* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download 10-15 Using Decision Support Systems
Survey
Document related concepts
Wizard of Oz experiment wikipedia , lookup
Time series wikipedia , lookup
Clinical decision support system wikipedia , lookup
Ethics of artificial intelligence wikipedia , lookup
Personal knowledge base wikipedia , lookup
Human–computer interaction wikipedia , lookup
Collaborative information seeking wikipedia , lookup
Ecological interface design wikipedia , lookup
Embodied cognitive science wikipedia , lookup
History of artificial intelligence wikipedia , lookup
Transcript
McGraw-Hill/Irwin Copyright © 2008 2008,The TheMcGraw-Hill McGraw-HillCompanies, Companies,Inc. Inc.All Allrights rightsreserved. reserved. Chapter 10 Decision Support Systems McGraw-Hill/Irwin Copyright © 2008 2008,The TheMcGraw-Hill McGraw-HillCompanies, Companies,Inc. Inc.All Allrights rightsreserved. reserved. Levels of Managerial Decision Making 10-3 Information Quality • Information products made more valuable by their attributes, characteristics, or qualities • Information that is outdated, inaccurate, or hard to understand has much less value • Information has three dimensions • Time • Content • Form 10-4 Attributes of Information Quality 10-5 Decision Structure • Structured (operational) • The procedures to follow when decision is needed can be specified in advance • Unstructured (strategic) • It is not possible to specify in advance most of the decision procedures to follow • Semi-structured (tactical) • Decision procedures can be pre-specified, but not enough to lead to the correct decision 10-6 Decision Support Systems • Decision support systems use the following to support the making of semi-structured business decisions • • • • Analytical models Specialized databases A decision-maker’s own insights and judgments An interactive, computer-based modeling process • DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers 10-7 DSS Model Base • Model Base • A software component that consists of models used in computational and analytical routines that mathematically express relations among variables • Spreadsheet Examples • Linear programming • Multiple regression forecasting • Capital budgeting present value 10-8 Applications of Statistics and Modeling • Supply Chain: simulate and optimize supply chain flows, reduce inventory, reduce stock-outs • Pricing: identify the price that maximizes yield or profit • Product and Service Quality: detect quality problems early in order to minimize them • Research and Development: improve quality, efficacy, and safety of products and services 10-9 Management Information Systems • The original type of information system that supported managerial decision making • Produces information products that support many day-to-day decision-making needs • Produces reports, display, and responses • Satisfies needs of operational and tactical decision makers who face structured decisions 10-10 Management Reporting Alternatives • Periodic Scheduled Reports • Prespecified format on a regular basis • Exception Reports • Reports about exceptional conditions • May be produced regularly or when an exception occurs • Demand Reports and Responses • Information is available on demand • Push Reporting • Information is pushed to a networked computer 10-11 Online Analytical Processing • OLAP • Enables managers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives • Done interactively, in real time, with rapid response to queries 10-12 Online Analytical Operations • Consolidation • Aggregation of data • Example: data about sales offices rolled up to the district level • Drill-Down • Display underlying detail data • Example: sales figures by individual product • Slicing and Dicing • Viewing database from different viewpoints • Often performed along a time axis 10-13 Geographic Information Systems • GIS • DSS uses geographic databases to construct and display maps and other graphic displays • Supports decisions affecting the geographic distribution of people and other resources • Often used with Global Positioning Systems (GPS) devices 10-14 Using Decision Support Systems • Using a decision support system involves an interactive analytical modeling process • Decision makers are not demanding pre-specified information • They are exploring possible alternatives • What-If Analysis • Observing how changes to selected variables affect other variables 10-15 Using Decision Support Systems • Sensitivity Analysis • Observing how repeated changes to a single variable affect other variables • Goal-seeking Analysis • Making repeated changes to selected variables until a chosen variable reaches a target value • Optimization Analysis • Finding an optimum value for selected variables, given certain constraints 10-16 Data Mining • Provides decision support through knowledge discovery • Analyzes vast stores of historical business data • Looks for patterns, trends, and correlations • Goal is to improve business performance • Types of analysis • • • • • Regression Decision tree Neural network Cluster detection Market basket analysis 10-17 Market Basket Analysis • One of the most common uses for data mining • Determines what products customers purchase together with other products • Results affect how companies • • • • • Market products Place merchandise in the store Lay out catalogs and order forms Determine what new products to offer Customize solicitation phone calls 