ORCID

Información ORCID de TURIAS DOMINGUEZ, IGNACIO JOSE

Biografía

Papers and research works can be found in:\nhttp://www.researcherid.com/rid/L-7211-2014\nhttp://www.linkedin.com/pub/ignacio-turias/46/515/305\nhttps://www.researchgate.net/profile/Ignacio_Turias/

Empleo

Full Professor - Dr. Industrial Engineering (Computer Science Departament)

University of Cádiz: Algeciras, ", , España

Obras

Air Pollution PM10 Forecasting Maps in the Maritime Area of the Bay of Algeciras (Spain)

2024 | JOURNAL_ARTICLE

DOI: 10.3390/jmse12030397

Mostrar Detalles

Application of Computational Contact tools of Finite Element Analysis to Predict Ground‐Borne Vibrations Generated by Trains in Ballasted Tracks

2024 | OTHER

DOI: 10.20944/preprints202402.0547.v1

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A Machine Learning Approach for Modelling Cold-Rolling Curves for Various Stainless Steels

2023 | JOURNAL_ARTICLE

DOI: 10.3390/ma17010147

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Forecasting air pollutants using classification models: a case study in the Bay of Algeciras (Spain)

2023 | JOURNAL_ARTICLE

DOI: 10.1007/s00477-023-02512-2

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Application of Multivariate Statistical Techniques as an Indicator of Variability of the Effects of COVID-19 on the Paris Memorandum of Understanding on Port State Control

2023 | JOURNAL_ARTICLE

DOI: 10.3390/math11143188

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Air pollution relevance analysis in the bay of Algeciras (Spain)

2023 | JOURNAL_ARTICLE

DOI: 10.1007/s13762-022-04466-4

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Long Short-Term Memory Approach for Short-Term Air Quality Forecasting in the Bay of Algeciras (Spain)

2023 | JOURNAL_ARTICLE

DOI: 10.3390/su15065089

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A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data

2023 | BOOK_CHAPTER

DOI: 10.1007/978-3-031-34953-9_33

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A Virtual Sensor Approach to Estimate the Stainless Steel Final Chemical Characterisation

2023 | BOOK_CHAPTER

DOI: 10.1007/978-3-031-18050-7_34

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Deep Learning Approach for the Prediction of the Concentration of Chlorophyll ɑ in Seawater. A Case Study in El Mar Menor (Spain)

2023 | BOOK_CHAPTER

DOI: 10.1007/978-3-031-18050-7_8

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Hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier

2023 | BOOK_CHAPTER

DOI: 10.1007/978-3-031-42529-5_8

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A comparison of ranking filter methods applied to the estimation of NO2 concentrations in the Bay of Algeciras (Spain)

2021 | JOURNAL_ARTICLE

DOI: 10.1007/s00477-021-01992-4

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Evaluation of Paris MoU Maritime Inspections Using a STATIS Approach

2021 | JOURNAL_ARTICLE

DOI: 10.3390/math9172092

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A permutation entropy-based EMD–ANN forecasting ensemble approach for wind speed prediction

2021 | JOURNAL_ARTICLE

DOI: 10.1007/s00521-020-05141-w

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A machine learning-based forecasting system of perishable cargo flow in maritime transport

2021 | JOURNAL_ARTICLE

DOI: 10.1016/j.neucom.2019.10.121

EID: 2-s2.0-85096179085

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Artificial neural networks, sequence-to-sequence lstms, and exogenous variables as analytical tools for no2 (Air pollution) forecasting: A case study in the bay of Algeciras (Spain)

2021 | JOURNAL_ARTICLE

DOI: 10.3390/s21051770

EID: 2-s2.0-85101918470

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Deep neural networks architecture driven by problem-specific information

2021 | JOURNAL_ARTICLE

DOI: 10.1007/s00521-021-05702-7

EID: 2-s2.0-85099944352

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Hourly Air Quality Index (AQI) Forecasting Using Machine Learning Methods

2021 | BOOK

DOI: 10.1007/978-3-030-57802-2_12

EID: 2-s2.0-85091276262

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A Hybrid Approach for Short-Term NO2 Forecasting: Case Study of Bay of Algeciras (Spain)

