Use of Factor Analysis (FA), Artificial Neural Networks (ANNs), and Multiple Linear Regression (MLR) for Electrical Conductivity Prediction in Aquifers in the Gallikos River Basin, Northern Greece

Autor: Christos Mattas, Lamprini Dimitraki, Pantazis Georgiou, Panagiota Venetsanou

Publikováno v: Hydrology, Vol 8, Iss 3, p 127 (2021)

Due to the fact of water resource deterioration from human activities and increased demand over the last few decades, optimization of management practices and policies is required, for which more reliable data are necessary. Cost and time are always

Externí odkaz: https://doaj.org/article/6cf5d07827344da9965832db010262fd

Predicting the average size of blasted rocks in aggregate quarries using artificial neural networks

Autor: Lamprini Dimitraki, Vassilis Marinos, Ioannis Vlahavas, Nikolas Arampelos, Basile Christaras

Publikováno v: Bulletin of Engineering Geology and the Environment. 78:2717-2729

The prediction of the average size of fragments in blasted rock piles produced after blasting in aggregate quarries is essential for decresing the cost of crushing and secondary breaking. There are several conventional and advanced processes to estim

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::078537f8e20827215d6bad7aba460a34
https://doi.org/10.1007/s10064-018-1270-1

COMPARATIVE SURFACE DAMAGE DETERMINATION AT A JEWISH GRAVE USING TWO DIFFERENT MOBILE ULTRASONIC VELOCITY DEVICES

Autor: An. Moropoulou, Basile Christaras, Kyriaki Devlioti, Lamprini Dimitraki, M. Chatziangelou

Publikováno v: Δελτίο της Ελληνικής Γεωλογικής Εταιρείας; Τόμ. 50 Αρ. 3 (2016): 14th International Conference of the G.S.G.; 1626-1632
Bulletin of the Geological Society of Greece; Vol. 50 No. 3 (2016): 14th International Conference of the G.S.G.; 1626-1632

Οι μη καταστροφικές μέθοδοι είναι απαραίτητες στην έρευνα των φυσικών και μηχανικών ιδιοτήτων των υλικών των ιστορικών μνημείων. Σε αυτ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48e1bdecd1d191cf3dae31a3a7774be5
https://ejournals.epublishing.ekt.gr/index.php/geosociety/article/view/11882