)
references
References 27 publications
0
116
0
Order By: Relevance
“…Two different topologies were applied (Local best and Global best referred in Section 2.3), in order to try to improve wind speed prediction for the best architecture found by ANN-LM model (model 3, case 2). In each topology, five different numbers of particles were tested (10,20,30,40, and 50) with the following PSO network parameters presented in Table 3.…”
Section: Forecasting Methodologymentioning
confidence: 99%
See 1 more Smart Citation
“…Two different topologies were applied (Local best and Global best referred in Section 2.3), in order to try to improve wind speed prediction for the best architecture found by ANN-LM model (model 3, case 2). In each topology, five different numbers of particles were tested (10,20,30,40, and 50) with the following PSO network parameters presented in Table 3.…”
Section: Forecasting Methodologymentioning
confidence: 99%
“…Advanced ANN techniques are also being applied to wind prediction. Khodayar et al argue that ANN may fail to provide the accuracy that is required, because they apply shallow architectures with error‐prone hand‐engineered features. Therefore, they propose a deep neural network (DNN) architecture with stacked autoencoder and stacked denoising autoencoder for ultrashort‐term and short‐term wind speed forecasting.…”
Section: Introductionmentioning
confidence: 99%
“…However, the NWP model usually runs once or twice a day, which is often applied for medium-to long-term forecasts [20].…”
Section: Mathematical Problems In Engineeringmentioning
confidence: 99%
“…Deep belief network, due to its strong ability of learning, has been performed in short-term WSP [26]. The stacked denoising autoencoder combined with rough set was applied to extract features from wind speed series [20]. In the literature [27], deep autoencoders act as base-regressors, whereas deep belief network is used as a metaregressor.…”
Section: Mathematical Problems In Engineeringmentioning
confidence: 99%
“…Different CNN structures have been developed to solve image processing, pattern recognition, classification, and other problems. Recently, CNNs have been used for facial recognition (Lawrence, Giles, Ah Chung, & Back, 1997), handwritten character classification (Ciresan, Meier, Gambardella, & Schmidhuber, 2011), visual document analysis (Simard, Steinkraus, & Platt, 2003), face sketch synthesis (Jiao, Zhang, Li, Liu, & Ma, 2018), microaneurysm detection (Chudzik, Majumdar, Calivá, Al-Diri, & Hunter, 2018), fingerprint enhancement (Li, Feng, & Kuo, 2018), the segmentation of glioma tumours in brains (Hussain, Anwar, & Majid, 2018), handwriting recognition (Baldominos, Saez, & Isasi, 2018), granite tile classification (Ferreira & Giraldi, 2017), segmenting the neuroanatomy (Wachinger, Reuter, & Klein, 2018), change detection using heterogeneous optical and radar images (Liu, Gong, Qin, & Zhang, 2018), predicting eye fixations (Liu, Han, Liu, & Li, 2018), improving acoustic source localization in noisy and reverberant conditions (Salvati, Drioli, & Foresti, 2018), chest disease detection (Abiyev & Ma'aitah, 2018), short-term wind speed forecasting (Khodayar, Kaynak, & Khodayar, 2017), natural language processing (Kalchbrenner, Grefenstette, & Blunsom, 2014), and image and video recognition problems (Karpathy et al, 2014) and showed good results.…”
mentioning
confidence: 99%