2020 | JOURNAL_ARTICLE

DOI: 10.1007/978-3-030-20055-8_18

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A clustering-based hybrid support vector regression model to predict container volume at seaport sanitary facilities

2020 | JOURNAL_ARTICLE

DOI: 10.3390/app10238326

EID: 2-s2.0-85096526529

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A freight inspection volume forecasting approach using an aggregation/disaggregation procedure, machine learning and ensemble models

2020 | JOURNAL_ARTICLE

DOI: 10.1016/J.NEUCOM.2019.06.109

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Analysis of Bootstrapped Operating Efficiency in Container Ports. A Case Study in Spain and Portugal

2020 | BOOK_CHAPTER

DOI: 10.1007/978-3-030-30938-1_42

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Container demand forecasting at border posts of ports: A hybrid SARIMA-SOM-SVR approach

2020 | BOOK

DOI: 10.1007/978-3-030-41913-4_7

EID: 2-s2.0-85080951359

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Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance

2020 | BOOK_CHAPTER

DOI: 10.1007/978-3-030-41913-4_6

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Spatial and Meteorological Behaviour of Daily Ozone Air Pollution in the Bay of Algeciras (2010–2015)

2020 | BOOK_CHAPTER

DOI: 10.1007/978-3-030-30938-1_4

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Clasificación de los puertos españoles mediante análisis cluster

2019 | JOURNAL_ARTICLE

DOI: 10.3989/ic.61806

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Spatial and meteorological relevance in NO2 estimations: a case study in the Bay of Algeciras (Spain)

2019 | JOURNAL_ARTICLE

DOI: 10.1007/s00477-018-01644-0

EID: 2-s2.0-85060334396

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A Deep Ensemble Neural Network Approach to Improve Predictions of Container Inspection Volume

2019 | JOURNAL_ARTICLE

DOI: 10.1007/978-3-030-20521-8_66

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A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations

2019 | BOOK_CHAPTER

DOI: 10.1007/978-3-030-20521-8_70

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A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel

2019 | JOURNAL_ARTICLE

DOI: 10.1007/978-3-030-29859-3_43

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A two-stage forecasting approach for short-term intermodal freight prediction

2019 | JOURNAL_ARTICLE

DOI: 10.1111/itor.12337

EID: 2-s2.0-84984831676

Mostrar Detalles

Addition of Pathway-Based Information to Improve Predictions in Transcriptomics

2019 | BOOK

DOI: 10.1007/978-3-030-17935-9_19

EID: 2-s2.0-85065734567

Mostrar Detalles

An artificial neural network ensemble approach to generate air pollution maps

2019 | JOURNAL_ARTICLE

DOI: 10.1007/S10661-019-7901-6

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Bootstrapped operating efficiency in container ports: a case study in Spain and Portugal

2019 | JOURNAL_ARTICLE

DOI: 10.1108/IMDS-03-2018-0132

EID: 2-s2.0-85059448800

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ESTIMATION OF NO2 CONCENTRATION VALUES IN A MONITORING SENSOR NETWORK USING A FUSION APPROACH

2019 | JOURNAL_ARTICLE

Mostrar Detalles

Efficient goods inspection demand at ports: a comparative forecasting approach

2019 | JOURNAL_ARTICLE

DOI: 10.1111/itor.12397

EID: 2-s2.0-85014082095

Mostrar Detalles

Estimation of NO2 concentration values in a monitoring sensor network using a fusion approach

2019 | JOURNAL_ARTICLE

EID: 2-s2.0-85067468363

Mostrar Detalles

Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar

2019 | JOURNAL_ARTICLE

DOI: 10.1007/978-3-030-20521-8_67

Mostrar Detalles

Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks

2019 | JOURNAL_ARTICLE

DOI: 10.1007/978-3-030-29859-3_48

Mostrar Detalles

SVR-Ensemble Forecasting Approach for Ro-Ro Freight at Port of Algeciras (Spain)

2019 | BOOK

DOI: 10.1007/978-3-319-94120-2_34

EID: 2-s2.0-85048621110

Mostrar Detalles

Data dimension and structure effects in predictive performance of deep neural networks

2018 | BOOK

DOI: 10.3233/978-1-61499-900-3-361

EID: 2-s2.0-85063392550

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Efficiency evolution of largest Iberian peninsula container ports: An application of malmquist productivity index

