Related Experiment Video
Updated: Jan 22, 2026
08:53
Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
5.5K
Quantifying Community Resilience Using Hierarchical Bayesian Kernel Methods: A Case Study on Recovery from Power
Jin-Zhu Yu1, Hiba Baroud1,2
1Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA.
Summary
Accurately measuring community recovery after disasters is crucial. A new hierarchical Bayesian kernel model (HBKM) effectively predicts recovery rates from power outages, even with limited data, aiding disaster response.
Area of Science:
- Disaster Management
- Infrastructure Resilience
- Statistical Modeling
Background:
- Accurate assessment of community recovery post-disaster is vital for effective response and resource allocation.
- Limited availability of recorded community recovery data presents a significant challenge in quantifying recovery rates.
- Understanding community resilience is key to optimizing infrastructure restoration efforts.
Purpose of the Study:
- To develop a novel method for predicting community recovery rates from power outages following disasters.
- To address the challenge of data scarcity in measuring community recovery.
- To enhance decision-making processes for disaster response and infrastructure management.
Main Methods:
- Development of a hierarchical Bayesian kernel model (HBKM) for predicting community recovery rates.
- Evaluation of HBKM performance using cross-validation.
- Comparison of HBKM with hierarchical Bayesian regression and Poisson generalized linear models.
- Case study in Shelby County, Tennessee, analyzing storm-related power outage recovery (2007-2017).
Main Results:
- The proposed HBKM demonstrated superior predictive accuracy compared to benchmark models.
- HBKM achieved the highest average out-of-sample predictive accuracy.
- Log-likelihood and root mean squared error were used to evaluate predictive accuracy.
Conclusions:
- The HBKM provides a robust approach for assessing community recoverability, particularly in data-scarce environments.
- This method can inform critical decision-making for disaster management and infrastructure restoration.
- Accurate community resilience measures can lead to reduced infrastructure restoration costs.
Keywords:
Community resiliencehierarchical Bayesian kernel modelpower outagepredictive accuracystochastic dominanceMore Related Videos
12:22Mindfulness in Motion MIM: An Onsite Mindfulness Based Intervention MBI for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement
Published on: July 1, 2015
24.4K
05:28Versatile Technique to Produce a Hierarchical Design in Nanoporous Gold
Published on: February 10, 2023
2.1K
Related Concept Videos
00:30What are Populations and Communities?
37.3K
Overview
37.3K
01:08Power
12.9K
The concept of work involves force and displacement; meanwhile, the work-energy theorem relates the net work done on a body to the difference in its kinetic energy, calculated between two points on its trajectory. While none of these quantities or relations involves time explicitly, we know that the time available to accomplish work is often just as important as the amount of work itself. For example, sprinters in a race may have achieved the same velocity at the finish, therefore,...
12.9K
02:30Quantifying Work
24.2K
As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.
24.2K
01:22Sums of Power
63
In definite integration, Riemann sums approximate the area under a curve by dividing it into subintervals and summing the areas of rectangles. When these approximations follow predictable numerical patterns, such as arithmetic or polynomial sequences, sum formulas offer a more efficient and accurate way to compute the result. In particular, the sum of consecutive integers, squares, and cubes plays an essential role in simplifying these calculations, especially when dealing with uniform...
63
01:22Instantaneous Power
887
Instantaneous power is important in electrical circuits, mainly when dealing with sinusoidal input. Instantaneous power, denoted as p(t), results from the multiplication of the instantaneous voltage (v(t)) across an element and the instantaneous current (i(t)) flowing through it. This relationship adheres to the passive sign convention and represents a fundamental principle in electrical engineering.
887
01:14Complex Power
881
Power engineers have introduced the concept of complex power to determine the cumulative effect of parallel loads. This idea plays a crucial role in power analysis because it encompasses all the details related to the power consumed by a specific load.
Complex power is defined as the multiplication of the voltage and the complex conjugate of the current. The magnitude of this power, known as apparent power, is measured in volt-amperes (VA). Notably, the angle of the complex power equates to the...
Complex power is defined as the multiplication of the voltage and the complex conjugate of the current. The magnitude of this power, known as apparent power, is measured in volt-amperes (VA). Notably, the angle of the complex power equates to the...
881