Surface Ship Safety Predictive Analysis

Abstract

This research seeks to find root causes of Class A or B mishaps in Navy surface ships in order to identify ships at risk for future mishaps. Additionally, by looking at data from ships that experienced mishaps between 2012 and 2017, and by searching beyond the root cause of specific causal factors for these incidents, we may be able to determine if indicator variables could have predicted the ships were at risk. We explored the LHD, LPD (San Antonio Class), and CG ship classes, as these classes experienced the most mishaps between 2012 and 2017. We used linear regression, descriptive statistics,

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2018
Accession Number
AD1052795

Entities

People

  • Alejandro D. Musquiz
  • Mark A. Roach

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Accidents
  • Aircrafts
  • California
  • Collision Avoidance
  • Collision Avoidance Systems
  • Data Analysis
  • Data Mining
  • Data Set
  • Databases
  • Descriptive Analytics
  • Digital Data
  • Guidance
  • Information Science
  • Linear Regression Analysis
  • Naval Operations
  • Navy
  • Predictive Modeling
  • Regression Analysis
  • Statistical Analysis
  • Statistics
  • Surveys
  • Ticonderoga Class
  • Time Series Analysis
  • Unmanned Aerial Vehicles

Readers

  • Aviation Safety Risk Assessment.
  • Computational Modeling and Simulation
  • Naval Architecture and Marine Engineering.