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| decision support and expert systems: Decision Support and Expert Systems Efraim Turban, 1995 Decision support systems; management support systems: an overview; decision making, systems, modeling, and support; data management; modeling and model management; user interface; constructing a decision support system; organizational DSS and advanced topics; enterprise support systems; Group decision support systems; executive information and support systems; fundamentals of artificial intelligence and expert systems; applied artificial intelligence: an overview; fundamentals of expert systems; knowledge acquisition and validation; knowledge representation; inferences, explanations, and uncertainty; building expert systems: process and tools; cutting edge decision support technologies; neural computing: the basics; neural computing applications, genetic algorithms, and fuzzy logic; integrating and implementation; integrating decision support technologies; Implementing management support systems; organizational and societal impacts of management support systems; appendix and student project. |
| decision support and expert systems: Decision Support and Expert Systems Efraim Turban, 1993 |
| decision support and expert systems: Understanding Decision Support Systems and Expert Systems Efrem Mallach, 1994 This core textbook contains a focused approach to understanding and building decision support systems. |
| decision support and expert systems: Decision Support Systems and Intelligent Systems Efraim Turban, Jay E. Aronson, Ting-Peng Liang, 2005 Appropriate for all courses in Decision Support Systems (DSS), computerized decision making tools, and management support systems. Todays networked computer systems enable executives to use information in radically new ways, to make dramatically more effective decisions -- and make those decisions more rapidly. Decision Support Systems and Intelligent Systems, Seventh Edition is a comprehensive, up-to-date guide to todays revolutionary management support system technologies, and how they can be used for better decision making. In this thoroughly revised edition, the authors go far beyond traditional decision support systems, focusing far more coverage on Web-enabled tools, performance analysis, knowledge management, and other recent innovations. The authors introduce each significant new technology, show how it works, and offer practical guidance on integrating it into real-world organizations. Examples, products, services, and exercises are presented throughout, and the text has been revised for improved clarity and readability. New and enhanced coverage includes: state-of-the-art data mining, OLAP, expert system, and neural network software; revamped coverage of knowledge management; and a far greater emphasis on the use of Web technologies throughout. Also covered in detail: data warehousing, including access, analysis, visualization, modeling, and support. This edition also contains DSS In Action boxes presenting real business scenarios for the use of advanced management support technology. Decision Support Systems and Intelligent Systems, Seventh Edition is supported by a Web site containing additional readings, relevant links, and other supplements. |
| decision support and expert systems: Fuzzy Sets, Decision Making, and Expert Systems Hans-Jürgen Zimmermann, 1987-07-31 In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed. |
| decision support and expert systems: Expert Systems Cornelius T. Leondes, 2001-09-26 This six-volume set presents cutting-edge advances and applications of expert systems. Because expert systems combine the expertise of engineers, computer scientists, and computer programmers, each group will benefit from buying this important reference work. An expert system is a knowledge-based computer system that emulates the decision-making ability of a human expert. The primary role of the expert system is to perform appropriate functions under the close supervision of the human, whose work is supported by that expert system. In the reverse, this same expert system can monitor and double check the human in the performance of a task. Human-computer interaction in our highly complex world requires the development of a wide array of expert systems. Expert systems techniques and applications are presented for a diverse array of topics including Experimental design and decision support The integration of machine learning with knowledge acquisition for the design of expert systems Process planning in design and manufacturing systems and process control applications Knowledge discovery in large-scale knowledge bases Robotic systems Geograhphic information systems Image analysis, recognition and interpretation Cellular automata methods for pattern recognition Real-time fault tolerant control systems CAD-based vision systems in pattern matching processes Financial systems Agricultural applications Medical diagnosis |
