Related papers: A Genetic Algorithm Analysis of N* Resonances in $…
The $(1+(\lambda,\lambda))$ genetic algorithm is a bright example of an evolutionary algorithm which was developed based on the insights from theoretical findings. This algorithm uses crossover, and it was shown to asymptotically outperform…
We propose a genetic algorithm (GA) for hyperparameter optimization of artificial neural networks which includes chromosomal crossover as well as a decoupling of parameters (i.e., weights and biases) from hyperparameters (e.g., learning…
The data on differential cross sections and photon-beam asymmetries for the $\gamma p \to K^+\Lambda(1520)$ reaction have been analyzed within a tree-level effective Lagrangian approach. In addition to the $t$-channel $K$ and $K^\ast$…
Big data applications, such as medical imaging and genetics, typically generate datasets that consist of few observations n on many more variables p, a scenario that we denote as p>>n. Traditional data processing methods are often…
Recently we presented a successful strategy to extract the position of the two $\Lambda(1405)$ poles from experimental photoproduction data on the $\gamma p \to K^+ \pi^0 \Sigma^0 $ reaction at Jefferson Lab. Following a similar strategy,…
Our goal in this paper is to automatically extract a set of decision rules (rule set) that best explains a classification data set. First, a large set of decision rules is extracted from a set of decision trees trained on the data set. The…
Results from a partial-wave analysis of the reaction $\gamma p \rightarrow K^+ \Lambda$ are presented. The reaction is dominated by the $S_{11}(1650)$ and $P_{13}(1720)$ resonances at low energies and by $P_{13}(1900)$ at higher energies.…
We apply a stochastic method of minimizing the ground state energy in variational calculations of light nuclei using the Refined Resonating Group Model (RRGM). The method utilizes a bit representation of the width parameters to be varied.…
Coverage of image features play an important role in many vision algorithms since their distribution affect the estimated homography. This paper presents a Genetic Algorithm (GA) in order to select the optimal set of features yielding…
We present development of a genetic algorithm for fitting potential energy curves of diatomic molecules to experimental data. Our approach does not involve any functional form for fitting, which makes it a general fitting procedure. In…
Isotonic regression is a nonparametric approach for fitting monotonic models to data that has been widely studied from both theoretical and practical perspectives. However, this approach encounters computational and statistical overfitting…
A Bayesian analysis of the world's $p(\gamma,K^+)\Lambda$ data is presented. We adopt a Regge-plus-resonance framework featuring consistent interactions for nucleon resonances up to spin $J = 5/2$. The power of the momentum dependence of…
Optimization problems frequently appear in any scientific domain. Most of the times, the corresponding decision problem turns out to be NP-hard, and in these cases genetic algorithms are often used to obtain approximated solutions. However,…
The high-precision differential cross-section data for the reaction $\gamma p \to K^{*+}\Lambda$ are reanalyzed within a Regge-inspired effective Lagrangian approach. The model adopts Regge phenomenology to constrain the $t$-channel…
An isobar model containing Born terms, vector meson exchange and nucleon resonances is used to analyze recent eta photoproduction data for cross section and beam asymmetry, as well as JLab electroproduction data. Good overall description is…
Genetic algorithms are a powerful tool in optimization for single and multi-modal functions. This paper provides an overview of their fundamentals with some analytical examples. In addition, we explore how they can be used as a parameter…
Genetic algorithms have played an important role in engineering optimization. Traditional GAs treat each gene separately. However, biophysical studies of gene regulatory networks revealed direct associations between different genes. It…
The associate $K\Lambda(1520)$ photon and hadronic production in the $\gamma p \to K^+\Lambda(1520)$, $p p \to p K^+ \Lambda(1520)$ and $\pi^- p \to K^0 \Lambda(1520)$ reactions are investigated within the effective Lagrangian approach and…
An algorithm for optimization of signal significance or any other classification figure of merit suited for analysis of high energy physics (HEP) data is described. This algorithm trains decision trees on many bootstrap replicas of training…
Image Registration (IR) is the process of aligning two (or more) images of the same scene taken at different times, different viewpoints and/or by different sensors. It is an important, crucial step in various image analysis tasks where…