Intelligence Science I

2017 ◽  
Keyword(s):  
Intelligence Science

Perspectives on Cognitive Informatics and Cognitive Computing

2010 ◽  
Vol 4 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Yingxu Wang ◽  
George Baciu ◽  
Yiyu Yao ◽  
Witold Kinsner ◽  
Keith Chan ◽  
...  
Keyword(s):  
Computational Linguistics ◽  
Computational Intelligence ◽  
Cognitive Computing ◽  
Cognitive Informatics ◽  
Intelligent Computing ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain ◽  
Science Information ◽  
Intelligence Science

Cognitive informatics is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. Cognitive computing is an emerging paradigm of intelligent computing methodologies and systems based on cognitive informatics that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This article presents a set of collective perspectives on cognitive informatics and cognitive computing, as well as their applications in abstract intelligence, computational intelligence, computational linguistics, knowledge representation, symbiotic computing, granular computing, semantic computing, machine learning, and social computing.

scholarly journals Implementation of Deep Learning for Slump Optimization Based on Concrete Quality Using Convolutional Neural Network in PT. SELO PROGO SAKTI

2020 ◽  
Vol 5 (2) ◽  
pp. 83-88
Author(s):  
Hedi Pandowo
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Deep Learning ◽  
Experimental Design ◽  
Convolutional Neural Network ◽  
Processing Unit ◽  
Training Process ◽  
Average Accuracy ◽  
Graphical Processing ◽  
Intelligence Science

Deep Learning is part of the scientific field of Machine Learning and Machine Learning is part of Artificial Intelligence science. Deep Learning has extraordinary capabilities by using a hardware Graphical Processing Unit (GPU) so that the artificial requirement network can run faster than using a Personal Computer Unit (CPU). Especially in terms of object classification in images using existing methods in the Convolutional Neural Network (CNN). The method used in this research is Preprocessing and Processing of Input Data, Training Process in which CNN is trained to obtain high accuracy from the classification carried out and the Testing Process which is a classification process using weights and bias from the results of the training process. This type of research is a pre experimental design (pre experimental design). The results of the object image classification test with different levels of confusion in the Concrete database with the Mix Design K-125, K-150, K-250 and K-300 produce an average accuracy value. This is also relevant to measuring the failure rate of concrete or slump

Intelligence Science

10.1142/8211 ◽  
2011 ◽  
Author(s):  
Zhongzhi Shi
Keyword(s):  
Intelligence Science
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