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## AN INFORMATIVE DIFFERENTIAL EVOLUTION AL- GORITHM WITH SELF ADAPTIVE RE-CLUSTERING TECHNIQUE FOR THE OPTIMIZATION OF PHASED ANTENNA ARRAY

### Citations

3886 |
Adaptation in Natural and Artificial Systems. The
- Holland
- 1975
(Show Context)
Citation Context ...ice. In past decades, many electromagnetic optimization problems have been solved by using EAs such as by using Invasive Weed Optimization [4–6], Particle Swarm Optimization [1, 7]. Genetic Algorithm =-=[1, 8, 9]-=-. Mouhamadou et al. used a new method called Sequential Quadratic Programming (SQP) algorithm to suppress multiple narrow and wide band interferences and track the desire signal by controlling only th... |

3769 | Particle Swarm Optimization
- Kennedy, Eberhart
- 1942
(Show Context)
Citation Context ...n proposed by Storn and Price. In past decades, many electromagnetic optimization problems have been solved by using EAs such as by using Invasive Weed Optimization [4–6], Particle Swarm Optimization =-=[1, 7]-=-. Genetic Algorithm [1, 8, 9]. Mouhamadou et al. used a new method called Sequential Quadratic Programming (SQP) algorithm to suppress multiple narrow and wide band interferences and track the desire ... |

3053 | Some methods for classification and analysis of multivariate observations. In:
- MacQueen
- 1967
(Show Context)
Citation Context ...en the algorithm re-clusters the whole population, the subpopulations those were very close to each other will belong to a same subpopulation now. This is because of the property of k-means Algorithm =-=[15]-=- that generates clusters based on the spatial distribution of the data in the n dimensional space. In this paper we have used DE/best/1strategy to each subpopulation separately because this variation ... |

1012 |
Individual comparisons by ranking method,”
- Wilcoxon
- 1945
(Show Context)
Citation Context ... we see that our algorithm out performs the rest two algorithms. To determine whether the result of proposed algorithm is different from the result of the other algorithms, the Wilcoxon rank sum test =-=[18, 19]-=- is conducted and whenever the result of our algorithm is statistically significant we put a ‘#’ besides our result and ‘!’ mark is given when algorithm is not statistically significant and when it is... |

817 |
Differential evolution a simple and efficient heuristic for global optimisation over continuous spaces.
- Storn, Price
- 1997
(Show Context)
Citation Context ...researchers have developed a lot of techniques along with some evolutionary algorithms. There are some powerful algorithms that have been proposed by researches in the last few decades. Among them DE =-=[2, 3]-=- is one of the most powerful algorithms that has been proposed by Storn and Price. In past decades, many electromagnetic optimization problems have been solved by using EAs such as by using Invasive W... |

165 |
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions,”
- Liang, Qin, et al.
- 2006
(Show Context)
Citation Context ...e will be 10 which can be afforded easily compared to the case if the ratio is taken as 100 or more. The generated cost functions are also optimized with other powerful algorithms SADE [17] and CLPSO =-=[16]-=-. For the comparison of proposed algorithm with other algorithms we took the same cost functions with same goal (suppression of side-lobes for same amount etc.) and the number of function evaluations ... |

109 |
Differential evolution: A survey of the stateof-the-art,”
- Das, Suganthan
- 2011
(Show Context)
Citation Context ...researchers have developed a lot of techniques along with some evolutionary algorithms. There are some powerful algorithms that have been proposed by researches in the last few decades. Among them DE =-=[2, 3]-=- is one of the most powerful algorithms that has been proposed by Storn and Price. In past decades, many electromagnetic optimization problems have been solved by using EAs such as by using Invasive W... |

82 |
Particle swarm optimization versus genetic algorithms for phased array synthesis,”
- Boeringer, Werner
- 2004
(Show Context)
Citation Context ...n proposed by Storn and Price. In past decades, many electromagnetic optimization problems have been solved by using EAs such as by using Invasive Weed Optimization [4–6], Particle Swarm Optimization =-=[1, 7]-=-. Genetic Algorithm [1, 8, 9]. Mouhamadou et al. used a new method called Sequential Quadratic Programming (SQP) algorithm to suppress multiple narrow and wide band interferences and track the desire ... |

71 |
Suganthan “Self-adaptive Differential Evolution Algorithm for Constrained Real-Parameter Optimization”, In:
- Huang, Qin, et al.
(Show Context)
Citation Context ...,i,t , if (randi,j[0, 1) < Cr or j = jrand uj,i,t = Xj,i,t , otherwise where randi,j[0, 1) is a uniformly distributed random number. For have an elaborate discussion on DE the readers are directed to =-=[17]-=- and the references therein. 2.3. Selection Operation The selection procedure is done by the following way: { ( ) ( ) Ui,t if f Ui,t ≤ f Xi,t Xi,t+1 = otherwise Xi,t for minimization problems. Th... |

60 |
A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,”
- Derrac, Garcıa, et al.
- 2011
(Show Context)
Citation Context ... we see that our algorithm out performs the rest two algorithms. To determine whether the result of proposed algorithm is different from the result of the other algorithms, the Wilcoxon rank sum test =-=[18, 19]-=- is conducted and whenever the result of our algorithm is statistically significant we put a ‘#’ besides our result and ‘!’ mark is given when algorithm is not statistically significant and when it is... |

