In gamma-ray spectrometry, computational detector model allows determining absolute detector efficiency for non-standard sources with varying chemical compositions in the absence of volumetric calibration standards. T...
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In gamma-ray spectrometry, computational detector model allows determining absolute detector efficiency for non-standard sources with varying chemical compositions in the absence of volumetric calibration standards. This study focuses on developing a computational model of a LaBr3(Ce) 1.5" x 1.5 '' scintillation detector based on characterization data. The detector was characterized using 137Cs and 152Eu point calibration sources placed at various positions relative to the detector cap. Modeling was performed using the MCNP6 code based on the Monte Carlo method. The initial modeling results revealed deviations between the calculated and experimental detector responses, which required model optimization. Optimization of the detector parameters was carried out using differential evolution algorithms. To verify the optimized LaBr3 model, studies were conducted with a volumetric KCl source. The deviations between the calculated and experimental results fell within the error limits.
This paper presents the results of the comparative study of differential evolution algorithms used as an alternative for tuning the gains of a PD+ type visual control structure, since tuning PD or PID type control str...
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This paper presents the results of the comparative study of differential evolution algorithms used as an alternative for tuning the gains of a PD+ type visual control structure, since tuning PD or PID type control structures is not trivial. We made the quantitative comparison using the performance index (L-2-norm) and we applied the algorithm of best performance in a case of study (detection and cutting of leaves using a Cartesian robot). We also present the stability analysis according to Lyapunov theory and experimental results.
In this study, an ensemble of differentialevolution (DE) algorithms is presented to classify electromagnetic targets in resonance scattering region. The algorithm aims to synthesize a special incident signal for each...
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In this study, an ensemble of differentialevolution (DE) algorithms is presented to classify electromagnetic targets in resonance scattering region. The algorithm aims to synthesize a special incident signal for each target, which is defined as the main discrimination feature in the given target recognition method. In the proposed algorithm, the amplitudes of basis functions and the duration of this incident signal are optimised to give minimum late-time scattered signal's energy, which is the main fitness function of the algorithm. The proposed DE algorithm is applied to a target set consisting of lossless dielectric spheres and correct recognition rates for both noiseless and noisy signals are obtained. The results for both developed DE algorithm and other DE variants of traditional DE, adaptive differentialevolution with optional external archive (JADE), jDE are also given to compare the algorithms and show the effectiveness of the proposed one.
In this paper, we present a strategy to stabilize the attitude of a planar vertical take off and landing (PVTOL) vehicle with variable pitch propeller (VPP) rotors. In the VPP configuration, the thrust is obtained wit...
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In this paper, we present a strategy to stabilize the attitude of a planar vertical take off and landing (PVTOL) vehicle with variable pitch propeller (VPP) rotors. In the VPP configuration, the thrust is obtained with the propeller pitch angle, instead of changing the rotor speed, and this concept adds maneuverability to the vehicle. The PVTOL used in this paper is highly unstable in its natural hovering flight state, therefore the main goal is to achieve a stable attitude. First of all, a simplified dynamic model that includes the VPP dynamics is obtained. Then, a methodology to select the parameters of a nonlinear controller using differential evolution algorithms (DEA) will be presented. The controller's parameters are selected with two purposes: to guarantee the asymptotic stability of the closed-loop system while taking into account the uncertainty, and to improve its robustness margin. And finally, The results are validated with real-time experiments.
This paper presents an ensemble of differential evolution algorithms employing the variable parameter search and two distinct mutation strategies in the ensemble to solve real-parameter constrained optimization proble...
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ISBN:
(纸本)9781424481262
This paper presents an ensemble of differential evolution algorithms employing the variable parameter search and two distinct mutation strategies in the ensemble to solve real-parameter constrained optimization problems. It is well known that the performance of DE is sensitive to the choice of mutation strategies and associated control parameters. For these reasons, the ensemble is achieved in such a way that each individual is assigned to one of the two distinct mutation strategies or a variable parameter search (VPS). The algorithm was tested using benchmark instances in Congress on evolutionary Computation 2010. For these benchmark problems, the problem definition file, codes and evaluation criteria are available in http://***/home/EPNSugan. Since the optimal or best known solutions are not available in the literature, the detailed computational results required in line with the special session format are provided for the competition.
In this article a web tool which contributes to the visual analysis of the differentialevolution (DE) algorithms is presented. The tool provides a graphic interface with 8 views that allows understanding the underlyi...
