Extraction of Abnormal Portion of Brain Using Jaya Algorithm

2017 ◽  
pp. 163-169
Author(s):  
Kanwarpreet Kaur ◽  
Gurjot Kaur ◽  
Jaspreet Kaur
Keyword(s):  
Jaya Algorithm

Multi-Start Jaya Algorithm for Software Module Clustering Problem

2018 ◽  
Vol 1 (1) ◽  
pp. 87-112 ◽  
Author(s):  
Kamal Z. Zamli ◽  
◽  
Abdulrahman Alsewari ◽  
Bestoun S. Ahmed ◽  
◽  
...  
Keyword(s):  
Jaya Algorithm ◽  
Software Module ◽  
Clustering Problem ◽  
Software Module Clustering

scholarly journals Optimized stable gait planning of biped robot using multi-objective evolutionary JAYA algorithm

2020 ◽  
Vol 17 (6) ◽  
pp. 172988142097634
Author(s):  
Huan Tran Thien ◽  
Cao Van Kien ◽  
Ho Pham Huy Anh
Keyword(s):  
Inverse Kinematics ◽  
Biped Robot ◽  
Step Length ◽  
Jaya Algorithm ◽  
Kinetic Chain ◽  
Biped Walking ◽  
Gait Planning ◽  
Multi Objective ◽  
Simulation And Experiment ◽  
Stable Gait

This article proposes a new stable biped walking pattern generator with preset step-length value, optimized by multi-objective JAYA algorithm. The biped robot is modeled as a kinetic chain of 11 links connected by 10 joints. The inverse kinematics of the biped is applied to derive the specified biped hip and feet positions. The two objectives related to the biped walking stability and the biped to follow the preset step-length magnitude have been fully investigated and Pareto optimal front of solutions has been acquired. To demonstrate the effectiveness and superiority of proposed multi-objective JAYA, the results are compared to those of MO-PSO and MO-NSGA-2 optimization approaches. The simulation and experiment results investigated over the real small-scaled biped HUBOT-4 assert that the multi-objective JAYA technique ensures an outperforming effective and stable gait planning and walking for biped with accurate preset step-length value.

A GPU-accelerated parallel Jaya algorithm for efficiently estimating Li-ion battery model parameters

2018 ◽  
Vol 65 ◽  
pp. 12-20 ◽  
Author(s):  
Long Wang ◽  
Zijun Zhang ◽  
Chao Huang ◽  
Kwok Leung Tsui
Keyword(s):  
Model Parameters ◽  
Jaya Algorithm ◽  
Li Ion Battery ◽  
Battery Model ◽  
Li Ion

Parameters identification for chaotic systems based on a modified Jaya algorithm

2018 ◽  
Vol 94 (4) ◽  
pp. 2307-2326 ◽  
Author(s):  
Feixin Chen ◽  
Zhenghao Ding ◽  
Zhongrong Lu ◽  
Xiangkun Zeng
Keyword(s):  
Chaotic Systems ◽  
Parameters Identification ◽  
Jaya Algorithm

scholarly journals Multi-Objective Optimization of Switched Reluctance Machine Design Using Jaya Algorithm (MO-Jaya)

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1107
Author(s):  
Mohamed Afifi ◽  
Hegazy Rezk ◽  
Mohamed Ibrahim ◽  
Mohamed El-Nemr
Keyword(s):  
Optimization Techniques ◽  
Design Parameters ◽  
Jaya Algorithm ◽  
Switched Reluctance Machine ◽  
Nsga Ii ◽  
Switched Reluctance ◽  
Multi Objective ◽  
Reluctance Machine ◽  
Linear Relationships ◽  
Forward Equations

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions.

Improved Binary JAYA algorithm-based scheduling dynamic cloud requests for Cloud-based computing

2021 ◽  
Author(s):  
Uttam Kumar Jena ◽  
Pradipta Kumar Das ◽  
Kaushik Mishra ◽  
Manas Ranjan Kabat
Keyword(s):  
Jaya Algorithm
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