| decision support and expert systems: Knowledge-based Expert Systems in Chemistry Philip Judson, 2019-02-07 There have been significant developments in the use of knowledge-based expert systems in chemistry since the first edition of this book was published in 2009. This new edition has been thoroughly revised and updated to reflect the advances. The underlying theme of the book is still the need for computer systems that work with uncertain or qualitative data to support decision-making based on reasoned judgements. With the continuing evolution of regulations for the assessment of chemical hazards, and changes in thinking about how scientific decisions should be made, that need is ever greater. Knowledge-based expert systems are well established in chemistry, especially in relation to toxicology, and they are used routinely to support regulatory submissions. The effectiveness and continued acceptance of computer prediction depends on our ability to assess the trustworthiness of predictions and the validity of the models on which they are based. Written by a pioneer in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry. |
| decision support and expert systems: Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering Management Association, Information Resources, 2021-05-28 Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries. |
| decision support and expert systems: Expert Systems and Artificial Intelligence in Decision Support Systems Henk G. Sol, Cees A.Th. Takkenberg, Pieter F. de Vries Robbé, 1987-03-31 In 1985 it was 20 years since Nobel Laureate Herbert A. Simon published: 'THE SHAPE OF AUTOMATION: For Men and Management'. This short but important and still topical book dwells on three subjects: - The Long-Range Economic Effects of Automation; - Will the Corporation be Managed by Machines? - The New Science of Management Decision. In contrast with George Orwell, who was a critic of contemporary political systems rather than a prophet, Simon portrays a far more rosy picture of our 'brave new world'. Simon's work breathes optimism. First, computer technology; looking back it is aoubtful whether even the professor expected the hardware development ~e have wittnessed. Secondly, our ability to 'tame the beast'; there is now not much reason for complacency and satisfaction. Offices and factories can by no means be called automated, at most semi-automated. Thirdly the organizational and social implications of these rapid technological developments; referring to what he then called: 'The Computer and the new decision making techniques ..• ' Concerning this last point, there is little need to emphasize that had been less practical application in organizations than the often impressive theoretical developments would lead one to believe. In Europe this situation is even more accute than in the USA and Japan. The ESPRIT programme of the ECC and many similar national programs intend to bridge the gap. |
| decision support and expert systems: Guide to Health Informatics Enrico Coiera, 2015-03-06 This essential text provides a readable yet sophisticated overview of the basic concepts of information technologies as they apply in healthcare. Spanning areas as diverse as the electronic medical record, searching, protocols, and communications as well as the Internet, Enrico Coiera has succeeded in making this vast and complex area accessible and understandable to the non-specialist, while providing everything that students of medical informatics need to know to accompany their course. |
| decision support and expert systems: Investment Management Robert R. Trippi, Efraim Turban, 1990 Includes bibliographical references. |
| decision support and expert systems: Expert Systems and Artificial Intelligence in Decision Support Systems Henk G. Sol, Cees A.Th. Takkenberg, Pieter F. de Vries Robbé, 2013-11-11 In 1985 it was 20 years since Nobel Laureate Herbert A. Simon published: 'THE SHAPE OF AUTOMATION: For Men and Management'. This short but important and still topical book dwells on three subjects: - The Long-Range Economic Effects of Automation; - Will the Corporation be Managed by Machines? - The New Science of Management Decision. In contrast with George Orwell, who was a critic of contemporary political systems rather than a prophet, Simon portrays a far more rosy picture of our 'brave new world'. Simon's work breathes optimism. First, computer technology; looking back it is aoubtful whether even the professor expected the hardware development ~e have wittnessed. Secondly, our ability to 'tame the beast'; there is now not much reason for complacency and satisfaction. Offices and factories can by no means be called automated, at most semi-automated. Thirdly the organizational and social implications of these rapid technological developments; referring to what he then called: 'The Computer and the new decision making techniques ..• ' Concerning this last point, there is little need to emphasize that had been less practical application in organizations than the often impressive theoretical developments would lead one to believe. In Europe this situation is even more accute than in the USA and Japan. The ESPRIT programme of the ECC and many similar national programs intend to bridge the gap. |
| decision support and expert systems: Knowledge-Based Decision Support Systems With Applications in Business Michel Klein, Leif B. Methlie, 1995-09-13 This book uniquely integrates expert system technology with decision support technology and introduces a new conceptual framework - knowledge-based decision support systems. The book provides comprehensive, knowledge-based decision support systems for a business-oriented audience. |
