Gravitational Search Algorithm for Microseismic Source Location in Tunneling: Performance Analysis and Engineering Case Study

2019 ◽  
Vol 52 (10) ◽  
pp. 3999-4016 ◽  
Author(s):  
Chunchi Ma ◽  
Yupeng Jiang ◽  
Tianbin Li
Keyword(s):  
Performance Analysis ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Source Location ◽  
Microseismic Source Location ◽  
Gravitational Search

Gravitational Search Algorithm Optimization for PID Controller Tuning in Waste-water Treatment Process

2015 ◽  
Vol 73 (3) ◽  
Author(s):  
Mohamad Saiful Islam Aziz ◽  
Sophan Wahyudi Nawawi ◽  
Shahdan Sudin ◽  
Norhaliza Abdul Wahab ◽  
Mahdi Faramarzi ◽  
...  
Keyword(s):  
Pid Controller ◽  
Treatment Process ◽  
Search Algorithm ◽  
Waste Water Treatment ◽  
Gravitational Search Algorithm ◽  
Water Treatment Process ◽  
Pid Controller Tuning ◽  
Gravitational Search ◽  
Law Of Gravity

This paper presents a new approach of optimization technique in the controller parameter tuning for waste-water treatment process (WWTP) application. In the case study of WWTP, PID controller is used to control substrate (S) and dissolved oxygen (DO) concentration level. Too many parameters that need to be controlled make the system becomes complicated. Gravitational Search Algorithm (GSA) is used as the main method for PID controller tuning process. GSA is based on Newton's Law of Gravity and mass interaction. In this algorithm, the searcher agents survey the masses that interact with each other using law of gravity and law of motion. For WWTP system, the activated sludge reactor is used and this system is multi-input multi-output (MIMO) process. MATLAB is used as the platform to perform the simulation, where this optimization is compared to other established optimization method such as the Particle Swarm Optimization (PSO) to determine whether GSA has better features compared to PSO or vice-versa. Based on this case-study, the results show that transient response of GSA-PID was 20%-30% better compared to transient response of the PSO-PID controller.

Gravitational search algorithm using CUDA: a case study in high-performance metaheuristics

2014 ◽  
Vol 71 (4) ◽  
pp. 1277-1296 ◽  
Author(s):  
Amirreza Zarrabi ◽  
Khairulmizam Samsudin ◽  
Ettikan K. Karuppiah
Keyword(s):  
High Performance ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Gravitational Search

Analysis of Optimal Power Flow Using Gravitational Search Algorithm

2016 ◽  
Vol 3 (4) ◽  
pp. 1-11
Author(s):  
M. Lakshmikantha Reddy ◽  
◽  
M. Ramprasad Reddy ◽  
V.C. Veera Reddy ◽  
◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Power ◽  
Gravitational Search

Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm

2017 ◽  
Vol 27 (03) ◽  
pp. 343-372 ◽  
Author(s):  
Umit Can ◽  
Bilal Alatas
Keyword(s):  
Association Rules ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Search Space ◽  
Search Method ◽  
Quantitative Association Rules ◽  
Gravitational Search

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.

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