Conferences related to Decision Theory

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

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


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier 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, automatic control, and related areas.


2020 IEEE Frontiers in Education Conference (FIE)

The Frontiers in Education (FIE) Conference is a major international conference focusing on educational innovations and research in engineering and computing education. FIE 2019 continues a long tradition of disseminating results in engineering and computing education. It is an ideal forum for sharing ideas, learning about developments and interacting with colleagues inthese fields.


2020 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 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

All topics related to engineering and technology management, including applicable analytical methods and economical/social/human issues to be considered in making engineering decisions.


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Periodicals related to Decision Theory

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


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, 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, ...


Engineering Management, IEEE Transactions on

Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.


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Most published Xplore authors for Decision Theory

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Xplore Articles related to Decision Theory

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Research on intelligent decision evaluation method for substation based on fuzzy analysis and decision theory

2016 International Conference on Fuzzy Theory and Its Applications (iFuzzy), 2016

According to the current transformer substation, there are a lot of problems, like a variety of complicated information, difficulty of effectively assessing and making decisions based on artificial experience. Therefore, a method of substation intelligent decision evaluation based on fuzzy analysis and decision theory is proposed in this paper. Firstly, all kinds of complex information in substation are classified, and ...


Solving the one-shot decision theory based newsvendor models

2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2015

The one-shot decision theory (OSDT)has been utilized to solve newsvendor models for innovative products. In fact, OSDT based newsvendor models are a special kind of bilevel programming problems. The existing approaches may not be applicable for solving these models because they include nonconvex nonsmooth lower level optimization problems. In this paper, we translate these models into conventional optimization models with ...


The one-shot decision theory based production planning models

2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2016

This paper considers that a company is planning to produce innovative products in an uncertain market environment. We build production planning models with the one-shot decision theory (OSDT) where the optimal production plan is obtained to correspond to some special scenarios. Since the OSDT based production planning model is a bi-level programming problem with a non-smooth lower level program which ...


Work in Progress: Practical Computerized Adaptive Assessment based on Bayesian decision theory

Proceedings. Frontiers in Education. 36th Annual Conference, 2006

This work reports on the development of a novel software tool, namely Module for Adaptive Assessment of Students or MAAS for short, for adaptive multi-user Web-based assessment. The framework of Bayesian decision theory has been used for sequential mastery testing to classify students as masters or non-masters based on their responses to adaptively selected test items. MAAS applies a naive ...


Robust optimization of risk for power system based on information gap decision theory

2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2015

Risk-control optimization has great significance for security of power system. Usually the probabilistic uncertainties of parameters are considered in the research of risk optimization of power system. However, the method of probabilistic uncertainty description will be insufficient in the case of lack of sample data. Thus non-probabilistic uncertainties of parameters should be considered, and will impose a significant influence on ...


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Educational Resources on Decision Theory

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IEEE.tv Videos

Bayesian Perception & Decision from Theory to Real World Applications
Fuzzy and Soft Methods for Multi-Criteria Decision Making - Ronald R Yager - WCCI 2016
Robotics History: Narratives and Networks Oral Histories: Max Mintz
Some Thoughts on a Gap Between Theory and Practice of Evolutionary Algorithms - WCCI 2012
A Conversation with…Toby Walsh: IEEE TechEthics
Q&A with Dr. Maryam Shanechi: IEEE Brain Podcast, Episode 6 Part 1
An Introduction to Computational Intelligence in Multi-Criteria Decision-Making: The Intersection of Search, Preference Tradeoff
What's There To Fear About AI?: IEEE TechEthics Keynote with Toby Walsh
Norbert Wiener in the 21st Century Conference Concept
Fusing Simultaneously Acquired EEG and fMRI to Infer Spatiotemporal Dynamics of Cognition in the Human Brain - IEEE Brain Workshop
Algorithmic Decision Making: Impacts and Implications - IEEE Internet Initiative Webinar
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - David M. Pozar
Ethical Considerations: A Key to Technological Advancement - IEEE TechEthics Virtual Panel
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - Magdalena Salazar Palma
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - Constantine A. Balanis
Inspiring Brilliance: The impact of control theory and cybernetics of Maxwell's paper: On governors
PGX Clinical Decision Support Implementation - Peter Hulick - IEEE EMBS at NIH, 2019
WIE: Our Own Voices - Noel Schulz, Kansas State University
Social Implications: Perils & Promises of AI - IEEE AI & Ethics Summit 2016
IMS 2015: Four scientists who saved Maxwells Theory

IEEE-USA E-Books

  • Research on intelligent decision evaluation method for substation based on fuzzy analysis and decision theory

    According to the current transformer substation, there are a lot of problems, like a variety of complicated information, difficulty of effectively assessing and making decisions based on artificial experience. Therefore, a method of substation intelligent decision evaluation based on fuzzy analysis and decision theory is proposed in this paper. Firstly, all kinds of complex information in substation are classified, and then take the comparison of the importance of the objectives of substation decision-making. Finally, the fuzzy decision theory model is designed with the improved fuzzy analysis decision theory. It was proved by an example that this intelligent decision evaluation method can effectively deal with all kinds of information of substation, and can effectively put forward effective decision-making strategy. Obviously it has a very high practical value.