| decision support and expert systems: Decision Support and Expert Systems William E. Leigh, Michael E. Doherty, 1986 The greater availability of computer systems has led to the application of computers to decision making processes in academia and business. This has led to the development of a specific area of academic research into computing, and this discipline is known as Decision Support Systems (DSS). This textbook supports the CIS-10 course of the Model Curriculum for Undergraduate Computer Information Systems Education of the Data Processing Management Association Education Foundation. Designed for use by upper-division students with previous grounding in the principles of computer information systems, or for business majors who expect to be uses of DSS and expert systems. |
| decision support and expert systems: Handbook on Decision Support Systems 1 Frada Burstein, Clyde W. Holsapple, 2008-01-22 Decision support systems have experienced a marked increase in attention and importance over the past 25 years. The aim of this book is to survey the decision support system (DSS) field – covering both developed territory and emergent frontiers. It will give the reader a clear understanding of fundamental DSS concepts, methods, technologies, trends, and issues. It will serve as a basic reference work for DSS research, practice, and instruction. To achieve these goals, the book has been designed according to a ten-part structure, divided in two volumes with chapters authored by well-known, well-versed scholars and practitioners from the DSS community. |
| decision support and expert systems: Data Mining and Decision Support Dunja Mladenic, 2003-09-30 Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting. |
| decision support and expert systems: Intelligent Decision Support Systems Surekha Borra, Nilanjan Dey, Siddhartha Bhattacharyya, Mohamed Salim Bouhlel, 2019-10-21 Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD). |
| decision support and expert systems: Decision Support and Expert Systems Efraim Turban, 1988 |
| decision support and expert systems: Decision Support Systems George-M. Marakas, 2007 |
| decision support and expert systems: Decision Support Models and Expert Systems David Louis Olson, James Forrest Courtney, 1992 |
| decision support and expert systems: Public Health Informatics and Information Systems J.A. Magnuson, Paul C. Fu, Jr., 2013-12-04 This revised edition covers all aspects of public health informatics and discusses the creation and management of an information technology infrastructure that is essential in linking state and local organizations in their efforts to gather data for the surveillance and prevention. Public health officials will have to understand basic principles of information resource management in order to make the appropriate technology choices that will guide the future of their organizations. Public health continues to be at the forefront of modern medicine, given the importance of implementing a population-based health approach and to addressing chronic health conditions. This book provides informatics principles and examples of practice in a public health context. In doing so, it clarifies the ways in which newer information technologies will improve individual and community health status. This book's primary purpose is to consolidate key information and promote a strategic approach to information systems and development, making it a resource for use by faculty and students of public health, as well as the practicing public health professional. Chapter highlights include: The Governmental and Legislative Context of Informatics; Assessing the Value of Information Systems; Ethics, Information Technology, and Public Health; and Privacy, Confidentiality, and Security. Review questions are featured at the end of every chapter. Aside from its use for public health professionals, the book will be used by schools of public health, clinical and public health nurses and students, schools of social work, allied health, and environmental sciences. |
| decision support and expert systems: The Dynamics of Decision Support Systems and Expert Systems Jay Liebowitz, 1990 In most business information systems curricula, either a course on decision support systems (DSSs) or a separate track in DSSs has been established. Decision support systems have been around since the early 1970s, and their proliferation and use in homes and businesses have increased dramatically over the years. In recent years, however, the impact of artificial intelligence, particularly expert systems (ESs), has accelerated DSS technology--its applications, design methodologies, and implementation strategies. The goal of this book is to explain DSSs and ESs--the relationships between these two applied technologies, their synergistic effects upon each other, and their differences--and to show what effect their interaction has had on the framework, processes, and technical components for building DSSs. |
| decision support and expert systems: Artificial Intelligence in Behavioral and Mental Health Care David D. Luxton, 2015-09-10 Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings |
