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Troubleshooting is a form of problem solving, often applied to repair failed products or processes on a machine or a system. It is a logical, systematic search for the source of a problem in order to solve it, and make the product or process operational again. Troubleshooting is needed to identify the symptoms.
Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields.
Gigerenzer & Gaissmaier (2011) state that sub-sets of strategy include heuristics, regression analysis, and Bayesian inference. [14]A heuristic is a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods (Gigerenzer and Gaissmaier [2011], p. 454; see also Todd et al. [2012], p. 7).
Network problems that involve finding an optimal way of doing something are studied as combinatorial optimization.Examples include network flow, shortest path problem, transport problem, transshipment problem, location problem, matching problem, assignment problem, packing problem, routing problem, critical path analysis, and program evaluation and review technique.
This approach can be seen as one of the two basic approaches to problem-solving, contrasted with an approach using insight and theory. However, there are intermediate methods that, for example, use theory to guide the method, an approach known as guided empiricism. [citation needed]
Social problem-solving, in its most basic form, is defined as problem solving as it occurs in the natural environment. [1] More specifically it refers to the cognitive-behavioral process in which one works to find adaptive ways of coping with everyday situations that are considered problematic.
Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges).
Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. [1] It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them.