This paper presents a new optimization study of the placement and size photovoltaic source (PVS) in distribution grid, based on annual records meteorological parameters (irradiance, temperature). Based recorded data, production output as well daily average power (24-h vector) PVS is extracted over year. When vector available, it can be used an input when searching for optimal PVS. allows to tak...

In an earlier paper Rakonczai et al. (2014), we have emphasized the effective sample size for autocorrelated data. The simulations were based on the block bootstrap methodology. However, the discreteness of the usual block size did not allow for exact calculations. In this paper we propose a generalisation of the block bootstrap methodology, relate it to the existing optimisation procedures and...

we developed biofunctionalized nanoparticles with magnetic properties by immobalizing diethyle-neglycol (deg) on gd2o3, and pegilation of small particulate gadolinium oxide (spgo) with two me-thoxy-polyethyleneglycol-silane (mpeg-silane 550 and 2000 da) using a new supervised polyol route, described recently. in conjunction to the previous study to achieve a high quality synthesis and increase ...

a mixture  of  sodium  lauryl  sulfate  (sls)  as  ionic  emulsifer  and  stearyl alcohol as non-ionic emulsifer was employed in a vinyl chloride emulsion polymerization  reaction  to  study  the  infuence  of  various  interactive parameters involved in the reaction system. it was found that the particle size was dependent on the amount and type of emulsifer. the average particle size of polyv...

We study the impact of backbones in optimization and approximation problems. We show that some optimization problems like graph coloring resemble decision problems, with problem hardness positively correlated with backbone size. For other optimization problems like blocks world planning and traveling salesperson problems, problem hardness is weakly and negatively correlated with backbone size, ...

This paper systematically proposed a multi-population agent co-genetic algorithm with double chainlike agent structure (MPATCGA) to solve the problem of the low optimization precision and long optimization time of simple genetic algorithm in terms of two coding strategy. This algorithm adopted multi-population parallel searching mode, close chain-like agent structure, cycle chain-like agent str...

The influence of non-constant population sizes in evolutionary multi-objective optimization algorithms is investigated. In contrast to evolutionary single-objective optimization algorithms an increasing population size is considered beneficial when approaching the Pareto-front. Firstly, different deterministic schedules are tested, featuring different parameters like the initial population size...