kaleoyster / decision-tree-nbi

This project contains an implementation of a decision tree model for maintenance and deterioration

🌉 Predicting Bridge Maintenance Using Decision Trees 🌟

The repository is implementation of prediction models to identify future bridge deterioration and maintenance using the existing National Bridge Inventory (NBI) dataset. This project is a part of the Bridging Big Data Group and SMARTI at University of Nebraska, Omaha.

[Interactive visualization of Results by Ashley Ramsay](https://repairs.ricks.io/)

🎯 Background

• Bridges are critical infrastructure whose maintenance is a key responsibility for both government and private organizations.
• Costly to build and repair, bridges are valuable assets that can benefit from improved predictive maintenance.
• In this work, we present a novel, straightforward, non-parametric method for doing predicting future maintenance and identifying influential factors to predict future maintenances of the bridges.

💪 Challenge

• In the NBI dataset, it is a challenge to identify maintenance patterns. Because, the reconstruction_year does not provide an valuable information about the type of repair or reconstruction done.
• Moreover, for every bridge time-line, the improvement in the condition ratings often does not map with the data in reconstruction_year.

🎯 Objective

• The objective of this research study is to develop a methodology for computing bridge maintenance frequency and based on existing timelines of the available data predict future time-line by accounting for improvement in the condition ratings.

🧪 Solution

• To address this challenge we can use bridge intervention matrix, that utilizes the bridge intervention matrix for deck to identify various types of intervention depending on the probability of the transition.

• The project contains several models which are broadly specified under two categories:
  • Deterioration models: In general, deterioration models predict the future deterioration of bridge conditions.
  • Maintenance models: In general, maintenance model predict the future maintenance of bridge conditions. There are three main components for which maintenance models can make predicitons:
    1. Substructure
    2. Superstructure
    3. Deck

👉 References

Document	Documentation type	Description
Quickstart	Concept	An overview and guide to setup this project
Methodology	Concept, Task	Simplest possible method of implementing your API
Functions	Reference	List of references for the functions used
Related Projects	Reference	List of projects related to this repository

Contact

• Akshay Kale - Email

decision-tree-nbi's Issues

Issue 1

file not working
line 57 (file.py)