scholarly journals A novel grey–fuzzy–Markov and pattern recognition model for industrial accident forecasting

2017 ◽  
Vol 14 (3) ◽  
pp. 455-489
Author(s):  
Inyeneobong Ekoi Edem ◽  
Sunday Ayoola Oke ◽  
Kazeem Adekunle Adebiyi
Keyword(s):  
Pattern Recognition ◽  
Industrial Accident ◽  
Recognition Model

Information Entropy Based Fuzzy Pattern Recognition Model for Identification of Vulnerable Groups in Water Resource Conflicts

2014 ◽  
Vol 610 ◽  
pp. 316-319
Author(s):  
Li Feng Lv ◽  
Yan Ping Chen
Keyword(s):  
Pattern Recognition ◽  
Water Resource ◽  
Information Entropy ◽  
Water Rights ◽  
Liaoning Province ◽  
Vulnerable Groups ◽  
Recognition Model ◽  
Resource Conflicts ◽  
Fuzzy Pattern Recognition ◽  
Fuzzy Pattern

Identification of vulnerable groups in water resource conflicts is to improve the identification of vulnerable groups in the allocation of water rights and water markets water rights system. There are two difficulties: one is how to determine the weight of evaluation indexes; another is how to effectively deal with the subjectivity of the evaluation process and the low resolution. Therefore, this paper proposes “Information Entropy Based Fuzzy Pattern Recognition Model for Identification of Vulnerable Groups in Water Resource Conflicts (EFPQ-VRWC)” according to the fuzzy pattern recognition based on the combination of the maximum entropy principle and genetic algorithms. And identifying vulnerable groups of Daling River Basin in Liaoning Province, it illustrates the method of application value. And evaluation results have continuity, comparability and versatility so that can accurately reflect the level of vulnerable groups in water resource conflicts.

scholarly journals Intelligent Face Tracking for Collaborative Synchronous e-Learning using Pattern Recognition Model

2021 ◽  
Vol 15 ◽  
pp. 105-109
Author(s):  
Kittimasak Naijit
Keyword(s):  
Pattern Recognition ◽  
Rapid Evolution ◽  
Product Evaluation ◽  
Face Tracking ◽  
Recognition Model ◽  
Synchronous Learning ◽  
Online Classrooms ◽  
Instructional Needs ◽  
E Learning ◽  
Evolution Of Technology

Intelligent Face Tracking for Collaborative Synchronous e-Learning using Pattern Recognition Model can provide high levels of interaction for distance learning initiatives. With the rapid evolution of technology, face recognition login and tracking, continuous product evaluation is necessary to ensure optimal methods and resources for connecting students, instructors, and educational content in rich, online learning communities. This article presents the analysis of online, synchronous learning solutions. Focusing on their abilities to meet technical and pedagogical needs in higher education. To make a solid comparison, the systems were examined in online classrooms with instructors, guest speakers, and students. Relative to usability, instructional needs, technical aspects and compatibility are outlined for systems.

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