scholarly journals Application of Genetic Algorithm for Binary Optimization of Microstrip Antennas: A Review

2021 ◽  
Vol 5 (4) ◽  
pp. 315-333
Author(s):  
Jeevani W. Jayasinghe ◽  
Keyword(s):  
Genetic Algorithm ◽  
Performance Enhancement ◽  
Optimization Procedure ◽  
Microstrip Antennas ◽  
Optimization Techniques ◽  
Global Optimizer ◽  
Trial And Error Method ◽  
Miniature Antennas ◽  
Local Optimizer ◽  
Error Method

<abstract> <p>Researchers have proposed applying optimization techniques to improve performance of microstrip antennas (MSAs) in terms of bandwidth, radiation characteristics, polarization, directivity and size. The drawbacks of the conventional MSAs can be overcome by optimizing the antenna parameters while keeping a compact configuration. Applying a global optimizer is a better technique than using a local optimizer or a trial and error method for performance enhancement. This paper discusses genetic algorithm (GA) optimization of microstrip antennas presented by the antenna research community. The GA optimization procedure, antenna parameters optimized by using GA and the optimization objectives are presented by reviewing the literature. Further, evolution of GA in the field of MSAs and its significance are explored. Application of GA optimization to design broadband, multiband, high-directivity and miniature antennas is demonstrated with the support of several case studies giving an insight for further developments in the field.</p> </abstract>

scholarly journals Hybrid Optimization Based Mathematical Procedure for Dimensional Synthesis of Slider-Crank Linkage

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1581
Author(s):  
Alfonso Hernández ◽  
Aitor Muñoyerro ◽  
Mónica Urízar ◽  
Enrique Amezua
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Linear Equations ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Dimensional Synthesis ◽  
Hybrid Strategy ◽  
Dimensional Parameters ◽  
Optimization Methodology ◽  
Crank Mechanism

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.

Weight Optimization of Steel Frames Using Genetic Algorithm

2002 ◽  
Vol 5 (2) ◽  
pp. 99-111 ◽  
Author(s):  
Ribelito F. Torregosa ◽  
Worsak Kanok-Nukulchai
Keyword(s):  
Genetic Algorithm ◽  
Steel Frames ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Weight Optimization ◽  
Discrete Variables ◽  
Design Problems ◽  
Plane Frames ◽  
Population Sizes ◽  
A New Technique

Genetic Algorithm (GA) is a new technique in optimization procedure that works best in design problems with discrete variables. It employs the survival of the fittest philosophy in determining the optimum combination. GA optimization procedure is applied to weight optimization of steel plane frames subjected to different load cases. Database of steel beam sizes is provided as the discrete variables. Both elitist and non-elitist search procedures are used to optimize the total weight of steel frames. Crossover types used are 20- and 50-percent uniform. Optimization result using population sizes 10, 20, and 40 are compared. Elitist search procedure showed superior results when compared to non-elitist for higher population sizes search because of its faster convergence rate. Performance of non-elitist is superior when using lesser population sizes. To examine the performance of genetic algorithms, case studies are conducted by varying material groups and the results are compared with the results from other optimization techniques. Genetic optimization showed superior results when compared to other techniques especially to problems with few material groupings.

Adaptive Genetic Algorithm Based Parameters Optimization of PI Controller for Battery System in Wind Farm

2014 ◽  
Vol 1055 ◽  
pp. 375-382
Author(s):  
Hui Ren ◽  
Dan Wei ◽  
David Watts ◽  
Jia Qi Fan
Keyword(s):  
Genetic Algorithm ◽  
Wind Farm ◽  
Storage System ◽  
Pi Controller ◽  
Parameters Optimization ◽  
Adaptive Genetic Algorithm ◽  
Trial And Error ◽  
Battery System ◽  
Trial And Error Method ◽  
Error Method

