Sensor-Based Decision Making in Uncertain Context

2017 ◽  
pp. 234-257
Author(s):  
Eric Villeneuve ◽  
François Pérès ◽  
Cedrik Beler ◽  
Vicente González-Prida
Keyword(s):  
Decision Making ◽  
Network Architecture ◽  
Measurement Errors ◽  
False Negative ◽  
Decision Makers ◽  
Organizational Network ◽  
Decision Aiding ◽  
External Impact ◽  
Information Collecting ◽  
Embedded Intelligence

Decision makers, whether human or computer, using sensor networks to instrument information collecting necessary for decision, often face difficulties in assessing confidence granted to signals transmitted and received in the network. Several organizational (network architecture or nature, distance between sensors ...), internal (sensor reliability or accuracy ...) or external (impact of environment ...) factors can lead to measurement errors (false alarm, non-detection by misinterpretation of the analyzed signals, false-negative …). A system-embedded intelligence is then necessary, to compare the information received for the purpose of decision aiding based on margin of errors converted in confidence intervals. In this chapter, the authors present four complementary approaches to quantify the interpretation of signals exchanged in a network of sensors in the presence of uncertainty.

Frameworks and Models in Decision-Making and Judgment in Child Welfare and Protection

2020 ◽  
pp. 3-26
Author(s):  
Rami Benbenishty ◽  
John D. Fluke
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Child Welfare ◽  
False Negative ◽  
Real Life ◽  
Decision Makers ◽  
Future Research ◽  
Theoretical Perspectives ◽  
Specificity And Sensitivity ◽  
Predictive Risk

This chapter presents the basic concepts, theoretical perspectives, and areas of scholarship that bear on decisions in child welfare—making choices in decision environments characterized by high levels of uncertainty. The authors distinguish between normative models that predict what decision-makers ought to choose when faced with alternatives and descriptive models that describe how they tend to make these choices in real life. The chapter reviews those challenges that may be especially relevant in the complex context of child welfare and protection. One way in which decision-makers overcome task complexities and limitations in human information processing (bounded rationality) is by using heuristics to navigate complex tasks. The chapter reviews strategies to correct some limitations in judgment. The authors examine the relationships between workers’ predictions of what would be the outcomes of the case and the actual outcomes and describe two types of error (false positive and false negative) and the related concepts of specificity and sensitivity. These issues are followed by a description of the Lens Model and some of its implications for child welfare decision-making, including predictive risk modeling and studies on information processing models. The final section presents current theoretical models in child welfare decision-making and describes Decision-Making Ecology (DME) and Judgments and Decision Processes in Context (JUDPiC). The chapter concludes with suggestions for future research on child welfare decision-making that could contribute to our conceptual understanding and have practical utility as well.

scholarly journals Modeling a satisficing judge

2018 ◽  
Vol 30 (2) ◽  
pp. 220-246
Author(s):  
Christoph Engel ◽  
Werner Gueth
Keyword(s):  
Decision Making ◽  
Rational Choice Theory ◽  
Choice Theory ◽  
False Negative ◽  
Decision Makers ◽  
Judicial Decision ◽  
Judicial Decision Making ◽  
Knowing That ◽  
Course Of Action ◽  
Graphic Illustration

Decision-makers often mean to react to the behavior of others, knowing that they only imperfectly observe them. Rational choice theory posits that they should weigh false positive versus false negative choices, and assess possible outcomes and their probabilities, if necessary, attaching subjective values to them. We argue that this recommendation is not only utterly unrealistic but highly error prone. We contrast it with an approach inspired by satisficing, where the decision-maker contents herself with gauging her confidence in not making too big a mistake by adopting one course of action. We model the competing approaches, using judicial decision-making as a graphic illustration.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

strategi dalam pengambilan keputusan

2019 ◽  
Author(s):  
Suci Handayani Handayani ◽  
Hade Afriansyah
Keyword(s):  
Decision Making ◽  
Imperfect Information ◽  
Economic Value ◽  
Decision Makers ◽  
Decision Making Process ◽  
Administrative Process ◽  
Left Behind ◽  
Information Time ◽  
Complex Matter ◽  
General Individuals

