Search results for "Swarm"

Training Artificial Neural Networks With Improved Particle Swarm Optimization

2020

Particle Swarm Optimization (PSO) is popular for solving complex optimization problems. However, it easily traps in local minima. Authors modify the traditional PSO algorithm by adding an extra step called PSO-Shock. The PSO-Shock algorithm initiates similar to the PSO algorithm. Once it traps in a local minimum, it is detected by counting stall generations. When stall generation accumulates to a prespecified value, particles are perturbed. This helps particles to find better solutions than the current local minimum they found. The behavior of PSO-Shock algorithm is studied using a known: Schwefel's function. With promising performance on the Schwefel's function, PSO-Shock algorithm is util…

Optimizing droop coefficients for minimum cost operation of islanded micro-grids

2017

This paper shows how minimum cost energy management can be carried out for islanded micro-grids considering an expanded state that also includes the system's frequency. Each of the configurations outputted by the energy management system at each hour are indeed technically sound and coherent from the point of view of generation-consumption balancing by exploiting a frequency dependent load flow algorithm. A Glow-worm Swarm Optimization (GSO) algorithm carried out in a 24 hour time frame provides optimized results. A test has been carried out for a residential PV-Storage-Microturbine islanded micro-grid to show the feasibility as well as the efficiency of the proposed approach and results ar…

Heuristic-Based Shiftable Loads Optimal Management in Smart Micro-Grids

2015

In this paper, an optimal power dispatch problem on a 24-h basis for distribution systems with distributed energy resources (DER) also including directly controlled shiftable loads is presented. In the literature, the optimal energy management problems in smart grids (SGs) where such types of loads exist are formulated using integer or mixed integer variables. In this paper, a new formulation of shiftable loads is employed. Such formulation allows reduction in the number of optimization variables and the adoption of real valued optimization methods such as the one proposed in this paper. The method applied is a novel nature-inspired multiobjective optimization algorithm based on an original…

Memetic Differential Evolution Frameworks in Filter Design for Defect Detection in Paper Production

2009

This chapter studies and analyzes Memetic Differential Evolution (MDE) Frameworks for designing digital filters, which aim at detecting paper defects produced during an industrial process. MDE Frameworks employ the Differential Evolution (DE) as an evolutionary framework and a list of local searchers adaptively coordinated by a control scheme. Here, three different variants of MDE are taken into account and their features and performance are compared. The binomial explorative features of the DE framework in contraposition to the exploitative features of the local searcher are analyzed in detail in light of the stagnation prevention problem, typical for the DE. Much emphasis in this chapter …

Optimal power flow based on glow worm-swarm optimization for three-phase islanded microgrids

2014

This paper presents an application of the Glowworm Swarm Optimization method (GSO) to solve the optimal power flow problem in three-phase islanded microgrids equipped with power electronics dc-ac inverter interfaced distributed generation units. In this system, the power injected by the distributed generation units and the droop control parameters are considered as variables to be adjusted by a superior level control. Two case studies with different optimized parameters have been carried out on a 6-bus test system. The obtained results showed the effectiveness of the proposed approach and overcomes the problem of OPF in islanded microgrids showing loads unbalance.

A computational proposal for a robust estimation of the Pareto tail index: An application to emerging markets

2022

Abstract In this work, we backtest and compare, under the VaR risk measure, the fitting performances of three classes of density distributions (Gaussian, Stable and Pareto) with respect to three different types of emerging markets: Egypt, Qatar and Mexico. We also propose a new technique for the estimation of the Pareto tail index by means of the Threshold Accepting (TAVaR) and the Hybrid Particle Swarm Optimization algorithm (H-PSOVaR). Furthermore, we test the accuracy and robustness of our estimates demonstrating the effectiveness of the proposed approach.

Nonlinear model based particle swarm optimization of PID shimmy damping control

2016

The present study aims to investigate the shimmy stability behavior of a single wheeled nose landing gear system. The system is supposed to be equipped with an electromechanical actuator capable to control the shimmy vibrations. A Proportional-Integrative-Derivative (PID) controller, tuned by using the Particle Swarm Optimization (PSO) procedure, is here proposed to actively damp the shimmy vibration. Time-history results for some test cases are reported and commented. Stochastic analysis is last presented to assess the robustness of the control system.

The role of swarming sites for maintaining gene flow in the brown long-eared bat (Plecotus auritus)

2004

Bat-swarming sites where thousands of individuals meet in late summer were recently proposed as 'hot spots' for gene flow among populations. If, due to female philopatry, nursery colonies are genetically differentiated, and if males and females of different colonies meet at swarming sites, then we would expect lower differentiation of maternally inherited genetic markers among swarming sites and higher genetic diversity within. To test these predictions, we compared genetic variance from three swarming sites to 14 nursery colonies. We analysed biparentally (five nuclear and one sex-linked microsatellite loci) and maternally (mitochondrial D-loop, 550 bp) inherited molecular markers. Three m…

Mesozoic mafic dyke swarm from Rio Ceará-Mirim (northeast Brazil)

1989

Escape planning in realistic fire scenarios with Ant Colony Optimisation

2014

Published version of an article from the journal:Applied Intelligence Also available on Springerlink: http://dx.doi.org/10.1007/s10489-014-0538-9 An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when predefined escape routes are blocked by a hazard, and there is a need to re-think which escape route is safest. This paper addresses automatically finding the safest escape routes in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony …