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Refinado por: assunto: Maschinelles Lernen remover Expert Systems With Applications remover
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An efficient stripped cover-based accelerator for reduction of attributes in incomplete decision tables
An efficient stripped cover-based accelerator for reduction of attributes in incomplete decision tables
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An efficient stripped cover-based accelerator for reduction of attributes in incomplete decision tables

Thuy, Nguyen Ngoc ; Wongthanavasu, Sartra

Expert systems with applications, 2020-04, Vol.143, p.113076, Article 113076 [Periódico revisado por pares]

New York: Elsevier Ltd

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2
Portfolio management via two-stage deep learning with a joint cost
Portfolio management via two-stage deep learning with a joint cost
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Portfolio management via two-stage deep learning with a joint cost

Yun, Hyungbin ; Lee, Minhyeok ; Kang, Yeong Seon ; Seok, Junhee

Expert systems with applications, 2020-04, Vol.143, p.113041, Article 113041 [Periódico revisado por pares]

New York: Elsevier Ltd

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3
Website categorization: A formal approach and robustness analysis in the case of e-commerce detection
Website categorization: A formal approach and robustness analysis in the case of e-commerce detection
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Website categorization: A formal approach and robustness analysis in the case of e-commerce detection

Bruni, Renato ; Bianchi, Gianpiero

Expert systems with applications, 2020-03, Vol.142, p.113001, Article 113001 [Periódico revisado por pares]

New York: Elsevier Ltd

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4
Time-varying hierarchical chains of salps with random weight networks for feature selection
Time-varying hierarchical chains of salps with random weight networks for feature selection
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Time-varying hierarchical chains of salps with random weight networks for feature selection

Faris, Hossam ; Heidari, Ali Asghar ; Al-Zoubi, Ala’ M. ; Mafarja, Majdi ; Aljarah, Ibrahim ; Eshtay, Mohammed ; Mirjalili, Seyedali

Expert systems with applications, 2020-02, Vol.140, p.112898, Article 112898 [Periódico revisado por pares]

New York: Elsevier Ltd

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5
Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0
Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0
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Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0

Romeo, Luca ; Loncarski, Jelena ; Paolanti, Marina ; Bocchini, Gianluca ; Mancini, Adriano ; Frontoni, Emanuele

Expert systems with applications, 2020-02, Vol.140, p.112869, Article 112869 [Periódico revisado por pares]

New York: Elsevier Ltd

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6
Continuous control with Stacked Deep Dynamic Recurrent Reinforcement Learning for portfolio optimization
Continuous control with Stacked Deep Dynamic Recurrent Reinforcement Learning for portfolio optimization
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Continuous control with Stacked Deep Dynamic Recurrent Reinforcement Learning for portfolio optimization

Aboussalah, Amine Mohamed ; Lee, Chi-Guhn

Expert systems with applications, 2020-02, Vol.140, p.112891, Article 112891 [Periódico revisado por pares]

New York: Elsevier Ltd

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7
Using high-fidelity meta-models to improve performance of small dataset trained Bayesian Networks
Using high-fidelity meta-models to improve performance of small dataset trained Bayesian Networks
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Using high-fidelity meta-models to improve performance of small dataset trained Bayesian Networks

MacAllister, Anastacia ; Kohl, Adam ; Winer, Eliot

Expert systems with applications, 2020-01, Vol.139, p.112830, Article 112830 [Periódico revisado por pares]

New York: Elsevier Ltd

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8
Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices
Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices
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Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices

Orimoloye, Larry Olanrewaju ; Sung, Ming-Chien ; Ma, Tiejun ; Johnson, Johnnie E.V.

Expert systems with applications, 2020-01, Vol.139, p.112828, Article 112828 [Periódico revisado por pares]

New York: Elsevier Ltd

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9
A hybrid data mining approach for identifying the temporal effects of variables associated with breast cancer survival
A hybrid data mining approach for identifying the temporal effects of variables associated with breast cancer survival
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A hybrid data mining approach for identifying the temporal effects of variables associated with breast cancer survival

Simsek, Serhat ; Kursuncu, Ugur ; Kibis, Eyyub ; AnisAbdellatif, Musheera ; Dag, Ali

Expert systems with applications, 2020-01, Vol.139, p.112863, Article 112863 [Periódico revisado por pares]

New York: Elsevier Ltd

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10
Fuzzy rule based unsupervised sentiment analysis from social media posts
Fuzzy rule based unsupervised sentiment analysis from social media posts
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Fuzzy rule based unsupervised sentiment analysis from social media posts

Vashishtha, Srishti ; Susan, Seba

Expert systems with applications, 2019-12, Vol.138, p.112834, Article 112834 [Periódico revisado por pares]

New York: Elsevier Ltd

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