Unified Feature Selection and Hyperparameter Bayesian Optimization for Machine Learning based Regression

Sandru, Elena-Diana; David, Emilian

doi:10.1109/isscs.2019.8801728

Cited by 2 publications

(1 citation statement)

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“…Once the data were preprocessed, the next step was preparing a feature selector tool adapted to the particular dataset but whose configuration could be modified based on the type of data typically available. Feature selection involves using only appropriate features that explain the dependent variable and the process helps produce good learners and models [47]. In this case, the dependent variable is the year when road intervention took place for a given road in the network.…”

Section: Developing Feature Selectormentioning

confidence: 99%

Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions

2021

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Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorities. This study develops a roadmap to help these authorities by using flexible data analysis and deep learning computational systems to highlight important factors within road networks, which are used to construct models that can help predict future intervention timelines. A case study in Palermo, Italy was successfully developed to demonstrate how the techniques could be applied to perform appropriate feature selection and prediction models based on limited data sources. The workflow provides a pathway towards more effective pavement maintenance management practices using techniques that can be readily adapted based on different environments. This takes another step towards automating these practices within the pavement management system.

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Section: Developing Feature Selectormentioning

confidence: 99%