scholarly journals Control And Path Planning Of AUVs Robot Using Krill Herd Optimization Algorithm And Learning Automata

2020 ◽  
Vol 2 (2) ◽  
pp. 1-8
Author(s):  
Seyyed Alireza Razavi Asfali ◽  
Keyword(s):  
Path Planning ◽  
Optimization Algorithm ◽  
Learning Automata ◽  
Krill Herd

scholarly journals Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm

2020 ◽  
Vol 89 ◽  
pp. 106076 ◽  
Author(s):  
Fatin H. Ajeil ◽  
Ibraheem Kasim Ibraheem ◽  
Mouayad A. Sahib ◽  
Amjad J. Humaidi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Algorithm ◽  
Autonomous Mobile Robot ◽  
Multi Objective

scholarly journals Quantification of Epicardial and Thoracic Adipose Tissue using WOA Optimized CNN

2019 ◽  
Vol 8 (9S2) ◽  
pp. 720-724
Keyword(s):  
Adipose Tissue ◽  
Optimization Algorithm ◽  
Selection Process ◽  
Heart Diseases ◽  
Epicardial Fat ◽  
Fat Depots ◽  
Krill Herd ◽  
Whale Optimization ◽  
Fully Automatic ◽  
Paracardial Fat

Cardiac fat depots are associated with the heart diseases. Epicardial fat and thoracic fat plays the major role in the development of cardiovascular disease. The increased thickness of the epicardial and thoracic fat leads to several diseases such as metabolic syndrome, coronary atherosclerosis, etc. It is necessary to quantify the epicardial adipose tissue and thoracic adipose tissue. There are different imaging and assessing techniques for epicardial and thoracic adipose tissue quantification. These tissues can be quantified automatically or manually from the CT and MRI cardiac scans. The quantification of the epicardial fat and thoracic fat requires segmentation of these fats by various segmentation methods and then they are quantified. This project proposes the fully automatic segmentation and quantification of the epicardial and thoracic adipose tissues from the cardiac CT scan images using the krill herd optimization algorithm and fuzzy c-means segmentation algorithm. The whale optimization algorithm performs the feature selection process. The fuzzy cmeans algorithm is used for the segmentation process by means of clustering which segments the epicardial fat and paracardial adipose tissue(EAT &PAT) from the input image. The segmented epicardial and paracardial fat region are then used for the quantification process which provides the epicardial and thoracic fat volume. The thoracic fat is the combination of the epicardial and paracardial fat. This proposed system is implemented by using the MATLAB code. The proposed system is simple, fully automatic and produces accurate results.

scholarly journals Application research of ant colony cellular optimization algorithm in population evacuation path planning

2020 ◽  
Vol 69 (8) ◽  
pp. 080504
Author(s):  
Pei-Liang Wang ◽  
Ting Zhang ◽  
Ying-Jie Xiao
Keyword(s):  
Path Planning ◽  
Optimization Algorithm ◽  
Ant Colony ◽  
Application Research
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