Decision making is one element of economic value, especially in the era of globalization, and if it is not acceptable in the decision making process, we will be left behind. According to Robins, (2003: 173), Salusu, (2000: 47), and Razik and Swanson, (1995: 476) say that decision making can be interpreted as a process of choosing a number of alternatives, how to act in accordance with concepts, or rules in solving problems to achieve individual or group goals that have been formulated using a number of specific techniques, approaches and methods and achieve optimal levels of acceptance.Decision making in organizations whether a decision is made for a person or group, the nature of the decision is often determined by rules, policies, prescribed, instructions that have been derived or practices that apply. To understand decision making within the organization it is useful to view decision making as part of the overall administrative process. In general, individuals tend to use simple strategies, even if in any complex matter, to get the desired solution, because the solution is limited by imperfect information, time and costs, limited thinking and psychological stress experienced by decision makers.

A Soft Hierarchical Process Approach for Decision Making in A Supply Chain

2015 ◽  
Vol 4 (1and2) ◽  
Author(s):  
Rajeev Dhingra ◽  
Preetvanti Singh
Keyword(s):  
Decision Making ◽  
Process Approach ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Conflicting Objectives ◽  
Realistic View ◽  
Hierarchy Process ◽  
Pair Wise Comparison ◽  
Supplier Selection Problem ◽  
Selection Of

Decision problems are usually complex and involve evaluation of several conflicting criteria (parameters). Multi Criteria Decision Making (MCDM) is a promising field that considers the parallel influence of all criteria and aims at helping decision makers in expressing their preferences, over a set of predefined alternatives, on the basis of criteria (parameters) that are contradictory in nature. The Analytic Hierarchy Process (AHP) is a useful and widespread MCDM tool for solving such type of problems, as it allows the incorporation of conflicting objectives and decision makers preferences in the decision making. The AHP utilizes the concept of pair wise comparison to find the order of criteria (parameters) and alternatives. The comparison in a pairwise manner becomes quite tedious and complex for problems having eight alternatives or more, thereby, limiting the application of AHP. This paper presents a soft hierarchical process approach based on soft set decision making which eliminates the least promising candidate alternatives and selects the optimum(potential) ones that results in the significant reduction in the number of pairwise comparisons necessary for the selection of the best alternative using AHP, giving the approach a more realistic view. A supplier selection problem is used to illustrate the proposed approach.

scholarly journals An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Andrea Duggento ◽  
Marco Aiello ◽  
Carlo Cavaliere ◽  
Giuseppe L. Cascella ◽  
Davide Cascella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Architecture ◽  
Ad Hoc ◽  
False Negative ◽  
Selection Criterion ◽  
Current Status ◽  
Clinical Image ◽  
Imaging Data ◽  
Breast Cancer Death ◽  
Random Initialization

Breast cancer is one of the most common cancers in women, with more than 1,300,000 cases and 450,000 deaths each year worldwide. In this context, recent studies showed that early breast cancer detection, along with suitable treatment, could significantly reduce breast cancer death rates in the long term. X-ray mammography is still the instrument of choice in breast cancer screening. In this context, the false-positive and false-negative rates commonly achieved by radiologists are extremely arduous to estimate and control although some authors have estimated figures of up to 20% of total diagnoses or more. The introduction of novel artificial intelligence (AI) technologies applied to the diagnosis and, possibly, prognosis of breast cancer could revolutionize the current status of the management of the breast cancer patient by assisting the radiologist in clinical image interpretation. Lately, a breakthrough in the AI field has been brought about by the introduction of deep learning techniques in general and of convolutional neural networks in particular. Such techniques require no a priori feature space definition from the operator and are able to achieve classification performances which can even surpass human experts. In this paper, we design and validate an ad hoc CNN architecture specialized in breast lesion classification from imaging data only. We explore a total of 260 model architectures in a train-validation-test split in order to propose a model selection criterion which can pose the emphasis on reducing false negatives while still retaining acceptable accuracy. We achieve an area under the receiver operatic characteristics curve of 0.785 (accuracy 71.19%) on the test set, demonstrating how an ad hoc random initialization architecture can and should be fine tuned to a specific problem, especially in biomedical applications.

