Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Nicholas Fiorentini"'
Publikováno v:
Infrastructures, Vol 8, Iss 7, p 115 (2023)
Stone pavement structures (SPS), also known as stone roads or stone-paved roads, are road pavements constructed using stones as the primary surface material. Different types of SPS exist; historically, irregular-shaped stones with downward protrusion
Externí odkaz:
https://doaj.org/article/2718f07cf1c64cac86e9b45597bd3d49
Publikováno v:
Remote Sensing, Vol 15, Iss 11, p 2722 (2023)
Cracks are fractures or breaks that occur in materials such as concrete, metals, rocks, and other solids. Various methods are used to detect and monitor cracks; among many of them, image-based methodologies allow fast identification of the distress a
Externí odkaz:
https://doaj.org/article/787840a732764798ad6b56f263566fbf
Publikováno v:
Sensors, Vol 21, Iss 10, p 3377 (2021)
This paper proposes a methodology for correlating products derived by Synthetic Aperture Radar (SAR) measurements and laser profilometric road roughness surveys. The procedure stems from two previous studies, in which several Machine Learning Algorit
Externí odkaz:
https://doaj.org/article/d9ba2a6794ec42f582aa85e6b83900ab
Publikováno v:
Remote Sensing, Vol 12, Iss 23, p 3976 (2020)
This paper introduces a methodology for predicting and mapping surface motion beneath road pavement structures caused by environmental factors. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) measurements, geospatial analyses
Externí odkaz:
https://doaj.org/article/c4ebdcca26bf43a58defa5d2126b5cc5
Autor:
Nicholas Fiorentini, Massimo Losa
Publikováno v:
Infrastructures, Vol 5, Iss 7, p 61 (2020)
Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine learning algorithms for predicting crash severity have recently gained interest by the academic community, there is a significant trend towards neglecting the fact
Externí odkaz:
https://doaj.org/article/b3da26cdab2944208f5a8313c9b6364f
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2677:1455-1470
In the present paper, we implemented the Bayesian regularization (BR) backpropagation algorithm for calibrating an artificial neural network (ANN) as an accident prediction model (APM) to be used on Italian four-lane divided roads. We chose the BR-AN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::149e62cfbec22d06691d9ade3636e128
https://doi.org/10.1177/03611981221111367
https://doi.org/10.1177/03611981221111367
Publikováno v:
Roads and Airports Pavement Surface Characteristics ISBN: 9781003429258
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db1b9d91936818dc4df2e4a04e0fa90d
https://doi.org/10.1201/9781003429258-48
https://doi.org/10.1201/9781003429258-48
Publikováno v:
International journal of injury control and safety promotion.
Four Accident Prediction Models have been defined for Italian two-lane rural, suburban, and urban roads by exploiting different Machine Learning Algorithms. Specifically, a Classification and Regression Tree, a Boosted Regression Tree, a Random Fores
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::387cc903269de519aa9ec096adf18f17
https://pubmed.ncbi.nlm.nih.gov/35613339
https://pubmed.ncbi.nlm.nih.gov/35613339
Publikováno v:
Sensors
Volume 21
Issue 10
Sensors, Vol 21, Iss 3377, p 3377 (2021)
Sensors (Basel, Switzerland)
Volume 21
Issue 10
Sensors, Vol 21, Iss 3377, p 3377 (2021)
Sensors (Basel, Switzerland)
This paper proposes a methodology for correlating products derived by Synthetic Aperture Radar (SAR) measurements and laser profilometric road roughness surveys. The procedure stems from two previous studies, in which several Machine Learning Algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::265c3080909c4946bf2da3fc1c81c0ce
This paper proposes a methodology based on Artificial Neural Networks (ANNs) for integrating products derived by three on-ground Non-Destructive high-performance Techniques (NDTs) to estimate the International Roughness Index (IRI) of flexible road p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9ec637114b4c927a0a32b790e426ae8
http://hdl.handle.net/11568/1141145
http://hdl.handle.net/11568/1141145