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This main contribution of this work is to propose a new approach based on a structure of MLPs (multi-layer perceptrons) for identifying current harmonics in low power distribution systems. In this approach, MLPs are proposed and trained with signal sets that are generated from real harmonic waveforms. After training, each trained MLP is able to identify the two coefficients of each harmonic term of the input signal. The effectiveness of the new approach is evaluated by two experiments and is also compared to another recent MLP method. Experimental results show that the proposed MLPs approach enables to identify effectively the amplitudes of harmonic terms from the signals under noisy condition. The new approach can be applied in harmonic compensation strategies with an active power filter to ensure power quality issues in electrical power systems.

The agronomic values of this population have been evaluated in the field experiments based on their phenotypic performance of agronomic traits, but the genetic variability of this population needs to be evaluated via techniques based on genetic material - DNA. In this study, the genetic variability in the investigated population of 71 hybrids and their parents was evaluated by RAPD technique, using eight selected arbitrarily primers; Genetic parameters and dendrogram expressing the genetic relationships among the investigated population were analyzed by GenALEx 6.1, Popgene 1.31 and NTSYSpc 2.1 softwares. Eight primers were used to generate the amplify products on each individual in the investigated population. From 74 genotypes, a total of 109 fragments were generated, among which, there were 89 polymorphic bands representing 81.65% with an average of 11 polymorphic bands/primer. Genetic similarity coefficient among the investigated population, based on DICE coefficient, ranged from 0.560 (LH05/0822 and PB260) to 0.991 (LH05/0781 and LH05/0841) with an average of 0,796, meaning that the genetic distance among ranged from 0.009 to 0.440 with an average of 0.231. The Shannon index and mean heterozygosity values were 0.328 and 0,176, respectively. This indicated that the progenies of the two investigated crosses possessed a relatively high range of genetic variability. The analysis of molecular variance (AMOVA) showed that genetic variation within population represented 62%, while genetic variation among two different crosses contributes 38% to the total genetic variability. Dendrogram based on DICE’s genetic similarity using UPGMA method showed that the hybrids divide into two major genetic groups (0.75), but the crosses were scattered independently of the hybrid.