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ISBN:
(纸本)9783319986784;9783319986777
In this article a web tool which contributes to the visual analysis of the differentialevolution (DE) algorithms is presented. The tool provides a graphic interface with 8 views that allows understanding the underlying process of the algorithm. The tool has a library which extracts data from DE algorithms and its main feature is that the functions of the library can be embedded in the code of any DE algorithm to be analyzed. To validate the tool, three DE algorithms: DE/Rand/1/bin, DE/best/1/bin, and JADE and three test functions: Sphere, Rosenbrock, and Rastrigin have been used, which produced a total of 234 different tests, all of them performed successfully. The tool can allow to experts to analyze algorithms, particularly DE algorithms, and it can contribute to improve such algorithms or in generating new strategies that can emerge from the analysis of the extracted information.
Nowadays, the population growth and economic development causes the need for electricity power to increase every year. An unit dispatch problem is defined as the attribution of operational values to each generation un...
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ISBN:
(纸本)9781479904549;9781479904532
Nowadays, the population growth and economic development causes the need for electricity power to increase every year. An unit dispatch problem is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be obeyed like the total power to be generated, operational bounds of these units etc. In this context, an optimal dispatch programming for hydroelectric units in energy plants provides a bigger production of electricity to be generated with a minimal water amount. This paper presents an optimization solution for hydroelectric generating system of a plant, using differential evolution algorithms. The novel mathematical model proposed and validation of the obtained algorithms will be performed with practical simulation experiments. Throughout the text, the equations and models for the system simulation will be fully described, and the experiments and results will be objectively analysed through statistical inference. Simulation results indicate savings of 6.5 million litres of water for each month of operation using the proposed solution.
In this paper, two novel morphing parametric models for flat-to-V-type (FV) and for spoke-to-V-type (SV) Permanent Magnet (PM) synchronous machine configurations are introduced. A combined multi-objective design optim...
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ISBN:
(纸本)9781479903375
In this paper, two novel morphing parametric models for flat-to-V-type (FV) and for spoke-to-V-type (SV) Permanent Magnet (PM) synchronous machine configurations are introduced. A combined multi-objective design optimization method employing Design of Experiments (DOE) and differentialevolution (DE) algorithms was developed and implemented. A Central Composite Design (CCD) approach combined with the Response Surface Method (RSM) was used to perform a sensitivity study from which the significant independent design variables were selected for the DE design optimization procedure. A computationally efficient-Finite Element Analysis (CE-FEA) technique was employed to evaluate the electromagnetic performance of the candidate designs. Three optimization objectives are concurrently considered for minimum material cost, power losses and torque ripple, respectively. The DE optimization results enable the systematic comparison of three interior permanent magnet (IPM) motor topologies: flat-type, generic V-shape and spoke, respectively. A discussion on the relative merits of each topology is included.
An effective coordination in an interconnected system can be obtained by ensuring proper settings of overcurrent relays. In this research work, the problem of coordinating the overcurrent relays is formulated as a non...
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An effective coordination in an interconnected system can be obtained by ensuring proper settings of overcurrent relays. In this research work, the problem of coordinating the overcurrent relays is formulated as a non-linear problem, taking into account the as discrete nature of time dial settings and the pickup current settings. An effective approach based on adaptive differentialevolution (ADE) algorithm is proposed to solve the coordination problem. The results obtained by ADE are compared with different algorithms on different model test systems and found to be feasible, robust and efficient.
This paper presents a novel stochastic optimisation approach to determining the feasible optimal solution of the economic dispatch (ED) problem considering various generator constraints. Many practical constraints of ...
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This paper presents a novel stochastic optimisation approach to determining the feasible optimal solution of the economic dispatch (ED) problem considering various generator constraints. Many practical constraints of generators, such as ramp rate limits, prohibited operating zones and the valve point effect, are considered. These constraints make the ED problem a non-smooth/non-convex minimisation problem with constraints. The proposed optimisation algorithm is called self-tuning hybrid differentialevolution (self-tuning HDE). The self-tuning HDE utilises the concept of the 115 success rule of evolution strategies (ESs) in the original HDE to accelerate the search for the global optimum. Three test power systems, including 3-, 13- and 40-unit power systems, are applied to compare the performance of the proposed algorithm with genetic algorithms, the differentialevolution algorithm and the HDE algorithm. Numerical results indicate that the entire performance of the proposed self-tuning HDE algorithm outperforms the other three algorithms.
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