| decision support and expert systems: Mathematical Models for Decision Support Harvey J. Greenberg, Gautam Mitra, Freerk A. Lootsma, Marcel J. Rijckaert, Hans J. Zimmermann, 2012-12-06 It is quite an onerous task to edit the proceedings of a two week long institute with learned contributors from many parts of the world. All the same, the editorial team has found the process of refereeing and reviewing the contributions worthwhile and completing the volume has proven to be a satisfying task. In setting up the institute we had considered models and methods taken from a number of different disciplines. As a result the whole institute - preparing for it, attending it and editing the proceedings - proved to be an intense learning experience for us. Here I speak on behalf of the committee and the editorial team. By the time the institute took place, the papers were delivered and the delegates exchanged their views, the structure of the topics covered and their relative positioning appeared in a different light. In editing the volume I felt compelled to introduce a new structure in grouping the papers. The contents of this volume are organised in eight main sections set out below: 1 . Abstracts. 2. Review Paper. 3. Models with Multiple Criteria and Single or Multiple Decision Makers. 4. Use of Optimisation Models as Decision Support Tools. 5. Role of Information Systems in Decision Making: Database and Model Management Issues. 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems. 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. 8. Mathematical Basis for Constructing Models and Model Validation. |
| decision support and expert systems: Decision Support Systems for Sustainable Development Gregory E. Kersten, Zbigniew Mikolajuk, Anthony Gar-On Yeh, 2006-03-01 In recent years, much work has been done in formulating and clarifying the concept of sustainable development and related theoretical and research issues. Now, the challenge has shifted to designing and stimulating processes of effective planning and decision-making, at all levels of human activity, in such a way as to achieve local and global sustainable development. Information technology can help a great deal in achieving sustainable development by providing well-designed and useful tools for decision makers. One such tool is the decision support system, or DSS. This book explores the area of DSS in the context of sustainable development. As DSS is a very new technique, especially in the developing world, this book will serve as a reference text, primarily for managers, government officials, and information professionals in developing countries. It covers the concept of sustainable development, defines DSS and how it can be used in the planning and management of sustainable development, and examines the state of the art in DSS use. Other interested readers will include students, teachers, and analysts in information sciences; DSS designers, developers, and implementors; and international development agencies. |
| decision support and expert systems: Foundations of Decision Support Systems Robert H. Bonczek, Clyde W. Holsapple, Andrew B. Whinston, 2014-05-10 Foundations of Decision Support Systems focuses on the frameworks, strategies, and techniques involved in decision support systems (DSS). The publication first takes a look at information processing, decision making, and decision support; frameworks for organizational information processing and decision making; and representative decision support systems. Discussions focus on classification scheme for DSS, abilities required for decision making, division of information-processing labor within an organization, and decision support. The text then elaborates on ideas in decision support, formalizations of purposive systems, and conceptual and operational constructs for building a data base knowledge system. The book takes a look at building a data base knowledge system, language systems for data base knowledge systems, and problem-processing systems for data base knowledge systems. Topics include problem processors for computationally oriented DSS, major varieties of logical data structures, and indirect associations among concepts. The manuscript also examines operationalizing modeling knowledge in terms of predicate calculus; combining the data base and formal logic approaches; and the language and knowledge systems of a DSS based on formal logic. The publication is a valuable reference for researchers interested in decision support systems. |
| decision support and expert systems: Fuzzy Sets, Decision Making, and Expert Systems Hans-Jürgen Zimmermann, 2012-12-06 In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed. |
| decision support and expert systems: Expert Systems for Decision-making Patricia Baird, 1987 Six papers describing how expert systems for decision making will affect organizational decision making and strategy planning. |
| decision support and expert systems: Understanding Decision Support Systems and Expert Systems Efrem G. Mallach, 1998 |
| decision support and expert systems: After the Digital Tornado Kevin Werbach, 2020-07-23 Leading technology scholars examine how networks powered by algorithms are transforming humanity, posing deep questions about power, freedom, and fairness. This title is also available as Open Access on Cambridge Core. |
| decision support and expert systems: Judicial Applications of Artificial Intelligence Giovanni Sartor, L. Karl Branting, 2013-04-17 The judiciary is in the early stages of a transformation in which AI (Artificial Intelligence) technology will help to make the judicial process faster, cheaper, and more predictable without compromising the integrity of judges' discretionary reasoning. Judicial decision-making is an area of daunting complexity, where highly sophisticated legal expertise merges with cognitive and emotional competence. How can AI contribute to a process that encompasses such a wide range of knowledge, judgment, and experience? Rather than aiming at the impossible dream (or nightmare) of building an automatic judge, AI research has had two more practical goals: producing tools to support judicial activities, including programs for intelligent document