China
Africa
Explore chapters and articles related to this topic
The Dual Porosity Model
Published in Abdon Atangana, Mathematical Analysis of Groundwater Flow Models, 2022
Siphokazi Simnikiwe Manundu, Abdon Atangana
Models are applied to provide qualitative descriptions of natural phenomena using mathematical formulas. These models greatly assist in solving complex real-world problems. Models can be classified into two different versions: stochastic models and deterministic models. A deterministic model does not consist of random outputs, and the complete input and output characteristics of the model are conclusively determined. An example of a deterministic model would be a car being driven on a cruise control system. The predetermined input values of the system such as speed and distance travelled over time provide a definite arrival time. This arrival time represents the output from the predetermined set of circumstances (inputs) (Atangana, 2020), whereas with stochastic models, the model consists of random outputs and the complete output characteristics of the model are randomly determined. One example of a stochastic model is a pumping test where head change is observed over time. In this case the head change is dependent on the aquifer characteristics at the given time which is also influenced by the geological conditions.
Definition of Simulation
Published in P. A. W. Lewis, E. J. Orav, Simulation Methodology for Statisticians, Operations Analysts, and Engineers, 2017
An idea that will come up repeatedly is that of a system. A system is a collection of interacting parts, and much of the effort in simulation is directed toward determining the result of such interactions. A computer is an example of a system, as is the whole complex of the computer users in their interaction with the computer. Some systems are called deterministic because, given the same input and starting situation, the output will be uniquely determined. But there are also systems where random, unpredictable events enter the interaction. These are called stochastic or random systems, and they are the type of systems considered in this book.
Modeling for System Control
Published in Bogdan M. Wilamowski, J. David Irwin, Control and Mechatronics, 2018
A deterministic system is a system without random parameters or inputs. In other words, the system is known exactly. On the other hand, a stochastic system is one in which at least one parameter or input is affected by random disturbances or noise. The external signals that influence a system also have to be modeled. They are also either deterministic or stochastic. These random disturbances affecting the system parameters or inputs could be known and measurable, known and nonmeasurable, or unknown. Smoothing, filtering, and estimation techniques are used to get an accurate response for a stochastic system.
Comfort and energy performance analysis of different glazing systems coupled with three shading control strategies
Published in Science and Technology for the Built Environment, 2018
Anna Maria Atzeri, Andrea Gasparella, Francesca Cappelletti, Athanasios Tzempelikos
Deterministic control strategies can be based on measured or model-predicted quantities. Measurement-based strategies using workplane or vertical illuminance, solar radiation, and indoor temperature are easier to implement. A detailed analysis of such strategies describing simple to more complex controls, including the case of variable set-points and intermediate shade positions, is reported in Tzempelikos and Shen (2013). Motorized roller shades that open from top to bottom, covering the lower part for glare control, were proposed by Kapsis et al. (2010). Such a design would allow daylight to be admitted into the room through the upper part, therefore reducing lighting energy consumption, and maintaining similar performance in terms of glare protection as common roller shades if internal installation is considered.
Approximate Q-Learning for Stacking Problems with Continuous Production and Retrieval
Published in Applied Artificial Intelligence, 2019
Judith Fechter, Andreas Beham, Stefan Wagner, Michael Affenzeller
A policy defines the sequence of actions. Roughly speaking, a deterministic policy is a mapping from states to actions, determining which action needs to be taken while being in a certain state.