Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
Uncertainty: Overview00:59

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Decision Making01:20

Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor 't,' or...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Reliability-integrated multi-objective optimization of offshore oil spill mechanical recovery and oily wastewater management.

Marine pollution bulletin·2026
Same author

Assessment of emerging onboard wastewater decanting technologies for sustainable marine oil spill response: A life cycle thinking perspective.

Marine pollution bulletin·2026
Same author

Coupling generative and predictive machine learning algorithms to enhance haloacetonitriles prediction in small water systems.

Journal of hazardous materials·2026
Same author

Implementing and evaluating a low-carbon, high-quality perioperative patient warming pathway.

BMJ quality & safety·2026
Same author

Dynamic graph learning framework based seasonal and trend decomposition approach for potato crop evapotranspiration prediction.

Scientific reports·2025
Same author

ConvNet-Generated Adversarial Perturbations for Evaluating 3D Object Detection Robustness.

Sensors (Basel, Switzerland)·2025

Related Experiment Video

Updated: Jun 17, 2026

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Decision making under uncertainty--an example for seismic risk management.

Solomon Tesfamariam1, Rehan Sadiq, Homayoun Najjaran

  • 1School of Engineering, The University of British Columbia, Okanagan, Kelowna, BC, Canada. Solomon.tesfamariam@ubc.ca

Risk Analysis : an Official Publication of the Society for Risk Analysis
|January 9, 2010
PubMed
Summary

This study enhances multicriteria decision-making (MCDM) by incorporating expert credibility and fuzzy utilities for uncertain scenarios. The new framework improves decision accuracy in complex risk management, like seismic assessments.

Related Experiment Videos

Last Updated: Jun 17, 2026

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Area of Science:

  • Decision Sciences
  • Risk Management
  • Fuzzy Logic

Background:

  • Multicriteria decision-making (MCDM) is essential for selecting optimal alternatives with conflicting criteria.
  • Incorporating uncertainty is crucial for robust decision-making processes in real-world applications.
  • Existing MCDM frameworks often lack comprehensive methods for handling multiple decision-makers and uncertain payoffs.

Purpose of the Study:

  • To extend Yager's MCDM framework to accommodate multiple decision-makers and fuzzy utilities.
  • To introduce and integrate the concept of an expert credibility factor into the decision-making process.
  • To provide a practical methodology for applying the enhanced MCDM approach to seismic risk management.

Main Methods:

  • Extension of Yager's MCDM framework.
  • Integration of fuzzy set theory for representing uncertain payoffs (utilities).
  • Introduction and application of an expert credibility factor.
  • Demonstration using a heuristic hierarchical structure for seismic risk assessment.

Main Results:

  • A novel MCDM framework capable of handling multiple decision-makers and fuzzy utilities under uncertainty.
  • Quantification of expert credibility to weigh their inputs effectively.
  • Successful application of the proposed method to a seismic risk management example.
  • Step-by-step illustration using a hypothetical case study involving a three-story reinforced concrete building.

Conclusions:

  • The proposed extended MCDM framework effectively addresses uncertainties and multiple stakeholders in decision-making.
  • The inclusion of expert credibility enhances the reliability of decisions in complex scenarios like seismic risk assessment.
  • The methodology offers a valuable tool for improving the robustness and accuracy of decisions in engineering and risk management.