Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning

R. Urraca, A. Sanz-Garcia, J. Fernandez-Ceniceros, E. Sodupe-Ortega, F. J. Martinez-de-Pison

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Alkuperäiskielienglanti
OtsikkoHybrid Artificial Intelligent Systems : 10th international conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015 ; proceedings
ToimittajatEnrique Onieva, Eneko Osaba, Hector Quintian, Emilio Corchado
Sivumäärä12
KustantajaSpringer International Publishing AG
Julkaisupäivä2015
Sivut632-643
ISBN (painettu)978-3-319-19643-5
ISBN (elektroninen)978-3-319-19644-2
DOI - pysyväislinkit
TilaJulkaistu - 2015
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Hybrid Artificial Intelligence Systems - Bilbao, Espanja
Kesto: 22 kesäkuuta 201524 kesäkuuta 2015
Konferenssinumero: 10

Julkaisusarja

NimiLecture Notes in Artificial Intelligence
KustantajaSpringer International Publishing
Numero9121
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Lisätietoja


Volume:
Proceeding volume:

Tieteenalat

  • 113 Tietojenkäsittely- ja informaatiotieteet

Lainaa tätä

Urraca, R., Sanz-Garcia, A., Fernandez-Ceniceros, J., Sodupe-Ortega, E., & Martinez-de-Pison, F. J. (2015). Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning. teoksessa E. Onieva, E. Osaba, H. Quintian, & E. Corchado (Toimittajat), Hybrid Artificial Intelligent Systems: 10th international conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015 ; proceedings (Sivut 632-643). (Lecture Notes in Artificial Intelligence; Nro 9121). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-19644-2_52
Urraca, R. ; Sanz-Garcia, A. ; Fernandez-Ceniceros, J. ; Sodupe-Ortega, E. ; Martinez-de-Pison, F. J. / Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning. Hybrid Artificial Intelligent Systems: 10th international conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015 ; proceedings . Toimittaja / Enrique Onieva ; Eneko Osaba ; Hector Quintian ; Emilio Corchado. Springer International Publishing AG, 2015. Sivut 632-643 (Lecture Notes in Artificial Intelligence; 9121).
@inproceedings{6bd77e3bd70340bdb2594013416d644a,
title = "Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning",
keywords = "Genetic algorithms, Soft computing, Hotel room demand forecasting, Feature selection, Parsimony criterion, Support vector machines, OPTIMIZATION, PREDICTION, FURNACE, MODEL, 113 Computer and information sciences",
author = "R. Urraca and A. Sanz-Garcia and J. Fernandez-Ceniceros and E. Sodupe-Ortega and Martinez-de-Pison, {F. J.}",
note = "Volume: Proceeding volume:",
year = "2015",
doi = "10.1007/978-3-319-19644-2_52",
language = "English",
isbn = "978-3-319-19643-5",
series = "Lecture Notes in Artificial Intelligence",
publisher = "Springer International Publishing AG",
number = "9121",
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editor = "Enrique Onieva and Eneko Osaba and Hector Quintian and Emilio Corchado",
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Urraca, R, Sanz-Garcia, A, Fernandez-Ceniceros, J, Sodupe-Ortega, E & Martinez-de-Pison, FJ 2015, Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning. julkaisussa E Onieva, E Osaba, H Quintian & E Corchado (toim), Hybrid Artificial Intelligent Systems: 10th international conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015 ; proceedings . Lecture Notes in Artificial Intelligence, Nro 9121, Springer International Publishing AG, Sivut 632-643, International Conference on Hybrid Artificial Intelligence Systems, Bilbao, Espanja, 22/06/2015. https://doi.org/10.1007/978-3-319-19644-2_52

Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning. / Urraca, R.; Sanz-Garcia, A.; Fernandez-Ceniceros, J.; Sodupe-Ortega, E.; Martinez-de-Pison, F. J.

Hybrid Artificial Intelligent Systems: 10th international conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015 ; proceedings . toim. / Enrique Onieva; Eneko Osaba; Hector Quintian; Emilio Corchado. Springer International Publishing AG, 2015. s. 632-643 (Lecture Notes in Artificial Intelligence; Nro 9121).

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

TY - GEN

T1 - Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning

AU - Urraca, R.

AU - Sanz-Garcia, A.

AU - Fernandez-Ceniceros, J.

AU - Sodupe-Ortega, E.

AU - Martinez-de-Pison, F. J.

N1 - Volume: Proceeding volume:

PY - 2015

Y1 - 2015

KW - Genetic algorithms

KW - Soft computing

KW - Hotel room demand forecasting

KW - Feature selection

KW - Parsimony criterion

KW - Support vector machines

KW - OPTIMIZATION

KW - PREDICTION

KW - FURNACE

KW - MODEL

KW - 113 Computer and information sciences

U2 - 10.1007/978-3-319-19644-2_52

DO - 10.1007/978-3-319-19644-2_52

M3 - Conference contribution

SN - 978-3-319-19643-5

T3 - Lecture Notes in Artificial Intelligence

SP - 632

EP - 643

BT - Hybrid Artificial Intelligent Systems

A2 - Onieva, Enrique

A2 - Osaba, Eneko

A2 - Quintian, Hector

A2 - Corchado, Emilio

PB - Springer International Publishing AG

ER -

Urraca R, Sanz-Garcia A, Fernandez-Ceniceros J, Sodupe-Ortega E, Martinez-de-Pison FJ. Improving Hotel Room Demand Forecasting with a Hybrid GA-SVR Methodology Based on Skewed Data Transformation, Feature Selection and Parsimony Tuning. julkaisussa Onieva E, Osaba E, Quintian H, Corchado E, toimittajat, Hybrid Artificial Intelligent Systems: 10th international conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015 ; proceedings . Springer International Publishing AG. 2015. s. 632-643. (Lecture Notes in Artificial Intelligence; 9121). https://doi.org/10.1007/978-3-319-19644-2_52