The randomness and intermittence of wind farm real power generation bring challenges to power system operation, and installing battery system for the mitigation of the fluctuation of wind farm output, following the short-term forecasting curve, even adjusting the output according to the operator’s requirement is a possible way to address the problem from the wind farm side. After a review of various storage control strategies for stabilizing the fluctuation of wind power output, the model of battery energy storage system as well as its control strategy is introduced. Adaptive Genetic Algorithm (AGA) is used for the optimization of PI control parameters. Simulation shows the effectiveness of the proposed method. Moreover, comparing with the trial-and-error method, the optimization algorithm proposed has the advantage of finding the optimal parameters under the lack of experience on PID control, and combined with trial-and-error method, the difficulties engineer could face on tuning the parameters of PI controller is decreased, which increases the feasibility for parameters of PI controller’s being transplanted to similar applications.

scholarly journals Total Internal Reflection-Based High Efficiency Grating Design for a Metal-Free Polarizing Filter Applications Using Hybrid Optimization Procedure

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
ChaBum Lee
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Total Internal Reflection ◽  
Optimization Problems ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Internal Reflection ◽  
Hybrid Optimization ◽  
Design Parameters ◽  
Metal Free

This paper presents a fast and rigorous design method for grating-based metal-free polarizing filter applications using two-step hybrid optimization techniques. Grating structures utilizing the total internal reflection in a lamellar configuration were used to achieve metal-free solution, which is a key technology in the chirped pulse amplification for high power laser system. Here two polarizing filters were designed: polarization sensitive and polarization insensitive. Those polarization performances were characterized by the rigorous coupled-wave analysis (RCWA), and the design parameters of grating structures, pitch, depth, and filling factor were optimized by two-step hybrid optimization procedure because the diffraction characteristics of grating-based polarizing filters are highly sensitive to small changes in design parameters. The Taguchi method is incorporated into selection process in the genetic algorithm, which indicates that the Taguchi method optimizes the design parameters in a coarse manner, and then, coarsely optimized parameters are finely optimized using the genetic algorithm. Therefore the proposed method could solve global numerical optimization problems with continuous variables. The proposed two-step hybrid optimization algorithm could effectively optimize the grating structures for the purpose of polarization filter applications, and the optimized grating structures could selectively filter the incident light up to 99.8% as to TE or TM waves.

scholarly journals Tuning of PID Controller Parameters with Genetic Algorithm Method on DC Motor

2021 ◽  
Vol 1 (1) ◽  
pp. 41-53
Author(s):  
Eka Widya Suseno ◽  
Alfian Ma'arif
Keyword(s):  
Genetic Algorithm ◽  
Rise Time ◽  
Biological Evolution ◽  
Parameter Tuning ◽  
Dc Motor ◽  
Settling Time ◽  
Trial And Error ◽  
Genetic Algorithm Method ◽  
Trial And Error Method ◽  
Error Method

Proportional Integral Derivative (PID) controllers are used in general to control a system, for example a DC motor system. The difficulty of using the controller is parameter tuning, because the tuning parameters still use the trial and error method to find the PID parameter constants, namely Proportional Gain (KP), Integral Gain (KI) and Derivative Gain (KD). In this case, the genetic algorithm method is used which can give better results in each iteration. Genetic algorithms are one of the smart methods inspired by the process of natural selection, the process that causes biological evolution, this concept is applied to tuning PID parameters. This research uses the Matlab simulation method and applies the simulation results to the DC motor hardware using the Arduino Uno. The genetic algorithm method gives a system that has a better steady time and a smaller maximum spike than the Trial and Error method. The test process produced the two best data with an overshoot value = 2, settling time = 13.5 and rise time of 2.7872 and the PID parameter value for mutation of 1 was KP = 3.7500; KI = 1.3184 and KD = 0.2051. Then the value of the best PID parameter on Crossover is 0.4, which is KP = 4.2090; KI = 1.2012 and KD = 0.2539 with an overshoot value = 2, settling time = 18 and rise time = 2.6462.

