Results 21 to 30 of about 434,779 (289)
Minimizing Driving Risk of Mobile Robots by Combining a Goal Guidance Vector Algorithm with Reactive Navigation [PDF]
한국정밀공학회지, 2021 In the navigation of mobile robots, the driving risk can be minimized by increasing the probability of success. The algorithm, which is currently commonly known as the shortest path algorithm, performs efficiently, but does not exhibit a good probability
Keun Ha Choi, SooHyun Kim
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Alexandria Engineering Journal, 2023 Probabilistic dual hesitant fuzzy set (PDHFS) can better reflect the hesitant attitude and probability information of decision-makers than existing fuzzy sets.
Baoquan Ning +3 more
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Lubricants, 2022 Information such as probability distribution, performance degradation trajectory, and performance reliability function varies with the service status of rolling bearings, which is difficult to analyze and evaluate using traditional reliability theory ...
Liang Ye +5 more
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On a derivation of the Goldstein–Einhorn probability weighting functions [PDF]
Aequationes mathematicae, 2020 AbstractThe well known Goldstein–Einhorn probability weighting functions have been characterized by Gonzalez and Wu using the linear in log odds preference condition. We provide an alternative way of deriving this class of functions. It is based on the concept of indifference prices.
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A shocking experiment: New evidence on probability weighting and common ratio violations
Judgment and Decision Making, 2007 We study whether probability weighting is observed when individuals are presented with a series of choices between lotteries consisting of real non-monetary adverse outcomes, electric shocks.
Gregory S. Berns +3 more
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Technological and Economic Development of Economy, 2023 Probabilistic dual hesitant fuzzy set (PDHFS) is a more powerful and important tool to describe uncertain information regarded as generalization of hesitant fuzzy set (HFS) and dual HFS (DHFS), not only reflects the hesitant attitude of decision-makers (
Baoquan Ning +3 more
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Probability weighting and insurance demand in a unified framework
The Geneva Risk and Insurance Review, 2022 We provide a comprehensive analysis of the impact of probability weighting on optimal insurance demand in a unified framework. We identify decreasing relative overweighting as a new local condition on the probability weighting function that is useful for
J. Jaspersen, R. Peter, Marc A. Ragin
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Nonlinear Probability Weighting Can Reflect Attentional Biases in Sequential Sampling
Annual Meeting of the Cognitive Science Society, 2021 Nonlinear probability weighting allows cumulative prospect theory (CPT) to account for key phenomena in decision making under risk (e.g., certainty effect, fourfold pattern of risk attitudes).
Veronika Zilker, Thorsten Pachur
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A Decision Probability Transformation Method Based on the Neural Network
Entropy, 2022 When the Dempster–Shafer evidence theory is applied to the field of information fusion, how to reasonably transform the basic probability assignment (BPA) into probability to improve decision-making efficiency has been a key challenge.
Junwei Li, Aoxiang Zhao, Huanyu Liu
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Second-best probability weighting
Games Econ. Behav., 2022 Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist?
Florian Herold, N. Netzer
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