896 resultados para swarm-founding wasps
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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.
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Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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In Brazilian Amazonia, 20 genera and more than 200 species of polistine wasps are recorded. Local faunas with 70 to 80 species are usually found in non floodable forest environments. However, a variety of wetlands exist in the region, the most expressive in surface area being varzea systems. In this paper, information is presented on polistines from two areas of wetlands in the Brazilian states of Amazonas and Amapá. These are reciprocally compared and also with nearby terra firme locations. Collecting methods consisted of active search for nests, handnetting and automatic trapping of individuals. Forty-six species of 15 genera were collected in Mamirauá, AM, most being widespread common wasps. However, five species deserve special mention in virtue of rarity and/or restricted distribution: Metapolybia rufata, Chartergellus nigerrimus, Chartergellus punctatior, Clypearia duckei, and Clypearia weyrauchi. In Região dos Lagos, AP, 31 species of 9 genera were collected, nearly all being common species with the exception of some Polistes, like P. goeldi and P. occipitalis. Even though less rich than vespid faunas from terra firme habitats, the Mamirauá fauna proved to be quite expressive considering limitations imposed by the hydrological regime. In Região dos Lagos, however, the very low diversity found was below the worst expectations. The virtual absence of otherwise common species in environments like tidal varzea forests along Araguari River is truly remarkable. The causes of low diversity are probably related to isolation and relative immaturity of the region, allied to strong degradation of forested habitats.
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The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.
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An inventory of social wasps in Cerrado biome of the southern of the state of Minas Gerais was performed. A comparison between field and Riparian Forest areas was made in relation to species richness; correlations between diversity, sample methods and environmental factors were conducted. A total of 32 species was registered and Polybia fastidiosuscula de Saussure, 1854 was the most abundant species. The higher richness was in the Cerrado Field, as well as the highest diversity index. The temperature and rainfall had significant correlation with species richness and a significant variation in richness between dry and wet seasons was observed. Polybia fastidiosuscula was more abundant in the Riparian Forest during the dry season and in the Cerrado Field during wet season. The study area showed a great diversity of social wasps, with record both widely distributed species such as rare species, which indicates the quality and potential area for future studies.
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no.14
Sociogenomics of Cooperation and Conflict during Colony Founding in the Fire Ant Solenopsis invicta.
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One of the fundamental questions in biology is how cooperative and altruistic behaviors evolved. The majority of studies seeking to identify the genes regulating these behaviors have been performed in systems where behavioral and physiological differences are relatively fixed, such as in the honey bee. During colony founding in the monogyne (one queen per colony) social form of the fire ant Solenopsis invicta, newly-mated queens may start new colonies either individually (haplometrosis) or in groups (pleometrosis). However, only one queen (the "winner") in pleometrotic associations survives and takes the lead of the young colony while the others (the "losers") are executed. Thus, colony founding in fire ants provides an excellent system in which to examine the genes underpinning cooperative behavior and how the social environment shapes the expression of these genes. We developed a new whole genome microarray platform for S. invicta to characterize the gene expression patterns associated with colony founding behavior. First, we compared haplometrotic queens, pleometrotic winners and pleometrotic losers. Second, we manipulated pleometrotic couples in order to switch or maintain the social ranks of the two cofoundresses. Haplometrotic and pleometrotic queens differed in the expression of genes involved in stress response, aging, immunity, reproduction and lipid biosynthesis. Smaller sets of genes were differentially expressed between winners and losers. In the second experiment, switching social rank had a much greater impact on gene expression patterns than the initial/final rank. Expression differences for several candidate genes involved in key biological processes were confirmed using qRT-PCR. Our findings indicate that, in S. invicta, social environment plays a major role in the determination of the patterns of gene expression, while the queen's physiological state is secondary. These results highlight the powerful influence of social environment on regulation of the genomic state, physiology and ultimately, social behavior of animals.
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Ant queens that attempt to disperse and found new colonies independently face high mortality risks. The exposure of queens to soil entomopathogens during claustral colony founding may be particularly harmful, as founding queens lack the protection conferred by mature colonies. Here, we tested the hypotheses that founding queens (I) detect and avoid nest sites that are contaminated by fungal pathogens, and (II) tend to associate with other queens to benefit from social immunity when nest sites are contaminated. Surprisingly, in nest choice assays, young Formica selysi BONDROIT, 1918 queens had an initial preference for nest sites contaminated by two common soil entomopathogenic fungi, Beauveria bassiana and Metarhizium brunneum. Founding queens showed a similar preference for the related but non-entomopathogenic fungus Fusarium graminearum. In contrast, founding queens had no significant preference for the more distantly related nonentomopathogenic fungus Petromyces alliaceus, nor for heat-killed spores of B. bassiana. Finally, founding queens did not increase the rate of queen association in presence of B. bassiana. The surprising preference of founding queens for nest sites contaminated by live entomopathogenic fungi suggests that parasites manipulate their hosts or that the presence of specific fungi is a cue associated with suitable nesting sites.
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The change over time in the fecundity and weight of queens was investigated in three monogynous, independent colony founding species,Lasius niger, Camponotus ligniperda andC. herculaneus, and two polygynous dependent colony founding species,Plagiolepis pygmaea andIridomyrmex humilis. Queens of the three species founding independently exhibited a similar pattern with a significant loss of weight between mating and the emergence of the first workers. In contrast, weights of queens of the species employing dependent colony founding remained more stable. Fecundity of queens founding independently increased slowly with time whereas fecundity of queens founding dependently reached the maximum level some weeks after the beginning of the first reproductive season. These results are discussed in relation to some differences in the life history (e.g., life-span) between queens utilizing independent and dependent colony founding.
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Aquesta memòria presenta les línies generals que s'han seguit per tal d'implementar una aplicació anomenada SWARM. En aquest document es recullen les bases del nostre projecte utilitzant el llenguatge de programació C# i fent servir altres eines i frameworks per les diferents capes de què consta el projecte, com poden ser Silverlight o WCF.