Related papers: Parameter optimization for surface flux transport …
A long-standing and difficult problem in, e.g., condensed matter physics is how to find the ground state of a complex many-body system where the potential energy surface has a large number of local minima. Spin systems containing complex…
This paper explores the effects of numerical algorithms on global magnetohydrodynamics (MHD) simulations of solar wind (SW) in the inner heliosphere. To do so, we use sunRunner3D, a 3-D MHD model that employs the boundary conditions…
Complex networks theory has commonly been used for modelling and understanding the interactions taking place between the elements composing complex systems. More recently, the use of generative models has gained momentum, as they allow…
Observations of the meridional circulation of the Sun, which plays a key role in the operation of the solar dynamo, indicate that its speed varies with the solar cycle, becoming faster during the solar minima and slower during the solar…
Without any doubt solar flaring loops possess a multi-thread internal structure that is poorly resolved and there are no means to observe heating episodes and thermodynamic evolution of the individual threads. These limitations cause…
Several approaches exist to model gravitational lens systems. In this study, we apply global optimization methods to find the optimal set of lens parameters using a genetic algorithm. We treat the full optimization procedure as a two-step…
This paper intends to cover three main topics. First, a fuzzy-PID controller is designed to control the thrust vector of a launch vehicle, accommodating a CanSat. Then, the genetic algorithm (GA) is employed to optimize the controller…
The problem of prediction of a given time series is examined on the basis of recent nonlinear dynamics theories. Particular attention is devoted to forecast the amplitude and phase of one of the most common solar indicator activity, the…
Many power system operation and planning problems use the DC power flow approximation to address computational challenges from the nonlinearity of the AC power flow equations. The DC power flow simplifies the AC power flow equations to a…
Using time-distance helioseismology applied to 14-years of SDO/HMI observations spanning solar cycle 24 and rising phase of cycle 25, we present evidence that meridional flows in the lower half of the near-surface shear layer (NSSL),…
We consider a numerical framework tailored to identifying optimal parameters in the context of modelling disease propagation. Our focus is on understanding the behaviour of optimisation algorithms for such problems, where the dynamics are…
Highly-optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is non-convex and characterized by…
While standard solar model (SSM) predictions depend on approximately 20 input parameters, SSM neutrino flux predictions are strongly correlated with a single model output parameter, the core temperature $T_c$. Consequently, one can extract…
The occurrence of grand minima like the Maunder minimum is an intriguing aspect of the sunspot cycle. We use the flux transport dynamo model to explain the grand minima, showing that they arise when either the poloidal field or the…
The dynamics of cellular pattern formation is crucial for understanding embryonic development and tissue morphogenesis. Recent studies have shown that human dermal fibroblasts cultured on liquid crystal elastomers can exhibit an increase in…
In this study, an interplanetary space flight mission design is established to obtain the minimum \(\Delta V\) required for a rendezvous and sample return mission from an asteroid. Given the initial (observed) conditions of an asteroid, a…
The solar dynamo problem is the question of how the cyclic variation in the solar magnetic field is maintained. One of the important processes is the transport of magnetic flux by surface convection. To reveal this process, the dependence…
Numerical plant models can predict the outcome of plant traits modifications resulting from genetic variations, on plant performance, by simulating physiological processes and their interaction with the environment. Optimization methods…
We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 h. Machine learning is used to devise algorithms that can learn from and make decisions on…
Data obtained from Flow Cytometry present pronounced variability due to biological and technical reasons. Biological variability is a well-known phenomenon produced by measurements on different individuals, with different characteristics…