scholarly journals A Novel Multiband Miniature Planar Inverted F Antenna Design for Bluetooth and WLAN Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
J. M. Jeevani W. Jayasinghe ◽  
Disala Uduwawala
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Ground Plane ◽  
Antenna Design ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Shorting Pin ◽  
5 Ghz ◽  
Patch Geometry ◽  
Compact Planar

A novel compact planar inverted F antenna (PIFA) optimized using genetic algorithms for 2.4 GHz (Bluetooth) and 5 GHz (UNII-1, UNII-2, UNII-2 extended, and UNII-3) bands is presented. The patch with a shorting pin is on a20×7×0.762 mm3substrate, which is suspended in air 5 mm above a30×7 mm2ground plane. Genetic algorithm optimization (GAO) is used to optimize the patch geometry, feed position, and shorting pin position simultaneously. Simulations are carried out by using HFSS and a prototype antenna is fabricated to compare the measurements with the simulations. The antenna shows fractional impedance bandwidths of 4% and 21% and gains of 2.5 dB and 3.2 dB at lower and upper bands, respectively.

scholarly journals Novel Quad-band Patch Antenna Design for Wireless Communications in 2.4, 5.2, 5.6 and 5.8 GHz Bands using Genetic Algorithm Optimization

2012 ◽  
Vol 1 (4) ◽  
pp. 466 ◽  
Author(s):  
J.M.J.W. Jayasinghe ◽  
D.N. Uduwawala
Keyword(s):  
Genetic Algorithm ◽  
Wireless Communications ◽  
Patch Antenna ◽  
Local Area ◽  
Coaxial Cable ◽  
Center Frequency ◽  
Fractional Bandwidth ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
5 Ghz

This paper presents the design of a novel quad band patch antenna for wireless communications in 2.4, 5.2, 5.6 and 5.8 GHz Bands. Antennas operating in these bands are available in various sizes and used in small hand-held devices as well as in wireless local area networks. A substrate with dielectric constant 3.2 and thickness 3.175mm is used for the design. The patch dimensions (40 30 mm) are similar to that of the conventional rectangular patch for the center frequency of the lowest frequency band which is 2.4 GHz. The antenna is fed by a 50? coaxial cable. Genetic algorithm optimization (GAO) is used to optimize the patch geometry and feed position. Simulations are carried out by using HFSS. The optimized antenna resonates at 2.4 GHz with fractional bandwidth of 4.1% and at 5 GHz bands with fractional bandwidth of 33.5%.

scholarly journals Optimization of Application of Genetic Algorithm Using C4.5 Method to Predict Breast Cancer Disease

bit-Tech ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 1-10
Author(s):  
Hartana Wijaya
Keyword(s):  
Breast Cancer ◽  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimization Techniques ◽  
The Body ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
C4.5 Algorithm ◽  
Parameter Values ◽  
Risk Of Cancer

Cancer is a big challenge for humanity. Cancer can affect various parts of the body. This deadly disease can be found in humans of all ages. However, the risk of cancer increases with age. Breast cancer is the most common cancer among women, and is the biggest cause of death for women. Then there are problems in the detection of breast cancer, causing patients to experience unnecessary treatment and huge costs. In a similar study, there were several methods used but there were problems due to the shape of nonlinear cancer cells. The C4.5 method can solve this problem, but C4.5 is weak in terms of determining parameter values, so it needs to be optimized. Genetic Algorithm is one of the good optimization methods, therefore the parameter values ​​of C4.5 will be optimized using Genetic Algorithms to get the best parameter values. The results of this study are that C4.5 Algorithm based on genetic algorithm optimization has a higher accuracy value (96%) than only using the C4.5 algorithm (94.99%) and which is optimized with the PSO algorithm (95.71%). This is evident from the increase in the value of accuracy of 1.01% for the C4.5 algorithm model that has been optimized with genetic algorithms. So it can be concluded that the application of genetic algorithm optimization techniques can increase the value of accuracy in the C4.5 algorithm.

scholarly journals Design of Dual Band Patch Antennas for Cellular Communications by Genetic Algorithm Optimization

2012 ◽  
Vol 1 (1) ◽  
pp. 26 ◽  
Author(s):  
Jeevani Jayasinghe ◽  
Disala Uduwawala ◽  
Jaume Anguera
Keyword(s):  
Genetic Algorithm ◽  
Practical Interest ◽  
Dual Band ◽  
Center Frequency ◽  
Patch Antennas ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Rectangular Patch ◽  
Shorting Pin ◽  
Final Design

Designing multiband antennas with low volume becomes of practical interest for mobile telecommunications. This paper presents the designs of five small dual band patch antennas for GSM 1800 (1710-1880MHz) and Bluetooth (2400-2483.5MHz) applications using a genetic algorithm combined with MoM (Method of Moments). A substrate with dielectric constant 3.2 and height 8mm is used for the first two dual band designs. The height is reduced thanks to the optimization process to 6mm in the third design by inserting a shorting pin to the fragmented patch antenna. Further the height is reduced to 4mm in the by inserting two shorting pins. In the final design with three shorting pins, the height is only 3mm. The patch dimensions are similar to that of the conventional rectangular patch for the center frequency of the lowest frequency band but with the advantage of having dual-band operation at the desired bands. Genetic algorithm optimization is used to optimize the patch geometry, feed position and shorting positions. HFSS is used to carry out simulations. The antenna thickness is reduced from 8mm to 3mm by incorporating shorting pins which position is optimized by the genetic algorithm.

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