Using data mining techniques to predict deformability properties of jet grouting laboratory formulations over time

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7026 LNAI, Issue , 2011, Pages 491-505

  Tinoco, Joaquim ^a   Gomes Correia, António ^a   Cortez, Paulo ^a  

^a UNIVERSITY OF MINHO   (Portugal)

Author keywords

Artificial Neural Networks; Functional Networks; Ground improvement; Jet Grouting; Regression; Support Vector Machines; Young Modulus

Indexed keywords

FUNCTIONAL NETWORK; GROUND IMPROVEMENT; JET GROUTING; REGRESSION; SUPPORT VECTOR; YOUNG MODULUS;

CONCRETE CONSTRUCTION; DEFORMATION; DESIGN; GROUTING; MORTAR; NEURAL NETWORKS; SENSITIVITY ANALYSIS; SOIL TESTING; SOILS; SUPPORT VECTOR MACHINES;

DATA MINING;

EID: 80054824464     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24769-9_36     Document Type: Conference Paper

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