Results 171 to 180 of about 443,747 (214)

Derecho a la ciudad y urbanización latinoamericana.

Proyección, 2021
Proyección Estudios geográficos y de Ordenamiento Territorial
doaj  

Enhanced impact resistance of novel sustainable preplaced aggregate geopolymer concrete reinforced with steel mesh and 5D fibers. [PDF]

Sci Rep
Samadi M, Murali G, Wong LS, Kurpińska M, Abdelgader HS, Abdulkadir I, Lim NHAS, Avudaiappan S, Abdellatief M.   +8 more
europepmc   +1 more source

Ordenamiento Territorial y Desarrollo Sostenible

Proyección, 2022
Proyección Estudios geográficos y de Ordenamiento Territorial
doaj  

Evaluating the strength of industrial wastesbased concrete reinforced with steel fiber using advanced machine learning. [PDF]

Sci Rep
Onyelowe KC, Kamchoom V, Ebid AM, Hanandeh S, Zurita Polo SM, Noboa Silva VF, Santillán Murillo RO, Zabala Vizuete RF, Awoyera P, Avudaiappan S.   +9 more
europepmc   +1 more source

Aproximación a un concepto técnico del ordenamiento civil [PDF]

, 1983
Coca Payeras, Miquel
core  

Edición Especial

Proyección, 2021
Proyección Estudios geográficos y de Ordenamiento Territorial
doaj  

Developing advanced datadriven framework to predict the bearing capacity of piles on rock. [PDF]

Sci Rep
Onyelowe KC, Hanandeh S, Kamchoom V, Ebid AM, Reyes Silva FD, Allauca Palta JL, Llamuca Llamuca JL, Avudaiappan S.   +7 more
europepmc   +1 more source

Physics-informed modeling of splitting tensile strength of recycled aggregate concrete using advanced machine learning. [PDF]

Sci Rep
Onyelowe KC, Kamchoom V, Hanandeh S, Anandha Kumar S, Zabala Vizuete RF, Santillán Murillo RO, Zurita Polo SM, Torres Castillo RM, Ebid AM, Awoyera P, Arunachalam KP.   +10 more
europepmc   +1 more source

Optimizing the utilization of Metakaolin in pre-cured geopolymer concrete using ensemble and symbolic regressions. [PDF]

Sci Rep
Onyelowe KC, Kamchoom V, Ebid AM, Hanandeh S, Llamuca Llamuca JL, Londo Yachambay FP, Allauca Palta JL, Vishnupriyan M, Avudaiappan S.   +8 more
europepmc   +1 more source

Developing data driven framework to model earthquake induced liquefaction potential of granular terrain by machine learning classification models. [PDF]

Sci Rep
Onyelowe KC, Kamchoom V, Gnananandarao T, Arunachalam KP.   +3 more
europepmc   +1 more source