Solving the Problem of Distribution of Fiscal Coupons by Using a Steady State Genetic Algorithm

2018 ◽  
pp. 49-59
Author(s):  
Qëndresë Hyseni ◽  
Sule Yildirim Yayilgan ◽  
Bujar Krasniqi ◽  
Kadri Sylejmani
Keyword(s):  
Genetic Algorithm ◽  
Steady State

Feature selection for classification in Steady state visually evoked potentials (SSVEP)-based brain-computer interfaces with genetic algorithm

2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Stanisław Karkosz ◽  
Marcin Jukiewicz
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Steady State ◽  
Brain Computer Interface ◽  
Morphological Features ◽  
Computer Interface ◽  
Visually Evoked Potentials ◽  
Computer Interfaces ◽  
Subject Variability ◽  
Selection For

AbstractObjectivesOptimization of Brain-Computer Interface by detecting the minimal number of morphological features of signal that maximize accuracy.MethodsSystem of signal processing and morphological features extractor was designed, then the genetic algorithm was used to select such characteristics that maximize the accuracy of the signal’s frequency recognition in offline Brain-Computer Interface (BCI).ResultsThe designed system provides higher accuracy results than a previously developed system that uses the same preprocessing methods, however, different results were achieved for various subjects.ConclusionsIt is possible to enhance the previously developed BCI by combining it with morphological features extraction, however, it’s performance is dependent on subject variability.

Image reconstruction for a partially immersed perfectly conducting cylinder using the steady state genetic algorithm

Radio Science ◽  
2004 ◽  
Vol 39 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Ching-Lieh Li ◽  
Shao-Hon Chen ◽  
Chih-Ming Yang ◽  
Chien-Ching Chiu
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Image Reconstruction ◽  
Conducting Cylinder

Optimum Selection of Hydraulic Devices for Water Hammer Control in the Pipeline Systems Using Genetic Algorithm

2003 ◽  
Author(s):  
Bong Seong Jung ◽  
Bryan W. Karney
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Optimization Problems ◽  
System Optimization ◽  
Water Hammer ◽  
Pipeline System ◽  
Optimal Size ◽  
Protection Strategy ◽  
Hydraulic Devices ◽  
Selection Of

Genetic algorithms have been used to solve many water distribution system optimization problems, but have generally been limited to steady state or quasi-steady state optimization. However, transient events within pipe system are inevitable and the effect of water hammer should not be overlooked. The purpose of this paper is to optimize the selection, sizing and placement of hydraulic devices in a pipeline system considering its transient response. A global optimal solution using genetic algorithm suggests optimal size, location and number of hydraulic devices to cope with water hammer. This study shows that the integration of a genetic algorithm code with a transient simulator can improve both the design and the response of a pipe network. This study also shows that the selection of optimum protection strategy is an integrated problem, involving consideration of loading condition, device and system characteristics, and protection strategy. Simpler transient control systems are often found to outperform more complex ones.

An Investigation in Optimal Locations by Genetic Algorithm for Balancing Flexible Rotor-Bearing Systems

2005 ◽  
Author(s):  
Tsu-Wei Lin ◽  
Yuan Kang ◽  
Chun-Chieh Wang ◽  
Chuan-Wei Chang ◽  
Chih-Pin Chiang
Keyword(s):  
Genetic Algorithm ◽  
Finite Element Method ◽  
Steady State ◽  
Hermitian Matrix ◽  
Influence Coefficient ◽  
Steady State Response ◽  
Flexible Rotor ◽  
The Finite Element Method ◽  
State Response ◽  
Rotor Bearing

This study utilizes genetic algorithm to minimize the condition number of Hermitian matrix of influence coefficient (HMIC) to reduce the computation errors in balancing procedure. Then, the optimal locations of balancing planes and sensors would be obtained as fulfilling optimization. The finite element method is used to determine the steady-state response of flexible rotor-bearing systems. The optimization improves the balancing accuracy, which can be validated by the experiments of balancing a rotor kit.

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