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Cognitive Computational Model Using Machine Learning Algorithm in Artificial Intelligence Environment

Shangyi Liu

Shangyi Liu

University of Science and Technology LiaoningAnshan, China
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Liu, Shangyi
, 
Constantin-Viktor Spiridonidis

Constantin-Viktor Spiridonidis

Department of Architecture, Faculty of Architecture and Interior Design, Canadian University DubaiDubai, United Arab Emirates
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Spiridonidis, Constantin-Viktor
 und 
Moaiad Ahmad Khder

Moaiad Ahmad Khder

Department of Business Administration, Faculty of Administration Sciences, Applied Science UniversityAl Eker, Kingdom of Bahrain
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Khder, Moaiad Ahmad
  
27. Dez. 2021
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Online veröffentlicht: 27. Dez. 2021
Seitenbereich: 803 - 814
Eingereicht: 17. Juni 2021
Akzeptiert: 24. Sept. 2021
DOI: https://doi.org/10.2478/amns.2021.2.00065
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© 2021 Shangyi Liu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

RBM network structure. RBM, restricted Boltzmann machine
RBM network structure. RBM, restricted Boltzmann machine

Fig. 2

DBN network. DBN: deep belief network; RBM: restricted Boltzmann machine
DBN network. DBN: deep belief network; RBM: restricted Boltzmann machine

Fig. 3

DBN training framework. DBN: deep belief network
DBN training framework. DBN: deep belief network

Fig. 4

Cognitive computational model based on machine learning algorithm
Cognitive computational model based on machine learning algorithm

Fig. 5

Relationship between model error rate and repetition number. DBN: deep belief network
Relationship between model error rate and repetition number. DBN: deep belief network

Fig. 6

Relationship between model error rate and number of units. DBN: deep belief network
Relationship between model error rate and number of units. DBN: deep belief network

Fig. 7

Relationship between model error rate and number of network layers. DBN: deep belief network
Relationship between model error rate and number of network layers. DBN: deep belief network

Context of import values

Imported value Context information
a1 g1, g2, g3, g4
a2 g1, g2, g3, g4
a3 g1, g2, g3, g4
a4 g1, g2, g3, g4
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Fachgebiete der Zeitschrift:
Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere
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