Feature of development for risk management in Pavement Maintenance system
| Autor: | Sergiu Jecan, Oana Dines, Lucia Rusu, Dan Benta |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
050210 logistics & transportation
Computer science business.industry 05 social sciences Reference class forecasting 0211 other engineering and technologies Nonparametric statistics Pavement maintenance 021107 urban & regional planning 02 engineering and technology Development (topology) Risk analysis (engineering) 0502 economics and business Management system Feature (machine learning) business Risk management |
| Zdroj: | 2016 IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA). |
| DOI: | 10.1109/icccbda.2016.7529593 |
| Popis: | The goal of this paper is to summarize some practical issues of date research concerning the development and implementation of the risk management application Risk3M for Pavement Maintenance and Management System (PMMS). The paper also illustrates the need for potential development of such a risk system for analysis and risk factors and mitigation in pavement maintenance and rehabilitation strategies. We use a particular implementation of the k-nearest neighbors (k-NN) algorithm as a non parametric alternative method for reference class forecasting, based on mathematical kernel density estimate. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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