Search results for " Genetic Algorithm"
showing 10 items of 45 documents
An Innovative Structural Dynamic Identification Procedure Combining Time Domain OMA Technique and GA
2022
In this paper an innovative and simple Operational Modal Analysis (OMA) method for structural dynamic identification is proposed. It combines the recently introduced Time Domain–Analytical Signal Method (TD–ASM) with the Genetic Algorithm (GA). Specifically, TD–ASM is firstly employed to estimate a subspace of candidate modal parameters, and then the GA is used to identify the structural parameters minimizing the fitness value returned by an appropriately introduced objective function. Notably, this method can be used to estimate structural parameters even for high damping ratios, and it also allows one to identify the Power Spectral Density (PSD) of the structural excitat…
A new approach to portfolio selection based on forecasting
2023
In this paper we analyze the portfolio selection problem from a novel perspective based on the analysis and prediction of the time series corresponding to the portfolio’s value. Namely, we define the value of a particular portfolio at the time of its acquisition. Using the time series of historical prices of the different financial assets, we calculate backward the value that said portfolio would have had in past time periods. A damped trend model is then used to analyze this time series and to predict the future values of the portfolio, providing estimates of the mean and variance for different forecasting horizons. These measures are used to formulate the portfolio selection problem, whic…
Hybrid Genetic Algorithms in Data Mining Applications
2009
Genetic algorithms (GAs) are a class of problem solving techniques which have been successfully applied to a wide variety of hard problems (Goldberg, 1989). In spite of conventional GAs are interesting approaches to several problems, in which they are able to obtain very good solutions, there exist cases in which the application of a conventional GA has shown poor results. Poor performance of GAs completely depends on the problem. In general, problems severely constrained or problems with difficult objective functions are hard to be optimized using GAs. Regarding the difficulty of a problem for a GA there is a well established theory. Traditionally, this has been studied for binary encoded …
An open-source GA framework for optimizing the seismic upgrading design of RC frames through BRBs
2022
Abstract Optimizing seismic upgrading interventions in reinforced concrete (RC) structures is a difficult task, due to the inner non-linearity of the analyses usually performed. Additionally, it is well known that the displacement demand to the structure depends from the mass and stiffness of the system, and consequently its definition cannot be made a-priori. This paper presents the application of a soft-computing method -i.e. Genetic Algorithm (GA)- for the shaping optimization of code-compliant seismic upgrading interventions on plane RC frames through Buckling-Restrained Braces (BRB). The metaheuristic procedure allows to minimize the cost while ensuring the required safety level, witho…
Automatic optimization of multichip RFID tags
2012
The automatic optimization is proposed of the passive RF part of RFID, with special attention to multi-chip tags, and to the novel concept of RFID grids. Performance metrics follows a recent all-comprehensive approach. The proposed approach employs a Genetic Algorithm-based optimization, and an efficient electromagnetic problem parameterization and solution strategy. Resulting structures, while non-intuitive in shape, exhibit enhanced performance.
Genetic Algorithm Optimized Grid-based RF Fingerprint Positioning in Heterogeneous Small Cell Networks
2015
In this paper we propose a novel optimization algorithm for grid-based RF fingerprinting to improve user equipment (UE) positioning accuracy. For this purpose we have used Multi-objective Genetic Algorithm (MOGA) which enables autonomous calibration of gridcell layout (GCL) for better UE positioning as compared to that of the conventional fingerprinting approach. Performance evaluations were carried out using two different training data-sets consisting of Minimization of Drive Testing measurements obtained from a dynamic system simulation in a heterogeneous LTE small cell environment. The robustness of the proposed method has been tested analyzing positioning results from two different area…
Multiobjective Optimal Reconfiguration of MV Networks with Different Earthing Systems
2010
The paper deals with the traditional problem of multiobjective optimal reconfiguration applied to power distribution systems considering the safety issue in the formulation. The applications are devoted to the solution of the posed problem in networks in which coexist energy sources with unearthed neutral point and resonant earthed neutral point. After a brief review of the most recent papers on optimal reconfiguration, the paper outlines the safety problem and provides a solution to the multiobjective problem using the Non dominated Sorting Genetic Algorithm II aiming at: minimal power losses operation, safety check at distribution substations and load balancing among the HV/MV transformer…
Development of a High Irradiance LED Configuration for Small Field of View Motion Estimation of Fertilizer Particles
2015
International audience; Better characterization of the fertilizer spreading process, especially the fertilizer pattern distribution on the ground, requires an accurate measurement of individual particle properties and dynamics. Both 2D and 3D high speed imaging techniques have been developed for this purpose. To maximize the accuracy of the predictions, a specific illumination level is required. This paper describes the development of a high irradiance LED system for high speed motion estimation of fertilizer particles. A spectral sensitivity factor was used to select the optimal LED in relation to the used camera from a range of commercially available high power LEDs. A multiple objective …