Conferences related to Decision Making

Back to Top

2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

The scope of the 2020 IEEE/ASME AIM includes the following topics: Actuators, Automotive Systems, Bioengineering, Data Storage Systems, Electronic Packaging, Fault Diagnosis, Human-Machine Interfaces, Industry Applications, Information Technology, Intelligent Systems, Machine Vision, Manufacturing, Micro-Electro-Mechanical Systems, Micro/Nano Technology, Modeling and Design, System Identification and Adaptive Control, Motion Control, Vibration and Noise Control, Neural and Fuzzy Control, Opto-Electronic Systems, Optomechatronics, Prototyping, Real-Time and Hardware-in-the-Loop Simulation, Robotics, Sensors, System Integration, Transportation Systems, Smart Materials and Structures, Energy Harvesting and other frontier fields.


2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore


2019 IEEE 17th International Conference on Industrial Informatics (INDIN)

Industrial information technologies


2019 IEEE 58th Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).


2019 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2019, the 26th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


More Conferences

Periodicals related to Decision Making

Back to Top

Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Computer Graphics and Applications, IEEE

IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...


More Periodicals

Most published Xplore authors for Decision Making

Back to Top

Xplore Articles related to Decision Making

Back to Top

Multi-criterial Decision-Making and the Cognitive Architecture of Problem Solving

[{u'author_order': 1, u'affiliation': u'Fellow, IEEE, Professor Emeritus of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210 USA. phone 614-292-0923, e-mail: chandra@cse.ohio-state.edu.edu', u'authorUrl': u'https://ieeexplore.ieee.org/author/37943740400', u'full_name': u'B. Chandrasekaran', u'id': 37943740400}] 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, 2007

Summary form only given. Rational decision-making is often modeled as choosing the alternative that maximizes utility for the decision maker. Over the last few decades, much evidence has been produced to demonstrate that human decision-making is subject to irrationalities, such as intransitivity and framing biases. The author seeks an explanation for how these irrationalities arise, specifically, how they relate to ...


Deriving a Ranking From Hesitant Fuzzy Preference Relations Under Group Decision Making

[{u'author_order': 1, u'affiliation': u'School of Economics and Management, Southeast University, Nanjing, China', u'full_name': u'Bin Zhu'}, {u'author_order': 2, u'affiliation': u'Uncertainty Decision-making Laboratory, Sichuan University, Chengdu, Sichuan, China', u'full_name': u'Zeshui Xu'}, {u'author_order': 3, u'affiliation': u'Uncertainty Decision-making Laboratory, Sichuan University, Chengdu, Sichuan, China', u'full_name': u'Jiuping Xu'}] IEEE Transactions on Cybernetics, 2014

In this paper, we explore the ranking methods with hesitant fuzzy preference relations (HFPRs) in the group decision making environments. As basic elements of hesitant fuzzy sets, hesitant fuzzy elements (HFEs) usually have different numbers of possible values. In order to compute or compare HFEs, we have two principles to normalize them, i.e., the α-normalization and the β-normalization. Based on ...


Multi-Criteria Decision-Making: The Intersection of Search, Preference Tradeoff, and Interaction Visualization Processes

[{u'author_order': 1, u'affiliation': u'Fellow, IEEE, Coolidge Fellow at General Electric Global Research, in Niskayuna, NY 12309, USA email: bonissone@crd.ge.com', u'authorUrl': u'https://ieeexplore.ieee.org/author/37271568900', u'full_name': u'Piero P. Bonissone', u'id': 37271568900}] 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, 2007

Summary form only given. The goal of the First IEEE Symposium of Computational Intelligence in Multicriteria Decision Making (MCDM 2007) is to provide a common forum for three scientific communities that have addressed different aspects of the MCDM problem and provided complementary approaches to its solution. The first approach is the search process over the space of possible solutions. We ...