assembly, case retrieval, and support for discretionary decision-making; and developing new analytical tools for understanding and modeling the judicial process, such as case-based reasoning and formal models of dialectics, argumentation, and negotiation. Judges, squeezed between tightening budgets and increasing demands for justice, are desperately trying to maintain the quality of their decision-making process while coping with time and resource limitations. Flexible AI tools for decision support may promote uniformity and efficiency in judicial practice, while supporting rational judicial discretion. Similarly, AI may promote flexibility, efficiency and accuracy in other judicial tasks, such as drafting various judicial documents. The contributions in this volume exemplify some of the directions that the AI transformation of the judiciary will take. |
| decision support and expert systems: Decision Support Basics Daniel J. Power, 2009-11-01 This book is targeted to busy managers and MBA students who need to grasp the basics of computerized decision support. Some of the topics covered include: What is a DSS? What do managers need to know about computerized decision support? And how can managers identify opportunities to create innovative DSS? Overall the book addresses 35 fundamental questions that are relevant to understanding computerized decision support. |
| decision support and expert systems: The State-of-the-art in Decision Support Systems Gerald W. Hopple, 1988 |
| decision support and expert systems: Industrial and Engineering Applications or Artificial Intelligence and Expert Systems Takushi Tanaka, Moonis Ali, Setsuo Ohsuga, 1997-01-30 This volume includes the proceedings from Proceedings of the Ninth International Conference Fukuoka, Japan, June 4-7, 1996. This work represents a broad spectrum of new ideas in the field of applied artificial intelligence and expert systems, and serves to disseminate information regarding intelligent methodologies and their implementation in solving various problems in industry and engineering. |
| decision support and expert systems: Decision Support Systems Chiang Jao, 2010-01-01 Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference. |
| decision support and expert systems: Evaluating Decision Support and Expert Systems Leonard Adelman, 1992 Decision Support Systems Engineering Andrew P. Sage This practical guide describes the everyday nuts-and-bolts to building a decision support system that unites the concerns of both system designers and users. Beginning with an outline of the generic components of a decision support system, readers are given a technologically rigorous, yet clear, tour of its assembly line basics. Data-base management systems, model-base management systems, and dialog generation and management systems are clearly described, with emphasis on how these make a decision support system feasible and practical. 1991 (0 471-53000-X) 360 pp. Software Systems Engineering Andrew P. Sage and James D. Palmer This unique text provides a thorough introduction to all aspects of the developmental life cycle of software production. For those interested in applying a systems-based approach to software development, Software Systems Engineering discusses key aspects of such an approach—from software quality, software reliability, and development environments, to integration, maintenance, management, and cost analysis. The book’s practical look features a set of tools instrumental to success in each life cycle phase, as well as a taxonomy of methods for making the productivity tools available and subject to wider use. 1990 (0 471-61758-X) 544 pp. Design for Success A Human-Centered Approach to Designing Successful Products and Systems William B. Rouse Drawn from methods tested in a wide array of industries—aviation, the process and power industries, manufacturing, the marine industry, and communications—this important text details how to design products and systems that are market-driven and user-oriented. Using a variety of methods and tools illustrated with case studies, Design for Success outlines a concrete, human-centered approach to the design of complex systems. This new approach to system design includes a look at understanding users’ needs, design and engineering evaluation of product and systems, and more. 1991 (0 471-52483-2) 304 pp. |
| decision support and expert systems: Medical Expert Systems M. K. Chytil, Rolf Engelbrecht, 1987 |
| decision support and expert systems: Introducing Decision Support Systems Paul N. Finlay, 1994 This new edition is updated throughout. In particular there is a new chapter on the human-computer interface and the vital question of measuring the success of decision support systems is given full treatment. Concludes with a discussion of the relationship between expert systems and decision support systems, and a brief look at future developments. Introducing Decision Support Systems is aimed at advanced undergraduate and postgraduate students in schools of management, business studies and computing. It will also be extremely relevant to professionals dealing with decision support systems, e.g. accountants, managers and IT staff. |
| decision support and expert systems: Handbook on Decision Support Systems 2 Frada Burstein, Clyde W. Holsapple, 2008-01-22 As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come. |
DECISION Definition & Meaning - Merriam-Webster
The meaning of DECISION is the act or process of deciding. How to use decision in a sentence.
