967 resultados para Ant colony optimisation algorithm


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The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

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The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

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This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for models that are linear in parameters to nonlinear multi-layer perceptrons (MLPs). We used an EM algorithm combined with variational approximation, the evidence procedure, and an optimisation algorithm. The technique was tested on two regression applications. The first one is a synthetic dataset and the second is gas forward contract prices data from the UK energy market. The results showed that forecasting accuracy is significantly improved by using Student-t noise models.

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In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided. © 2011 IEEE.

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In this article we present an approach to object tracking handover in a network of smart cameras, based on self-interested autonomous agents, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to learn the vision graph, that is, the camera neighbourhood relations, during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online, enabling efficient deployment in unknown scenarios and camera network topologies, and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multicamera calibration can be avoided. We have evaluated our approach both in a simulation study and in network of real distributed smart cameras.

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In this paper we present increased adaptivity and robustness in distributed object tracking by multi-camera networks using a socio-economic mechanism for learning the vision graph. To build-up the vision graph autonomously within a distributed smart-camera network, we use an ant-colony inspired mechanism, which exchanges responsibility for tracking objects using Vickrey auctions. Employing the learnt vision graph allows the system to optimise its communication continuously. Since distributed smart camera networks are prone to uncertainties in individual cameras, such as failures or changes in extrinsic parameters, the vision graph should be sufficiently robust and adaptable during runtime to enable seamless tracking and optimised communication. To better reflect real smart-camera platforms and networks, we consider that communication and handover are not instantaneous, and that cameras may be added, removed or their properties changed during runtime. Using our dynamic socio-economic approach, the network is able to continue tracking objects well, despite all these uncertainties, and in some cases even with improved performance. This demonstrates the adaptivity and robustness of our approach.

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The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

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Several ant species vary in the number of queens per colony, yet the causes and consequences of this variation remain poorly understood. In previous experiments, we found that Formica selysi workers originating from multiple-queen (=polygyne) colonies had a lower resistance to a fungal pathogen than workers originating from single-queen (=monogyne) colonies. In contrast, group diversity improved disease resistance in experimental colonies. This discrepancy between field and experimental colonies suggested that variation in social structure in the field had antagonistic effects on worker resistance, possibly through a down-regulation of the immune system balancing the positive effect of genetic diversity. Here, we examined if workers originating from field colonies with alternative social structure differed in three major components of their immune system. We found that workers from polygyne colonies had a lower bacterial growth inhibitory activity than workers from monogyne colonies. In contrast, workers from the two types of colonies did not differ significantly in bacterial cell wall lytic activity and prophenoloxidase activity. Overall, the presence of multiple queens in a colony correlated with a slight reduction in one inducible component of the immune system of individual workers. This reduced level of immune defence might explain the lower resistance of workers originating from polygyne colonies despite the positive effect of genetic diversity. More generally, these results indicate that social changes at the group level can modulate individual immune defences.

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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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Understanding the interplay between cooperation and conflict in social groups is a major goal of biology. One important factor is genetic relatedness, and animal societies are usually composed of related but genetically different individuals, setting the stage for conflicts over reproductive allocation. Recently, however, it has been found that several ant species reproduce predominantly asexually. Although this can potentially give rise to clonal societies, in the few well-studied cases, colonies are often chimeric assemblies of different genotypes, due to worker drifting or colony fusion. In the ant Cerapachys biroi, queens are absent and all individuals reproduce via thelytokous parthenogenesis, making this species an ideal study system of asexual reproduction and its consequences for social dynamics. Here, we show that colonies in our study population on Okinawa, Japan, recognize and effectively discriminate against foreign workers, especially those from unrelated asexual lineages. In accord with this finding, colonies never contained more than a single asexual lineage and average pairwise genetic relatedness within colonies was extremely high (r = 0.99). This implies that the scope for social conflict in C. biroi is limited, with unusually high potential for cooperation and altruism.

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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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The breeding system of social organisms affects many important aspects of social life. Some species vary greatly in the number of breeders per group, but the mechanisms and selective pressures contributing to the maintenance of this polymorphism in social structure remain poorly understood. Here, we take advantage of a genetic dataset that spans 15 years to investigate the dynamics of colony queen number within a socially polymorphic ant species. Our study population of Formica selysi has single- and multiple-queen colonies. We found that the social structure of this species is somewhat flexible: on average, each year 3.2% of the single-queen colonies became polygynous, and conversely 1.4% of the multiple-queen colonies became monogynous. The annualized queen replacement rates were 10.3% and 11.9% for single- and multiple-queen colonies, respectively. New queens were often but not always related to previous colony members. At the population level, the social polymorphism appeared stable. There was no genetic differentiation between single- and multiple-queen colonies at eight microsatellite loci, suggesting ongoing gene flow between social forms. Overall, the regular and bidirectional changes in queen number indicate that social structure is a labile trait in F. selysi, with neither form being favored within a time-frame of 15 years.

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Emigration of a colony of the leaf-cutting ant Acromyrmex heyeri Forel (Hymenoptera, Formicidae). Colony migration is a poorly studied phenomenon in leaf-cutting ants. Here we report on the emigration of a colony of the leaf-cutting ant A. heyeri in Brazil. The colony emigrated to a new location 47.4 m away from the original nest site, possibly because it had undergone considerable stress due to competitive interactions with a colony of Acromyrmex crassispinus.