scholarly journals An Innovative Grey Approach for Group Multi-Criteria Decision Analysis Based on the Median of Ratings by Using Python

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 124
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Florentin Smarandache ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Likert Scale ◽  
Decision Makers ◽  
Interval Numbers ◽  
Multi Criteria Decision Analysis

Some decision-making problems, i.e., multi-criteria decision analysis (MCDA) problems, require taking into account the attitudes of a large number of decision-makers and/or respondents. Therefore, an approach to the transformation of crisp ratings, collected from respondents, in grey interval numbers form based on the median of collected scores, i.e., ratings, is considered in this article. In this way, the simplicity of collecting respondents’ attitudes using crisp values, i.e., by applying some form of Likert scale, is combined with the advantages that can be achieved by using grey interval numbers. In this way, a grey extension of MCDA methods is obtained. The application of the proposed approach was considered in the example of evaluating the websites of tourism organizations by using several MCDA methods. Additionally, an analysis of the application of the proposed approach in the case of a large number of respondents, done in Python, is presented. The advantages of the proposed method, as well as its possible limitations, are summarized.

scholarly journals A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

2021 ◽  
Vol 11 (4) ◽  
pp. 1660 ◽  
Author(s):  
Ivan Marović ◽  
Monika Perić ◽  
Tomaš Hanak
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Project Performance ◽  
Decision Makers ◽  
Construction Project Management ◽  
Analytic Hierarchy ◽  
Conflicting Demands ◽  
Decision Making Problem ◽  
Scientific Approach ◽  
Hierarchy Process

A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.

scholarly journals Trade-Control Compliance in SMEs: Do Decision-Makers and Supply Chain Position Make a Difference?

2021 ◽  
Author(s):  
Christian Hauser
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Behavioral Ethics ◽  
Managerial Decision ◽  
Organizational Responses ◽  
Control Laws ◽  
Compliance Programs ◽  
External Pressures ◽  
Compliance Program ◽  
Trade Control

AbstractIn recent years, trade-control laws and regulations such as embargoes and sanctions have gained importance. However, there is limited empirical research on the ways in which small- and medium-sized enterprises (SMEs) respond to such coercive economic measures. Building on the literature on organizational responses to external demands and behavioral ethics, this study addresses this issue to better understand how external pressures and managerial decision-making are associated with the scope of trade-control compliance programs. Based on a sample of 289 SMEs, the findings show that the organizational responses of SMEs reflect proportionate adjustments to regulatory pressures but only if decision-makers are well informed and aware of the prevailing rules and regulations. Conversely, uninformed decision-making leads to a disproportionate response resulting in an inadequately reduced scope of the compliance program. In addition, the results indicate that SMEs that are highly integrated into supply chains are susceptible to passing-the-buck behavior.

Systems thinking, a consilience of values and logic

2005 ◽  
Vol 24 (4) ◽  
pp. 259-274
Author(s):  
Sameer Kumar ◽  
Thomas Ressler ◽  
Mark Ahrens
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Systems Thinking ◽  
Qualitative Reasoning ◽  
Colleges And Universities ◽  
Decision Makers ◽  
Modern World ◽  
Problem Solving Process ◽  
Problem Solvers

This article is an appeal to incorporate qualitative reasoning into quantitative topics and courses, especially those devoted to decision-making offered in colleges and universities. Students, many of whom join professional workforce, must become more systems thinkers and decision-makers than merely problem-solvers. This will entail discussion of systems thinking, not just reaching “the answer”. Managers will need to formally and forcefully discuss objectives and values at each stage of the problem-solving process – at the start, during the problem-solving stage, and at the interpretation of the results stage – in order to move from problem solving to decision-making. The authors suggest some methods for doing this, and provide examples of why doing so is so important for decision-makers in the modern world.

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