A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems

The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data. In order to enhance the significance of the small and specific region belonging to the positive class in the decision region, the SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Based on the over-sampled training data, the RBF classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier structure and the parameters of RBF kernels are determined using a particle swarm optimization algorithm based on the criterion of minimizing the leave-one-out misclassification rate. The experimental results on both simulated and real imbalanced data sets are presented to demonstrate the effectiveness of our proposed algorithm.

The system identification and control of Hammerstein system using non-uniform rational B-spline neural network and particle swarm optimization

In this paper a new system identification algorithm is introduced for Hammerstein systems based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a non-uniform rational B-spline (NURB) neural network. The proposed system identification algorithm for this NURB network based Hammerstein system consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a model based controller are utilized to demonstrate the efficacy of the proposed approach. The controller consists of computing the inverse of the nonlinear static function approximated by NURB network, followed by a linear pole assignment controller.

Particle swarm optimisation assisted classification using elastic net prefiltering

A novel two-stage construction algorithm for linear-in-the-parameters classifier is proposed, aiming at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage to construct a sparse linear-in-the-parameters classifier. For the first stage learning of generating the prefiltered signal, a two-level algorithm is introduced to maximise the model's generalisation capability, in which an elastic net model identification algorithm using singular value decomposition is employed at the lower level while the two regularisation parameters are selected by maximising the Bayesian evidence using a particle swarm optimization algorithm. Analysis is provided to demonstrate how “Occam's razor” is embodied in this approach. The second stage of sparse classifier construction is based on an orthogonal forward regression with the D-optimality algorithm. Extensive experimental results demonstrate that the proposed approach is effective and yields competitive results for noisy data sets.

Intraplate earthquake swarm in Belo Jardim, NE Brazil: reactivation of a major Neoproterozoic shear zone (Pernambuco Lineament)

Intraplate earthquakes in stable continental areas have been explained basically by reactivation of pre-existing zones of weakness, stress concentration, or both. Zones of weakness are usually identified as sites of the last major orogeny, provinces of recent alkaline intrusions, or stretched crust in ancient rifts. However, it is difficult to identify specific zones of weakness and intraplate fault zones are not always easily correlated with known geological features. Although Northeastern Brazil is one of the most seismically active areas in the country (magnitudes 5 roughly every 5 yr), with hypocentral depths shallower than similar to 10 km and seismic zones as long as 30-40 km, no clear relationship with the known surface geology can be usually established with confidence, and a clear identification of zones of weakness has not yet been possible. Here we present the first clear case of seismic activity occurring as reactivation of an old structure in Brazil: the Pernambuco Lineament, a major Neoproterozoic shear zone. The 2004 earthquake swarm of Belo Jardim (magnitudes up to 3.1) and the recurrent activities in the nearby towns of Sao Caetano and Caruaru (magnitudes up to 4.0 and 3.8), show that the Pernambuco Lineament is a weak zone. A local seismic network showed that the Belo Jardim swarm of 2004 November occurred by normal faulting on a North dipping, E-W oriented fault plane in close agreement with the E-W trending structures within the Pernambuco Lineament. The Belo Jardim activity was concentrated in a 1.5 km (E-W) by 2 km (downdip) fault area, and average depth of 4.5 km. The nearby Caruaru activity occurs as both strike-slip and normal faulting, also consistent with local structures of the Pernambuco Lineament. The focal mechanisms of Belo Jardim, Caruaru and S. Caetano, indicate E-W compressional and N-S extensional principal stresses. The NS extension of this stress field is larger than that predicted by numerical models such as those of Coblentz & Richardson and we propose that additional factors such as flexural stresses from the nearby Sergipe-Alagoas marginal basin could also affect the current stress field in the Pernambuco Lineament.

A late Neoproterozoic paleomagnetic pole for the Congo craton: Tectonic setting, paleomagnetism and geochronology of the Nola dike swarm (Central African Republic)

New structural, geochronological and paleomagnetic data were obtained on dolerite dikes of the Nola region (Central African Republic) at the northern border of the Congo craton. In this region metavolcanic, successions were thrust southward onto the craton during the Panafrican orogenic events. Our structural data reveal at least two structural klippes south of the present-day limits of the Panafrican nappe suggesting that it has once covered the whole Nola region, promoting the pervasive hydrothermal green-schist metamorphism observed in the underlying cratonic basement and also in the intrusive dolerite dikes. Paleomagnetic measurements revealed a stable dual-polarity low-inclination magnetization component in nine dikes (47 samples), carried by pyrrhotite and magnetite. This component corresponds to a paleopole at 304.8 degrees E and 61.8 degrees S (dp = 5.4, dm = 10.7) graded at 2 = 6. Both metamorphism and magnetic resetting were dated by the Ar-40/Ar-39 method on amphibole grains separated from the dikes at 571 +/- 6 Ma. The Nola pole is the first well-dated paleomagnetic pole for the Congo craton between 580 and 550 Ma. It marks a sudden change in direction of the Congo craton apparent polar wander path at the waning stages of the Panafrican orogenic events. (c) 2008 Elsevier B.V. All rights reserved.