DECISION | English meaning - Cambridge Dictionary
DECISION definition: 1. a choice that you make about something after thinking about several possibilities: 2. the…. Learn more.
DECISION Definition & Meaning | Dictionary.com
Decision definition: the act or process of deciding; deciding; determination, as of a question or doubt, by making a judgment.. See examples of DECISION used in a sentence.
decision noun - Definition, pictures, pronunciation and usage …
Definition of decision noun in Oxford Advanced American Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Decision - definition of decision by The Free Dictionary
1. the act or process of deciding. 2. the act of making up one's mind: a difficult decision. 3. something that is decided; resolution. 4. a judgment, as one pronounced by a court. 5. the …
What does Decision mean? - Definitions.net
What does Decision mean? This dictionary definitions page includes all the possible meanings, example usage and translations of the word Decision. A choice or judgement. Firmness of …
decision - Wiktionary, the free dictionary
Jun 7, 2025 · (choice or judgment): Most often, to decide something is to make a decision; however, other possibilities exist as well. Many verbs used with destination or conclusion, such …
SUPREME COURT OF THE UNITED STATES
4 days ago · judgment” rule articulated by the Eighth Circuit in its 1982 decision in Monahan, in which the Eighth Circuit reasoned that to prove dis-crimination under the Rehabilitation Act in …
Decision-making - Wikipedia
In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several …
Decision - Definition, Meaning & Synonyms - Vocabulary.com
To make a decision is to make up your mind about something. To act with decision is to proceed with determination, which might be a natural character trait.
DECISION Definition & Meaning - Merriam-Webster
The meaning of DECISION is the act or process of deciding. How to use decision in a sentence.
DECISION | English meaning - Cambridge Dictionary
DECISION definition: 1. a choice that you make about something after thinking about several possibilities: 2. the…. Learn more.
DECISION Definition & Meaning | Dictionary.com
Decision definition: the act or process of deciding; deciding; determination, as of a question or doubt, by making a judgment.. See examples of DECISION used in a sentence.
decision noun - Definition, pictures, pronunciation and usage …
Definition of decision noun in Oxford Advanced American Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Decision - definition of decision by The Free Dictionary
1. the act or process of deciding. 2. the act of making up one's mind: a difficult decision. 3. something that is decided; resolution. 4. a judgment, as one pronounced by a court. 5. the …
What does Decision mean? - Definitions.net
What does Decision mean? This dictionary definitions page includes all the possible meanings, example usage and translations of the word Decision. A choice or judgement. Firmness of …
decision - Wiktionary, the free dictionary
Jun 7, 2025 · (choice or judgment): Most often, to decide something is to make a decision; however, other possibilities exist as well. Many verbs used with destination or conclusion, such …
SUPREME COURT OF THE UNITED STATES
4 days ago · judgment” rule articulated by the Eighth Circuit in its 1982 decision in Monahan, in which the Eighth Circuit reasoned that to prove dis-crimination under the Rehabilitation Act in …
Decision-making - Wikipedia
In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several …
Decision - Definition, Meaning & Synonyms - Vocabulary.com
To make a decision is to make up your mind about something. To act with decision is to proceed with determination, which might be a natural character trait.
