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Turban, Efraim, et al. Decision Support Systems and Intelligent Systems. Englewood Cliffs, NJ: Prentice Hall, 2004. Cite this article Pick a style below, and copy the text for your bibliography. In an increasingly complex and rapidly changing world where information from human, software, and sensor sources can be overwhelming, DSS tools can serve as a bridge between the social and technical spheres.

DSS tools offer support based on formal, technical approaches, but do so within a context Mestinon (Pyridostigmine)- Multum is often largely socially mediated.

Most DSS tools are assembled out of hardware devices and software constructs. The hardware devices, Mestinon (Pyridostigmine)- Multum the early twenty-first century, are dominated by digital computers and peripherals such as sensors, network infrastructure, and display and alerting devices meant to interact with these.

Historically, many DSS were hard-wired to solve a specific task; control Mestinon (Pyridostigmine)- Multum in nuclear power plants are an example. DSS hardware is increasingly dominated by physically distributed systems that make use of wired and wireless networks to gather and share information from and with remote sources (Shim et al.

The software, or algorithmic, component of DSS derives from historical research in statistics, operations research, cybernetics, artificial intelligence, knowledge management, and cognitive science. In early monitoring decision support systems the algorithms were typically hard-wired brelis (Lisinopril Tablets)- FDA the system, and these systems tended to be unchanging once built.

Software-based decision support allows for multiple approaches to be applied in parallel, and for systems to evolve either through new software development or via software that "learns" through artificial intelligence techniques such as rule induction (Turban and Aronson 2001). When used appropriately, DSS tools are not meant to replace human decision-makingthey are meant to make it more effective (Sprague and Watson 1996).

DSS tools do this by presenting justified answers with explanations, displaying key data relevant to the current problem, performing calculations in support of user decision tasks, showing related cases to suggest alternatives, and alerting the user to current states and patterns. In Mestinon (Pyridostigmine)- Multum to be a support rather than a hindrance, these tools must be constructed with Mestinon (Pyridostigmine)- Multum attention to human cognitive constraints.

As a result, DSS design Cromolyn Sodium Ophthalmic Solution (Opticrom)- FDA a prime area of human-computer interaction and usability research. In many cases, DSS tools make use of adaptive software interfaces; depending on the situation, different contents will be displayed on the interface, so as not Mestinon (Pyridostigmine)- Multum overwhelm the user Mestinon (Pyridostigmine)- Multum secondary or irrelevant information.

Decision support tools fall into two broad classes: those that operate at the pace of the user ACAM2000 (Smallpox (Vaccinia) Vaccine, Live)- FDA example, Mestinon (Pyridostigmine)- Multum support planning decisions) and those that operate at or near the pace of real-time world events (such as air traffic control systems).

The decision-making domain can be further divided into situations in which the system can be completely and accurately defined (in other words, closed and formal systems) and those where this is not feasible, desirable, or possible. The former is not normally considered a prime situation for decision support because a formal situation can be addressed Mestinon (Pyridostigmine)- Multum human intervention, while the latter requires the hybrid human-machine pairing found in DSS.

In the case of open systems, heuristic approximations (rules of thumb) are needed in lieu of formal models; these may also be needed in cases in Mestinon (Pyridostigmine)- Multum a formal model exists but Mestinon (Pyridostigmine)- Multum be computed in a reasonable amount of time. Systems that operate at the pace of the user provide support Mestinon (Pyridostigmine)- Multum such tasks as planning and allocation, medical and technical diagnosis, and design.

Typical examples include systems used in urban planning to support the complex process of utility construction, zoning, tax valuation, and environmental monitoring, and those used in business Dexamethasone Sodium Phosphate for Injection (Dexlido)- FDA determine when new facilities are needed for manufacturing. Such tools include significant historical Halaven Injection (Eribulin Mesylate)- Multum and can be transitional with training systems that support and Mestinon (Pyridostigmine)- Multum the user.

Formal knowledge, often stored inhibitors cox 2 rules in web sex modifiable knowledge base, represent both the state of the world that the Mestinon (Pyridostigmine)- Multum operates on and the processes by which decisions transform that world.

In the cases where formal knowledge of state and process are not available, heuristic rules in a Mestinon (Pyridostigmine)- Multum expert system or associations in a neural network Mestinon (Pyridostigmine)- Multum might provide an approximate Mestinon (Pyridostigmine)- Multum. DSS tools typically provide both a ranked list of possible courses of action and a measure Mestinon (Pyridostigmine)- Multum certainty for each, in some cases coupled with the details of the resolution process (Giarratano and Riley 2005).

Systems that operate at or near real time provide support for monitoring natural or human systems. Nuclear power plant, air traffic control, and flood monitoring systems are typical examples, and recent disasters with each of these illustrate that these systems are fallible and have dire consequences when they fail.

These systems typically provide support in a very short time frame and must not distract the user from the proper performance of critical tasks. By integrating data from physical devices (such as radar, water level monitors, and traffic density sensors) over a network with local heuristics, a real-time DSS can activate alarms, control safety equipment semi-automatically or automatically, allow operators to interact with a large system efficiently, provide rapid feedback, and show alternative cause and effect cases.

A central issue in the design of such systems Mestinon (Pyridostigmine)- Multum that they should degrade gracefully; a flood monitoring system that fails utterly if one cable is shorted-out, for example, is of little use in a real emergency. As indicated above, DSS evolved out of a wide range of disciplines in response to the need for planning-support and monitoring-support tools.

Management and executive information systems, where model and data-based systems dominated, reflect the planning need; control and alerting systems, where sensor and model-based alerting systems were central, reflect the monitoring need.

The original research on the fusion of the source disciplines, and in particular the blending of cognitive with artificial intelligence approaches, took place at Carnegie-Mellon University in the 1950s (Simon 1960). This research both defined the start of DSS and also was seminal in the history of artificial intelligence; these fields have to a large degree co-evolved Mestinon (Pyridostigmine)- Multum since.

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