Columnar joints in the Patino Formation sandstones, Eastern Paraguay: a dynamic interaction between dyke intrusion, quartz dissolution and cooling-induced fractures

The Patino Formation sandstones, which crop out in Aregua neighborhood in Eastern Paraguay and show columnar joints near the contact zone with a nephelinite dyke, have as their main characteristics the high proportion of syntaxial quartz overgrowth and a porosity originated from different processes, initially by dissolution and later by partial filling and fracturing. Features like the presence of floating grains in the syntaxial cement, the transitional interpenetrative contact between the silica-rich cement and grains as well as the intense fracture porosity are strong indications that the cement has been formed by dissolution and reprecipitation of quartz from the framework under the effect of thermal expansion followed by rapid contraction. The increase of the silica-rich cement towards the dyke in association with the orthogonal disposition of the columns relative to dyke walls are indicative that the igneous body may represent the main heat source for the interstitial aqueous solutions previously existing in the sediments. At macroscopic scale, the increasing of internal tensions in the sandstones is responsible for the nucleation of polygons, leading to the individualization of prisms, which are interconnected by a system of joints, formed firstly on isotherm surfaces of low temperature and later on successive adjacent planes towards the dyke heat source.

Precambrian geotectonic units of the Rio de La Plata craton

The main Precambrian tectonic units of Uruguay include the Piedra Alta tectonostratigraphic terrane (PATT) and Nico Perez tectonostratigraphic terrane (NPTT), separated by the Sarandi del Yi high-strain zone. Both terranes are well exposed in the Rio de La Plata craton (RPC). Although these tectonic units are geographically small, they record a wide span of geologic time. Therefore improved geological knowledge of this area provides a fuller understanding of the evolution of the core of South America. The PATT is constituted by low-to medium-grade metamorphic belts (ca. 2.1 Ga); its petrotectonic associations such as metavolcanic units, conglomerates, banded iron formations, and turbiditic deposits suggest a back-arc or a trench-basin setting. Also in the PATT, a late to post-orogenic, arc-related layered mafic complex (2.3-1.9 Ga), followed by A-type granites (2.08 Ga), and finally a taphrogenic mafic dike swarm (1.78 Ga) occur. The less thoroughly studied NPTT consists of Palaeoproterozoic high-grade metamorphic sequences (ca. 2.2 Ga), mylonites and postorogenic and rapakivi granites (1.75 Ga). The Brasiliano-Pan African orogeny affected this terrane. Neoproterozoic cover occurs in both tectonostratigraphic terranes, but is more developed in the NPTT. Over the past 15 years, new isotopic studies have improved our recognition of different tectonic events and associated processes, such as reactivation of shear zones and fluids circulation. Transamazonian and Statherian tectonic events were recognized in the RPC. Based on magmatism, deformation, basin development and metamorphism, we propose a scheme for the Precambrian tectonic evolution of Uruguay, which is summarized in the first Palaeoproterozoic tectonic map of the Rio de La Plata craton.

Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Foraging Behavior of the Swarm-Founding Wasp, Polybia (Trichothorax) sericea (Hymenoptera, Vespidae): Prey Capture and Load Capacity

The main component of the protein diet of P. sericea was larvae of Lepidoptera (75.38%), with predominance of the following Families: Noctuidae (30.99%), Hesperiidae (19.01%); Pyralidae (19.01%) and Nymphalidae (11.98%). The average weight of the prey captured was 14.2 mg, a value equivalent to 24.7% of the average wasp weight. The average glucidic food load was 28.61 mg, corresponding to approximately half the wasp weight (49.64%). The weight of the load transported in the crop varied according to the food density, which, in turn, influenced the time spent in its collection (Pearson: n=64; r=0.64;p<0.05). Polybia sericea showed predatory interactions against Lepidopteran caterpillars, who are known to be agricultural pests. P. sericea has potential to be used in Integrated Pest Management.

Foraging Behavior of the Swarm-founding Wasp Polybia (Trichothorax) sericea (Hymenoptera, Vespidae): Daily Resource Collection Activity and Flight Capacity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)