An Agent Formal Model for Autonomous Decision-Making

[{u'author_order': 1, u'full_name': u'Linjin Wu'}, {u'author_order': 2, u'full_name': u'Dongying Wu'}, {u'author_order': 3, u'full_name': u'Jiayong Chen'}, {u'author_order': 4, u'full_name': u'Wenxiong Li'}] 2012 Fourth International Conference on Multimedia Information Networking and Security, 2012

With the development of artificial intelligence, agent is widely applied to the intelligent system. As the intelligent decision at a higher sense, autonomous decision-making directly affects the intelligent level of intelligent system. In order to improve autonomous decision-making ability of intelligent system, the paper aims to use formal method to research on the process of autonomous decision-making. Combining the feature ...


A New Method for Triangular Fuzzy Number Multiple Attribute Decision Making

[{u'author_order': 1, u'affiliation': u'Mathematics and Information Science College, Guangxi University, Nanning 530004, Guangxi, P. R. China. Email: qinjuying@126.com', u'authorUrl': u'https://ieeexplore.ieee.org/author/37944991500', u'full_name': u'Qin Juying', u'id': 37944991500}, {u'author_order': 2, u'affiliation': u'Mathematics and Information Science College, Guangxi University, Nanning 530004, Guangxi, P. R. China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37944992000', u'full_name': u'Meng Fanyong', u'id': 37944992000}, {u'author_order': 3, u'affiliation': u'Mathematics and Information Science College, Guangxi University, Nanning 530004, Guangxi, P. R. China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37944997100', u'full_name': u'Zeng Xuelan', u'id': 37944997100}] 2007 Chinese Control Conference, 2007

On the basis of the new distance formula for triangular fuzzy numbers given by the paper, a priority method for triangular fuzzy numbers multiple attribute decision making is given. A new assembly method and decision method are given for triangular fuzzy numbers multiple attribute group decision-making. Finally, a numerical example is given to show its effectiveness and practicability.


More Xplore Articles

Educational Resources on Decision Making

Back to Top

eLearning

No eLearning Articles are currently tagged "Decision Making"

IEEE-USA E-Books

  • Framing Privacy in Digital Collections with Ethical Decision Making

    As digital collections continue to grow, the underlying technologies to serve up content also continue to expand and develop. As such, new challenges are presented whichcontinue to test ethical ideologies in everyday environs of the practitioner. There are currently no solid guidelines or overarching codes of ethics to address such issues. The digitization of modern archival collections, in particular, presents interesting conundrums when factors of privacy are weighed and reviewed in both small and mass digitization initiatives. Ethical decision making needs to be present at the onset of project planning in digital projects of all sizes, and we also need to identify the role and responsibility of the practitioner to make more virtuous decisions on behalf of those with no voice or awareness of potential privacy breaches. In this book, notions of what constitutes private information are discussed, as is the potential presence of such information in both analog and digital collections. This book lays groundwork to introduce the topic of privacy within digital collections by providing some examples from documented real- world scenarios and making recommendations for future research. A discussion of the notion privacy as concept will be included, as well as some historical perspective (with perhaps one the most cited work on this topic, for example, Warren and Brandeis' "Right to Privacy," 1890). Concepts from the The Right to Be Forgotten case in 2014 (Google Spain SL, Google Inc. v Agencia Española de Protección de Datos, Mario Costeja González) are discussed as to how some lessons may be drawn from the response in Europe and also how European data privacy laws have been applied. The European ideologies are contrasted with the Right to Free Speech in the First Amendment in the U.S., highlighting the complexities in setting guidelines and practices revolving around privacy issues when applied to real life scenarios. Two ethical theories are explored: Consequentialism and Deontological. Finally, ethical decision making models will also be applied to our framework of digital collections. Three case studies are presented to illustrate how privacy can be defined within digital collections in some real-world examples.

