Search results for "STOCHASTIC"
showing 10 items of 1018 documents
The influence of temperature model assumptions on the prognosis accuracy of extinction risk
2000
Abstract For a species whose abundance is well-known to correlate on the degree of heat different temperature model assumptions may affect the prognosis accuracy of persistence. Likewise, year-to-year autocorrelations in weather fluctuations are known to decrease extinction risk. Thus, we investigated the grey bush cricket Platycleis albopunctata . For this species is known that growth and reproduction is mainly influenced by temperature. We developed a stochastic individual based model for the bush cricket. This day–degree model described the demographic growth of the species that depends on temperature. Daily temperatures were generated by five different methods: (i) temperatures were seq…
A laplace type problem for three lattices with non-convex cell
2016
In this paper we consider three lattices with cells represented in Fig. 1, 3 and 5 and we determine the probability that a random segment of constant length intersects a side of lattice. c ⃝2016 All rights reserved.
Disturbance observer-based disturbance attenuation control for a class of stochastic systems
2016
This paper studies a class of stochastic systems with multiple disturbances which include the disturbance with partially-known information and the white noise. A disturbance observer is constructed to estimate the disturbance with partially-known information, based on which, a disturbance observer-based disturbance attenuation control (DOBDAC) scheme is proposed by combining pole placement and linear matrix inequality (LMI) methods.
Tracking Control of Networked Multi-Agent Systems Under New Characterizations of Impulses and Its Applications in Robotic Systems
2016
This paper examines the problem of tracking control of networked multi-agent systems with multiple delays and impulsive effects, whose results are applied to mechanical robotic systems. Four kinds of impulsive effects are taken into account: 1) both the strengths of impulsive effects and the number of nodes injected with impulses are time dependent; 2) the strengths of impulsive effects occur according to certain probabilities and the number of nodes under impulsive control is time varying; 3) the strengths of impulses are time varying, whereas the number of nodes with impulses takes place according to certain probabilities; 4) both the strengths of impulses and the number of nodes with imp…
A Methodology for Modeling and Optimizing Social Systems
2020
[EN] A system methodology for modeling and optimizing social systems is presented. It allows constructing dynamical models formulated stochastically, i.e., their results are given by confidence intervals. The models provide optimal intervention ways to reach the stated objectives. Two optimization methods are used: (1) to test strategies and scenarios and (2) to optimize with a genetic algorithm. The application case presented is a small nonformal education Spanish business. First, the model is validated in the 2008-2012 period, and subsequently, the optimal way to obtain a maximum profit in the 2013-2025 period is obtained using the two methods.
Opinion Dynamics and Stubbornness via Multi-Population Mean-Field Games
2016
This paper studies opinion dynamics for a set of heterogeneous populations of individuals pursuing two conflicting goals: to seek consensus and to be coherent with their initial opinions. The multi-population game under investigation is characterized by (i) rational agents who behave strategically, (ii) heterogeneous populations, and (iii) opinions evolving in response to local interactions. The main contribution of this paper is to encompass all of these aspects under the unified framework of mean-field game theory. We show that, assuming initial Gaussian density functions and affine control policies, the Fokker---Planck---Kolmogorov equation preserves Gaussianity over time. This fact is t…
A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem
2012
Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_78 This paper deals with the Stochastic-Point Location (SPL) problem. It presents a solution which is novel in both philosophy and strategy to all the reported related learning algorithms. The SPL problem concerns the task of a Learning Mechanism attempting to locate a point on a line. The mechanism interacts with a random environment which essentially informs it, possibly erroneously, if the unknown parameter is on the left or the right of a given point which also is the current guess. The first pioneering work […
JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES
2018
In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By leveraging the Kalman filter framework, a three steps iterative algorithm is utilized to predict and update signal estimation as well as graph topology learning, called Topological Kalman Filter or TKF. Similar to the regular Kalman filter, we first predict the a posterior signal state based on the prior available data and then this prediction is updated and corrected based on the recently arrived measurement. But contrary to the conventional Kalman filter algorithm, we have no information of the transition matrix and hence we relate t…
On the estimation of the fatigue cycle distribution from spectral density data
1999
This paper deals with the fatigue life prediction of components and structures subjected to random fatigue, i.e. to cyclic loading whose amplitude varies in an essentially random manner. In particular, this study concentrates on the general problem of directly relating fatigue cycle distribution to the power spectral density (PSD) by means of closed-form expressions that avoid expensive digital simulations of the stress process. At present, all the methods proposed to achieve this objective are based on the use of a single parameter of the PSD. In this work, by numerical simulations and theoretical considerations, it is shown that the statistical distribution of fatigue cycles depends on f…
Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension
2016
We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…