Structure learning for belief rule base expert system: A comparative study

2013 ◽  
Vol 39 ◽  
pp. 159-172 ◽  
Author(s):  
Leilei Chang ◽  
Yu Zhou ◽  
Jiang Jiang ◽  
Mengjun Li ◽  
Xiaohang Zhang
2021 ◽  
pp. 113558
Author(s):  
You Cao ◽  
Zhijie Zhou ◽  
Changhua Hu ◽  
Shuaiwen Tang ◽  
Jie Wang

Author(s):  
Md. Mahashin Mia ◽  
Abdullah Al Hasan ◽  
Rahman Atiqur ◽  
Rashed Mustafa

<p><span>An intelligent belief rule base (BRB) based system with internet of things (IoT) integration can evaluate earthquake prediction (EP). This ingenious and rational system can predict earthquake by aggregating changed animal behavior combined with environmental and chemical changes which are taken as real time inputs from sensors. The BRB expert system blends knowledge demonstration criterion like attribute weight, rule weight, belief degree. The intelligent BRB system with IoT predicts the probable occurrence of the earthquake in a region based on the sign and symptoms culled by the persistent sensors. The final result taken from Intelligent BRB system with IoT integration is compared with expert and fuzzy-based system. The projected method gives a better prediction than the up-to-date expert system and fuzzy system</span></p>


Author(s):  
Zhi-Jie Zhou ◽  
Guan-Yu Hu ◽  
Chang-Hua Hu ◽  
Cheng-Lin Wen ◽  
Lei-Lei Chang

Algorithms ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 213
Author(s):  
Sharif Noor Zisad ◽  
Etu Chowdhury ◽  
Mohammad Shahadat Hossain ◽  
Raihan Ul Islam ◽  
Karl Andersson

Visual sentiment analysis has become more popular than textual ones in various domains for decision-making purposes. On account of this, we develop a visual sentiment analysis system, which can classify image expression. The system classifies images by taking into account six different expressions such as anger, joy, love, surprise, fear, and sadness. In our study, we propose an expert system by integrating a Deep Learning method with a Belief Rule Base (known as the BRB-DL approach) to assess an image’s overall sentiment under uncertainty. This BRB-DL approach includes both the data-driven and knowledge-driven techniques to determine the overall sentiment. Our integrated expert system outperforms the state-of-the-art methods of visual sentiment analysis with promising results. The integrated system can classify images with 86% accuracy. The system can be beneficial to understand the emotional tendency and psychological state of an individual.


2016 ◽  
Vol 96 ◽  
pp. 40-60 ◽  
Author(s):  
Ying-Ming Wang ◽  
Long-Hao Yang ◽  
Yang-Geng Fu ◽  
Lei-Lei Chang ◽  
Kwai-Sang Chin

2017 ◽  
Vol 9 (3) ◽  
pp. 168781401769457 ◽  
Author(s):  
Xiaojing Yin ◽  
Zhanli Wang ◽  
Bangcheng Zhang ◽  
Zhijie Zhou ◽  
Zhi Gao

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