ADAPTIVE ZONING DESIGN BY SUPERVISED LEARNING USING MULTI-OBJECTIVE OPTIMIZATION

2014 ◽  
Vol 13 (01) ◽  
pp. 1450004 ◽  
Author(s):  
F. M. MANGINI ◽  
G. PIRLO
Keyword(s):  
Genetic Algorithm ◽  
Learning Strategy ◽  
Optimization Procedure ◽  
Optimal Number ◽  
Optimization Techniques ◽  
Handwritten Digit Recognition ◽  
Nsga Ii ◽  
Multi Objective ◽  
Digit Recognition ◽  
Handwritten Digit

Zoning is a widespread feature extraction technique for handwritten digit recognition, since it is able to handle handwritten pattern variability. Static techniques for zoning design have recently been superseded by adaptive techniques, in which zoning design is considered as the result of an optimization procedure. This paper presents a new learning strategy to optimal zoning design using multi-objective genetic algorithm. More precisely, the nondominant sorting genetic algorithm II (NSGA II) has been applied to define, in a single process, both the optimal number of zones and the optimal zones for the Voronoi-based zoning method. The experimental tests, carried out in the field of handwritten digit recognition, show the effectiveness of this new approach with respect to traditional dynamic approaches for zoning design, based on single-objective optimization techniques.

CONTEXTUAL SUBTEXT INFORMATION OF A FOREIGN LANGUAGE TEXT: HERMENEUTIC APPROACH

2020 ◽  
Vol 2020 (30) ◽  
pp. 75-87
Author(s):  
Lidiya Derbenyova
Keyword(s):  
Foreign Language ◽  
Optimal Solution ◽  
Decision Making Process ◽  
Trial And Error ◽  
Transmission Of Information ◽  
Hermeneutic Approach ◽  
Trial And Error Method ◽  
Problems Of Translation ◽  
Error Method ◽  
Language Text

The article focuses on the problems of translation in the field of hermeneutics, understood as a methodology in the activity of an interpreter, the doctrine of the interpretation of texts, as a component of the transmission of information in a communicative aspect. The relevance of the study is caused by the special attention of modern linguistics to the under-researched issues of hermeneutics related to the problems of transmission of foreign language text semantics in translation. The process of translation in the aspect of hermeneutics is regarded as the optimum search and decision-making process, which corresponds to a specific set of functional criteria of translation, which can take many divergent forms. The translator carries out a number of specific translation activities: the choice of linguistic means and means of expression in the translation language, replacement and compensation of nonequivalent units. The search for the optimal solution itself is carried out using the “trial and error” method. The translator always acts as an interpreter. Within the boundaries of a individual utterance, it must be mentally reconstructed as conceptual situations, the mentally linguistic actions of the author, which are verbalized in this text.

scholarly journals A Password Meter without Password Exposure

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 345
Author(s):  
Pyung Kim ◽  
Younho Lee ◽  
Youn-Sik Hong ◽  
Taekyoung Kwon
Keyword(s):  
Performance Enhancement ◽  
Homomorphic Encryption ◽  
Optimization Techniques ◽  
Third Party ◽  
Fully Homomorphic Encryption ◽  
Performance Achievement ◽  
Server Side ◽  
On Line ◽  
Internal Mechanism ◽  
High Chance

To meet password selection criteria of a server, a user occasionally needs to provide multiple choices of password candidates to an on-line password meter, but such user-chosen candidates tend to be derived from the user’s previous passwords—the meter may have a high chance to acquire information about a user’s passwords employed for various purposes. A third party password metering service may worsen this threat. In this paper, we first explore a new on-line password meter concept that does not necessitate the exposure of user’s passwords for evaluating user-chosen password candidates in the server side. Our basic idea is straightforward; to adapt fully homomorphic encryption (FHE) schemes to build such a system but its performance achievement is greatly challenging. Optimization techniques are necessary for performance achievement in practice. We employ various performance enhancement techniques and implement the NIST (National Institute of Standards and Technology) metering method as seminal work in this field. Our experiment results demonstrate that the running time of the proposed meter is around 60 s in a conventional desktop server, expecting better performance in high-end hardware, with an FHE scheme in HElib library where parameters support at least 80-bit security. We believe the proposed method can be further explored and used for a password metering in case that password secrecy is very important—the user’s password candidates should not be exposed to the meter and also an internal mechanism of password metering should not be disclosed to users and any other third parties.

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