  • Interactive Sensing and Decision Making in Social Networks

    The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks have witnessed significant progress in the electrical engineering, computer science, economics, finance, and sociology research communities. Research in this area involves the interaction of dynamic random graphs, socio-economic analysis, and statistical inference algorithms. Interactive Sensing and Decision Making in Social Networks provides a survey, tutorial development, and discussion of four highly stylized examples of sensing and decision making in social networks: social learning for interactive sensing; tracking the degree distribution of social networks; sensing and information diffusion; and coordination of decision making via game-theoretic learning. Each of the four examples is motivated by practical examples, and comprises of a literature survey together with careful problem formulation and mathematical analysis. Despite being highly stylized, these examples provide a rich variety of models, algorithms and analysis tools that are readily accessible to a signal processing, control/systems theory, and applied mathematics audience

  • Predicting Human Decision-Making: From Prediction to Action

    Human decision-making often transcends our formal models of "rationality." Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.

  • Decision Making Under Uncertainty

    This chapter contains sections titled: Half Title, MIT Lincoln Laboratory Series, Title, Copyright, Dedication, Table of Contents, Preface, About the Authors, Acknowledgments

  • Learning and Decision-Making from Rank Data

    The ubiquitous challenge of learning and decision-making from rank data arises in situations where intelligent systems collect preference and behavior data from humans, learn from the data, and then use the data to help humans make efficient, effective, and timely decisions. Often, such data are represented by rankings. This book surveys some recent progress toward addressing the challenge from the considerations of statistics, computation, and socio-economics. We will cover classical statistical models for rank data, including random utility models, distance-based models, and mixture models. We will discuss and compare classical and state of-the-art algorithms, such as algorithms based on Minorize-Majorization (MM), Expectation-Maximization (EM), Generalized Method- of-Moments (GMM), rank breaking, and tensor decomposition. We will also introduce principled Bayesian preference elicitation frameworks for collecting rank data. Finally, we will examine socio-economic aspects of statistically desirable decision-making mechanisms, such as Bayesian estimators. This book can be useful in three ways: (1) for theoreticians in statistics and machine learning to better understand the considerations and caveats of learning from rank data, compared to learning from other types of data, especially cardinal data; (2) for practitioners to apply algorithms covered by the book for sampling, learning, and aggregation; and (3) as a textbook for graduate students or advanced undergraduate students to learn about the field. This book requires that the reader has basic knowledge in probability, statistics, and algorithms. Knowledge in social choice would also help but is not required.

  • Data Mining and Market Intelligence: Implications for Decision Making

    This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to inspire and inform readers on how to conduct market intelligence by leveraging data and technology, supporting smart decision making. The book explains some suitable methodologies for data analysis that are based on robust statistical methods. For illustrative purposes, the author uses real-life data for all the examples in this book. In addition, the book discusses the concepts, techniques, and applications of digital media and mobile data mining. Hence, this book is a guide tool for policy makers, academics, and practitioners whose areas of interest are statistical inference, applied statistics, applied mathematics, business mathematics, quantitative techniques, and economic and social statistics.

  • Probabilistic Models

    Rational decision making requires reasoning about one's uncertainty and objectives. This chapter focuses on the representation of uncertainty as a probability distribution. Real-world problems require reasoning about distributions over many different variables. We will discuss how to construct these models and how to use them to make inferences.

  • 2003-01-2261 Obstacle State Estimation For Imminent Crash Prediction & Countermeasure Deployment Decision-Making

    None

  • Sequential Decision Making

    None

  • Louder Voices and the International Debate on Developing Country Participation in ICT Decision Making

    This chapter contains sections titled: Mapping the International ICT Decision- Making Universe, Assessing the Impact of Developing Countries in International Decision Making, Obstacles to Developing Country Participation, The Louder Voices Program of Action, The Louder Voices Recommendations, Conclusions and Recommendations, Notes, References



Standards related to Decision Making

Back to Top

No standards are currently tagged "Decision Making"


Jobs related to Decision Making

Back to Top