  • Solving the one-shot decision theory based newsvendor models

    The one-shot decision theory (OSDT)has been utilized to solve newsvendor models for innovative products. In fact, OSDT based newsvendor models are a special kind of bilevel programming problems. The existing approaches may not be applicable for solving these models because they include nonconvex nonsmooth lower level optimization problems. In this paper, we translate these models into conventional optimization models with considering the characteristics of the optimal solutions, which effectively handle the difficulties of the original newsvendor models. The theoretical results are given and a numerical example is used to show the effectiveness of the proposed methods.

  • The one-shot decision theory based production planning models

    This paper considers that a company is planning to produce innovative products in an uncertain market environment. We build production planning models with the one-shot decision theory (OSDT) where the optimal production plan is obtained to correspond to some special scenarios. Since the OSDT based production planning model is a bi-level programming problem with a non-smooth lower level program which is difficult to be solved, we propose an efficient method with considering a smooth approximation function to solve it.

  • Work in Progress: Practical Computerized Adaptive Assessment based on Bayesian decision theory

    This work reports on the development of a novel software tool, namely Module for Adaptive Assessment of Students or MAAS for short, for adaptive multi-user Web-based assessment. The framework of Bayesian decision theory has been used for sequential mastery testing to classify students as masters or non-masters based on their responses to adaptively selected test items. MAAS applies a naive Bayesian decision model to adaptive testing, assuming many levels of student performance and taking into account not only right/wrong, but also blank answers. MAAS is embedded in a software platform, namely Platform for Adaptive and Reliable Evaluation of Students or PARES. MAAS is currently in a pilot use both for formative assessment and self-assessment. A preliminary experiment of using MAAS under real world conditions is described

  • Robust optimization of risk for power system based on information gap decision theory

    Risk-control optimization has great significance for security of power system. Usually the probabilistic uncertainties of parameters are considered in the research of risk optimization of power system. However, the method of probabilistic uncertainty description will be insufficient in the case of lack of sample data. Thus non-probabilistic uncertainties of parameters should be considered, and will impose a significant influence on the results of optimization. To solve this problem, a robust optimization operation method of power system risk-control is presented in this paper, considering the non- probabilistic uncertainty of parameters based on information gap decision theory (IGDT). In the method, loads are modeled as the non-probabilistic uncertainty parameters, and the model of robust optimization operation of risk-control is presented. By solving the model, the maximum fluctuation of the pre-specified target can be obtained, and the strategy of this situation can be obtained at the same time. The proposed model is applied to the IEEE-30 system of risk-control by simulation. The results can provide the valuable information for operating department to risk management.

  • Robust Team Decision Theory

    This technical note considers linear quadratic team decision problems. It shows that linear decisions are optimal and can be found by solving a linear matrix inequality.

  • Rough Cluster Quality Index Based on Decision Theory

    Quality of clustering is an important issue in application of clustering techniques. Most traditional cluster validity indices are geometry-based cluster quality measures. This paper proposes a cluster validity index based on the decision-theoretic rough set model by considering various loss functions. Experiments with synthetic, standard, and real-world retail data show the usefulness of the proposed validity index for the evaluation of rough and crisp clustering. The measure is shown to help determine optimal number of clusters, as well as an important parameter called threshold in rough clustering. The experiments with a promotional campaign for the retail data illustrate the ability of the proposed measure to incorporate financial considerations in evaluating quality of a clustering scheme. This ability to deal with monetary values distinguishes the proposed decision-theoretic measure from other distance-based measures. The proposed validity index can also be extended for evaluating other clustering algorithms such as fuzzy clustering.

  • A multimodal biometric system coupling iris recognition and speaker identification systems through decision theory

    Using the energy compaction and time frequency resolution of wavelet analysis, the paper proposes to develop a multimodal biometric system that combines iris recognition and speaker identification systems. The uniqueness of iris pattern and the robustness of speaker identification based on pitch period estimation complement each other in the proposed system. The paper also critically analyzes the implementation of Daubechies wavelets (Db3 and Db4) in the analysis of iris and speech samples with an endeavor to have a high success rate with optimal computational complexity.

  • Watermark detection algorithm using statistical decision theory

    Watermark detection plays a crucial role in multimedia copyright protection and has traditionally been tackled using correlation-based algorithms. However, correlation-based detection is not actually the best choice, as it does not utilize the distributional characteristics of the image being marked. Accordingly, an efficient watermark detection scheme for DWT coefficients is proposed as optimal for non-additive schemes. Based on the statistical decision theory, the proposed method is derived according to Bayes' decision theory, the Neyman-Pearson criterion, and the distribution of the DWT coefficients, thereby minimizing the missed detection probability subject to a given false alarm probability. The proposed method has been tested in the context of robustness, and the results confirm the superiority of the proposed technique over conventional correlation-based detection methods.

  • A class of distortionless codes designed by Bayes decision theory

    The problem of distortionless encoding when the parameters of the probabilistic model of a source are unknown is considered from a statistical decision theory point of view. A class of predictive and nonpredictive codes is proposed that are optimal within this framework. Specifically, it is shown that the codeword length of the proposed predictive code coincides with that of the proposed nonpredictive code for any source sequence. A bound for the redundancy for universal coding is given in terms of the supremum of the Bayes risk. If this supremum exists, then there exists a minimax code whose mean code length approaches it in the proposed class of codes, and the minimax code is given by the Bayes solution relative to the prior distribution of the source parameters that maximizes the Bayes risk.<<ETX>>



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