83690136 sess-3-modelling-and-simulation

17 de Sep de 2012
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
83690136 sess-3-modelling-and-simulation
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83690136 sess-3-modelling-and-simulation

Notas do Editor

  1. Being numerate does not necessarily mean being a mathematician, but it does mean being comfortable with figures and appreciating that there are a number of numerate techniques that can be applied to business problems.
  2. Another example of a system would be the accounting/bookkeeping functions of a small business. In this case we would have the accounting employees who would be using their separate accounting responsibilities, the computer information system, clients, suppliers. “ There are many definitions of complexity, therefore many natural, artificial and abstract objects or networks can be considered to be complex systems , and their study ( complexity science ) is highly interdisciplinary. Examples of complex systems include ant-hills, ants themselves, human economies, nervous systems, cells and living things, including human beings, as well as modern energy or telecommunication infrastructures. " Without doubts, the common property of complex systems is the difficulty of their formal modeling" (Gadomski. A.M.). Beyond the fact that these things are all networks of some kind, and that they are complex, it may appear that they have little in common, hence that the term "complex system" is vacuous. However, all complex systems are held to have behavioural and structural features in common, which at least to some degree unites them as phenomena. They are also united theoretically, because all these systems may, in principle, be modelled with varying degrees of success by a certain kind of mathematics. It is therefore possible to state clearly what it is that these systems are supposed to have in common with each other, in relatively formal terms.” Wikipedia
  3. Example: Ecological systems are open systems with respect to most elements and processes. They receive energy and nutrient inputs from their physical environment and, at the same time, cycle nutrients back out of the system. They are also open to outside influences such as disturbances (e.g., hurricanes, ice storms, fires, insect outbreaks).
  4. For example, the nested system above right could represent: atoms (black dots), molecules (blue balls ), cells (brown circle), and organs (green); leaves (black dots), trees (blue balls ), stands (brown circle), and landscapes (green); planets (black dots), solar systems (blue balls ), galaxies (brown circle), and universes (green).
  5. The hard and soft systems approaches each provide a basic guide for conceptualizing and structuring management problems. Distinguishing between them is not necessarily meant to imply that either is right or wrong. Indeed, it many cases it is advantageous to adopt an approach that exploits the notion of soft/hard complementarity, with the soft systems approach providing an overall problem management framework, and the hard systems approach focused on appropriate sub-problems (Walker, 1996).
  6. The hard systems approach conceptualizes problems with well-defined boundaries and simple linkages with other problems . Goals, alternatives and consequences are well-defined. The standard management technique is to collect and analyse data, unilaterally decide on a best course of action, and implement accordingly. An example of a hard systems approach to a management problem is the use of optimization models to determine reservoir levels for maximum hydro-power production efficiency. In contrast, soft systems problems are viewed as having the following characteristics: ambiguous boundaries and complex linkages with other problems; goals, alternatives, and consequences which are not well-defined or well-understood; pervasive uncertainty which may not be quantifiable; and iterative management which involves conflict and negotiation among multiple stakeholders with divergent interests and values.
  7. 2. Hierarchic systems may be decomposable, because they can be divided into identifiable parts; also systems may be nearly decomposable, because their parts are not completely independent. 3. This difference between intra- and inter-component interactions provides a clear separation of concerns among the various parts of a system, making it possible to study each part in relative isolation. 4. In other words, complex systems have common patterns. These patterns may involve the reuse of small components, such as the cells found in both plants and animals, or of larger structures, such as vascular systems, also found in both plants and animals.
  8. Many financial systems are static in that they give the financial state of a company or individual at a particular date. The progress of an airline passenger as he/she moves through an airport is dynamic system since he/she will be in a different position at different times.
  9. Scale Models: models of cars, ships, aircraft, wax statues. Imitation Models: dolls, shop window models, cartoons, puppets, logical or political divisions in a map. Analogue Models: blood flow or money flow, water flow to study traffic flow, mercury or alcohol to measure temperature, rats and monkeys to test new medicines.
  10. The real system refers to nothing more or less than a source of observable data. The variable of a real system can be classified as observable or non-observable. The non-observable variables are those that cannot at present be measured directly. Observable variables are classified as input or output variables.
  11. The basic elements and relations of the modelling and simulation enterprise.