Knowledge acquisition and decision making based on Bayes risk minimization method

2018 ◽  
Vol 49 (2) ◽  
pp. 804-818 ◽  
Author(s):  
Mingliang Suo ◽  
Zhiping Zhang ◽  
Ying Chen ◽  
Ruoming An ◽  
Shunli Li
Keyword(s):  
Decision Making ◽  
Knowledge Acquisition ◽  
Bayes Risk ◽  
Risk Minimization ◽  
Minimization Method

scholarly journals Introducing Decision Free Solutions - A Generic, Systemic Approach to Minimize Risk by Avoiding Decision Making

2016 ◽  
Vol 8 (2) ◽  
pp. 102
Author(s):  
Jorn Verweij
Keyword(s):  
Decision Making ◽  
Measurement Theory ◽  
Systemic Approach ◽  
Risk Minimization ◽  
Minimization Method ◽  
Information Measurement ◽  
The Core ◽  
Best Value ◽  
Procurement System ◽  
Consistent Application

“Decision Free Solutions” (DFS) is a generic, systemic approach to minimize risk in achieving an aim by avoiding decision making. Applying DFS will benefit those who have an aim, and those who have expertise. DFS is based on Information Measurement Theory (IMT) and the Kashiwagi Solution Model (KSM), and is congruous with the Best Value Approach (BVA). Despite BVA being an approach aimed at utilizing expertise (and thereby minimizing risk), and not a procurement system, BVA and its applications are very much intertwined with procurement. This makes it challenging to apply BVA to other fields. Establish a generic, systemic approach to implement the technologies of IMT/KSM in any field. Analyzing existing BVA and IMT/KSM documentation, identify the logic and the principles by which expertise is utilized. Define a generic, systemic approach to minimize risk and demonstrate it by applying it to a field other than procurement. Avoiding all types of decision making was identified as the core principle to ensure the utilization of expertise. An approach consisting out of four steps (labelled DICE) and the consistent application of five principles (labelled TONNNO) has been proposed. The approach has been applied to the field of Lean. A generic and systemic approach to minimize risk by avoiding decision making has been introduced which can be applied in any field. It has been applied in Lean, where it addresses several of Lean’s weaknesses as perceived in practice and where it was demonstrated to reduce the risk of project failure. DFS can be considered a risk minimization method to which risk management is integral. DFS makes expertise matter.

New Method of Knowledge Acquisition of Aid Decision-Making for Missile-Launching

2014 ◽  
Vol 1006-1007 ◽  
pp. 685-688
Author(s):  
Guo Bao Ding ◽  
Hao Xing ◽  
Lian Bing Wang ◽  
Dan Li
Keyword(s):  
Decision Making ◽  
Knowledge Acquisition ◽  
Power Supply System ◽  
Supply System ◽  
Pulse Power Supply ◽  
Causal Knowledge ◽  
Diagram Method ◽  
New Knowledge ◽  
Knowledge Acquisition Methods ◽  
Aid Decision

Acquiring causal knowledge of abnormity is essential to Missile-Launching reliably. There are lots of Knowledge Acquisition methods. But it is absence for usage and maintenance support process. So it is necessary to start the research on new knowledge acquisition technology of aid Decision-Making for Missile-Launching. Based on the Usage and Maintenance-Support Process, this thesis acquires knowledge with the ESD and CESD (Converse Event Sequence Diagram) method. First, this thesis gives the concept of CESD. Then, in order to adapt the CESD model of the complex systems more effectively, this paper expands the CESD framework and provides a software frame of computer aided ESD study. Finally, the operation of pulse power supply system is analyzed on the basis of the improved ESD and CESD. This sample shows the applicability of ESD and CESD methodology in knowledge acquisition technology of aid Decision-Making for Missile-Launching.

scholarly journals Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making

2017 ◽  
Vol 37 (5) ◽  
pp. 512-522
Author(s):  
Laura A. Hatfield ◽  
Christine M. Baugh ◽  
Vanessa Azzone ◽  
Sharon-Lise T. Normand
Keyword(s):  
Decision Making ◽  
Medical Device ◽  
Hierarchical Modeling ◽  
Loss Functions ◽  
Safety Signal ◽  
Theoretic Approach ◽  
Z Score ◽  
Bayes Risk ◽  
Decision Theoretic Approach ◽  
Safety Signals

Background. Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. Objective. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. Methods. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. Results. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score–based decisions, even when the loss functions or hierarchical models are misspecified. Limitations. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. Conclusions. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

On the Behavior-Based Risk Communication Models in Crisis Management and Social Risks Minimization

2020 ◽  
Vol 10 (2) ◽  
pp. 27-45
Author(s):  
Yuriy V. Kostyuchenko ◽  
Viktor Pushkar ◽  
Olga Malysheva ◽  
Maxim Yuschenko
Keyword(s):  
Decision Making ◽  
Crisis Management ◽  
Management Practices ◽  
Formal Model ◽  
Future Research ◽  
Communication Model ◽  
Risk Minimization ◽  
Social Risks ◽  
Assessment Approach ◽  
Future Research Directions

The article formulates and calibrates a formal model of risk communications in the framework of a risk-based community resilience assessment approach in transforming societies under crises and conflicts. It was demonstrated that perception of risks is not adequate. This situation is recognized as a threat, which leads to a significant increase of losses and to spreading of wrong crisis management practices. To improve decision-making at the personal, group, and population levels, a behavioral-based communication model has been proposed. The modified form of engagement into collective actions for substantially fractionalized society is proposed. A number of models of action calls and a collective decision-making under stress conditions with dynamic communication are put forward. On the basis of the developed model, ways of optimizing communication strategies are aimed at corresponding risk minimization are developed. Future research directions are highlighted.

Local Bayes Risk Minimization Based Stopping Strategy for Hierarchical Classification

2017 ◽  
Author(s):  
Yu Wang ◽  
Qinghua Hu ◽  
Yucan Zhou ◽  
Hong Zhao ◽  
Yuhua Qian ◽  
...  
Keyword(s):  
Hierarchical Classification ◽  
Bayes Risk ◽  
Risk Minimization

A Multi Autonomic Objects Flexible Workflow and its Knowledge Acquisition Supporting Engineering Design Process

2010 ◽  
Vol 97-101 ◽  
pp. 3341-3344
Author(s):  
Dong Bo Wang ◽  
Xiu Tian Yan ◽  
Ning Sheng Guo ◽  
Tao Li
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Literature Review ◽  
Knowledge Acquisition ◽  
Engineering Design ◽  
Design Process ◽  
Design Activity ◽  
Learning Method ◽  
Matlab Simulation ◽  
Engineering Design Process

In order to support the dynamic and creative Engineering Design Process (EDP) comprehensively, after a detailed literature review, a multi autonomic objects (AO) flexible workflow is applied into the supporting and management of EDP, its support for decision making, EDP evolution and design activity granularity is explained, finally and most importantly, a genetic algorithm-based AO knowledge learning method is proposed, the algorithm is demonstrated by a MATLAB simulation that it can satisfy the knowledge acquisition in EDP satisfactorily.

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