10-18 Artificial Intelligence (AI) • AI is a field of science and technology based on • • • • • • Computer science Biology Psychology Linguistics Mathematics Engineering • The goal is to develop computers than can simulate the ability to think • And see, hear, walk, talk, and feel as well 10-19 Attributes of Intelligent Behavior • Some of the attributes of intelligent behavior • • • • • • Think and reason Use reason to solve problems Learn or understand from experience Acquire and apply knowledge Exhibit creativity and imagination Deal with complex or perplexing situations 10-20 Attributes of Intelligent Behavior • Attributes of intelligent behavior (continued) • Respond quickly and successfully to new situations • Recognize the relative importance of elements in a situation • Handle ambiguous, incomplete, or erroneous information 10-21 Domains of Artificial Intelligence 10-22 Cognitive Science • Applications in the cognitive science of AI • • • • • • • Expert systems Knowledge-based systems Adaptive learning systems Fuzzy logic systems Neural networks Genetic algorithm software Intelligent agents • Focuses on how the human brain works and how humans think and learn 10-23 Robotics • AI, engineering, and physiology are the basic disciplines of robotics • Produces robot machines with computer intelligence and humanlike physical capabilities • This area include applications designed to give robots the powers of • • • • • Sight or visual perception Touch Dexterity Locomotion Navigation 10-24 Natural Interfaces • Major thrusts in the area of AI and the development of natural interfaces • Natural languages • Speech recognition • Virtual reality • Involves research and development in • • • • Linguistics Psychology Computer science Other disciplines 10-25 Latest Commercial Applications of AI • Decision Support • Helps capture the why as well as the what of engineered design and decision making • Information Retrieval • Distills tidal waves of information into simple presentations • Natural language technology • Database mining 10-26 Latest Commercial Applications of AI • Virtual Reality • X-ray-like vision enabled by enhanced-reality visualization helps surgeons • Automated animation and haptic interfaces allow users to interact with virtual objects • Robotics • Machine-vision inspections systems • Cutting-edge robotics systems • From micro robots and hands and legs, to cognitive and trainable modular vision systems 10-27 Expert Systems • An Expert System (ES) • A knowledge-based information system • Contain knowledge about a specific, complex application area • Acts as an expert consultant to end users 10-28 Benefits of Expert Systems • Captures the expertise of an expert or group of experts in a computer-based information system • • • • • Faster and more consistent than an expert Can contain knowledge of multiple experts Does not get tired or distracted Cannot be overworked or stressed Helps preserve and reproduce the knowledge of human experts 10-29 Limitations of Expert Systems • The major limitations of expert systems • • • • • Limited focus Inability to learn Maintenance problems Development cost Can only solve specific types of problems in a limited domain of knowledge 10-30 Developing Expert Systems • Suitability Criteria for Expert Systems • Domain: the domain or subject area of the problem is small and well-defined • Expertise: a body of knowledge, techniques, and intuition is needed that only a few people possess • Complexity: solving the problem is a complex task that requires logical inference processing 10-31 Developing Expert Systems • Suitability Criteria for Expert Systems • Structure: the solution process must be able to cope with ill-structured, uncertain, missing, and conflicting data and a changing problem situation • Availability: an expert exists who is articulate, cooperative, and supported by the management and end users involved in the development process 10-32 Neural Networks • Computing systems modeled after the brain’s mesh-like network of interconnected processing elements (neurons) • Interconnected processors operate in parallel and interact with each other • Allows the network to learn from the data it processes 10-33 Fuzzy Logic • Fuzzy logic • Resembles human reasoning • Allows for approximate values and inferences and incomplete or ambiguous data • Uses terms such as “very high” instead of precise measures • Used more often in Japan than in the U.S. • Used in fuzzy process controllers used in subway trains, elevators, and cars 10-34 Example of Fuzzy Logic Rules and Query 10-35 Virtual Reality (VR) • Virtual reality is a computer-simulated reality • Fast-growing area of artificial intelligence • Originated from efforts to build natural, realistic, multi-sensory human-computer interfaces • Relies on multi-sensory input/output devices • Creates a three-dimensional world through sight, sound, and touch • Also called telepresence 10-36 Typical VR Applications • Current applications of virtual reality • • • • • • • Computer-aided design Medical diagnostics and treatment Scientific experimentation Flight simulation Product demonstrations Employee training Entertainment 10-37 Intelligent Agents • A software surrogate for an end user or a process that fulfills a stated need or activity • Uses built-in and learned knowledge base to make decisions and accomplish tasks in a way that fulfills the intentions of a user • Also call software robots or bots 10-38