55 |
A novel numerical optimization algorithm inspired from weed colonization.”
- Mehrabian, Lucas
- 2006
(Show Context)
Citation Context ...culated using (2) becomes less than R limit then the algorithm calls for the local search technique. The R limit is defined as: √ ( R limit = Xupper − ) T ( Xlower · Xupper − ) Xlower × 10 −2 , =-=(4)-=- where Xupper is the upper bound of the search space and Xlower is the lower bound of the search space and (·) T denotes the transpose of the matrix (·). The local search technique introduces some... |

21 |
Synthesis of thinned linear antenna arrays with fixed sidelobe level using realProgress
- Mahanti, Pathak, et al.
(Show Context)
Citation Context ...n presented in [12]. Mahanti et al. presented a new technique for designing thinned linear antenna arrays with fixed side-lobe level and fixed percentage of thinning using realcoded genetic algorithm =-=[13]-=- in the year 2007. In the same year, Guney and Onay used Bees algorithm for interference suppression of linear antenna array, controlling the amplitude in the paper [14]. Again in the year of 2008, Gu... |

20 | Amplitude-only pattern nulling of linear antenna arrays with the use of bees algorithm
- Guney, Onay
(Show Context)
Citation Context ...ng realcoded genetic algorithm [13] in the year 2007. In the same year, Guney and Onay used Bees algorithm for interference suppression of linear antenna array, controlling the amplitude in the paper =-=[14]-=-. Again in the year of 2008, Guney and Basbug used Bacterial Foraging algorithm for interference suppression of linear antenna array, only controlling the amplitude of the element excitation [11]. Opt... |

17 | Interference Suppression of Linear Antenna Arrays by Amplitude Only Control Using Bacteria Foraging algorithm,”
- Guney, Basbug
- 2008
(Show Context)
Citation Context ...aper [14]. Again in the year of 2008, Guney and Basbug used Bacterial Foraging algorithm for interference suppression of linear antenna array, only controlling the amplitude of the element excitation =-=[11]-=-. Optimization problems in electromagnetic domain generally involve with large number of designing parameters and the parameters may also include constrains in the search range. So for these reasons, ... |

12 | Design of an E-shaped MIMO antenna using IWO algorithm for wireless application at 5.8 GHz.
- Mallahzadeh, haghi, et al.
- 2009
(Show Context)
Citation Context ...e particles. We used the following relations to find exploiters number and r exploit. ⎛ ⎞ (exploiters ( max −exploiters min) exploitersi = round ⎝ ) ) 2 ⎠ , · 1 − +exploiters min ( fi−best worst−best =-=(5)-=- where exploitersi denotes the number of exploiters generated around the particle i and fi denotes the fitness value of the i-th particle, the best and worst denotes the best fit and worst fit particl... |

9 |
Interference suppression of the linear antenna arrays controlled by phase with use of SQP algorithm
- Mouhamadou, Armand, et al.
(Show Context)
Citation Context ... method called Sequential Quadratic Programming (SQP) algorithm to suppress multiple narrow and wide band interferences and track the desire signal by controlling only the phase has been presented in =-=[12]-=-. Mahanti et al. presented a new technique for designing thinned linear antenna arrays with fixed side-lobe level and fixed percentage of thinning using realcoded genetic algorithm [13] in the year 20... |

8 |
Compact U-array MIMO antenna designs using IWO algorithm,”
- Mallahzadeh, Es’haghi, et al.
- 2009
(Show Context)
Citation Context ...cle, the best and worst denotes the best fit and worst fit particle among the chosen 40% particles respectively. r exploiti = best where k = worst . performance. ( 1 − k d) · ( ) (fi − best) + r ini, =-=(6)-=- worst − best The parameter d is chosen either 1 or 2 for best 4. ARRAY FACTOR AND ARRAY OPTIMIZATION The far field radiation pattern that has to be minimised is given by F F (θ) = AF (θ) · EP (θ), [1... |

6 |
Genetical swarm optimization: Self-adaptive hybrid evolutionary algorithm for electromagnetics
- Grimaccia, Mussetta, et al.
- 2007
(Show Context)
Citation Context ...umber of elements. Realistic phased array using aperture elements such as slots or patches370 Maity et al. typically have directive elements that give rise to a element pattern often approximated by =-=[10]-=-. EP (θ) = √ cos n θ (8) where n = 0 would represent ideal isotropic array elements and n > 0 represents directive array elements. In this paper, n is taken to be 1.2 according to [1] and the element ... |

5 | Dynamic thinning of antenna array using genetic algorithm
- Jain, Mani
- 2011
(Show Context)
Citation Context ...ice. In past decades, many electromagnetic optimization problems have been solved by using EAs such as by using Invasive Weed Optimization [4–6], Particle Swarm Optimization [1, 7]. Genetic Algorithm =-=[1, 8, 9]-=-. Mouhamadou et al. used a new method called Sequential Quadratic Programming (SQP) algorithm to suppress multiple narrow and wide band interferences and track the desire signal by controlling only th... |