2018 | JOURNAL_ARTICLE

DOI: 10.19272/201806701004

EID: 2-s2.0-85051725896

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Forecasting freight inspection volume using bayesian regularization artificial neural networks: An aggregation-disaggregation procedure

2018 | BOOK

DOI: 10.1007/978-3-319-67180-2_17

EID: 2-s2.0-85028630098

Mostrar Detalles

Prediction of pitting corrosion status of EN 1.4404 stainless steel by using a 2‐stage procedure based on support vector machines

2017 | JOURNAL_ARTICLE

DOI: 10.1002/cem.2936

EID: 2-s2.0-85028525360

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Una comparativa entre redes neuronales artificiales y métodos clásicos para la predicción de la movilidad entre zonas de transporte. Aplicación práctica en el Campo de Gibraltar, España

2017 | JOURNAL_ARTICLE

DOI: 10.15446/dyna.v84n200.56571

EID: 2-s2.0-85021784050

Mostrar Detalles

Prediction of carbon monoxide (CO) atmospheric pollution concentrations using meterological variables

2017 | JOURNAL_ARTICLE

DOI: 10.2495/AIR170141

EID: 2-s2.0-85029809920

Mostrar Detalles

Solving scheduling problems with genetic algorithms using a priority encoding scheme

2017 | BOOK

DOI: 10.1007/978-3-319-59153-7_5

EID: 2-s2.0-85020517095

Mostrar Detalles

Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain)

2016 | JOURNAL_ARTICLE

DOI: 10.15446/dyna.v83n195.47027

EID: 2-s2.0-84958770203

Mostrar Detalles

A two-stage model based on artificial neural networks to determine pitting corrosion status of 316L stainless steel

2016 | JOURNAL_ARTICLE

DOI: 10.1515/corrrev-2015-0048

EID: 2-s2.0-84960958483

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Classification of Spanish Ports by studying Operational Indicators using Cluster Analysis

2016 | JOURNAL_ARTICLE

DOI: 10.17981/INGECUC.12.2.2016.04

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Comparison of international normalized ratio audit parameters in patients enrolled in GARFIELD-AF and treated with vitamin K antagonists

2016 | JOURNAL_ARTICLE

DOI: 10.1111/BJH.14084

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Short-term Forecasting of Intermodal Freight Using ANNs and SVR: Case of the Port of Algeciras Bay

2016 | CONFERENCE_PAPER

DOI: 10.1016/j.trpro.2016.12.015

EID: 2-s2.0-85019158707

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Short-term forecasting of intermodal freight using ANNs and SVR: Case of the Port of Algeciras Bay

2016 | JOURNAL_ARTICLE

DOI: 10.4995/CIT2016.2016.3464

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Time Analysis of the Containerized Cargo Flow in the Logistic Chain Using Simulation Tools: The Case of the Port of Seville (Spain)

2016 | CONFERENCE_PAPER

DOI: 10.1016/j.trpro.2016.12.003

EID: 2-s2.0-85019053861

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Time analysis of the containerized cargo flow in the logistic chain using simulation tools: the case of the Port of Seville (Spain)

2016 | JOURNAL_ARTICLE

DOI: 10.4995/CIT2016.2016.3083

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A novel three-step procedure to forecast the inspection volume

2015 | JOURNAL_ARTICLE

DOI: 10.1016/j.trc.2015.04.024

EID: 2-s2.0-84955327395

Mostrar Detalles

A two-stage procedure for forecasting freight inspections at Border Inspection Posts using SOMs and support vector regression

2015 | JOURNAL_ARTICLE

DOI: 10.1080/00207543.2014.965852

EID: 2-s2.0-84922780008

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Analysis of the global and technical efficiencies of major Spanish container ports

2015 | JOURNAL_ARTICLE

EID: 2-s2.0-84951264276

Mostrar Detalles

Characterization of pitting corrosion of stainless steel using artificial neural networks

2015 | JOURNAL_ARTICLE

DOI: 10.1002/maco.201408173

EID: 2-s2.0-84943198823

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Pitting corrosion behaviour modelling of stainless steel with support vector machines

2015 | JOURNAL_ARTICLE

DOI: 10.1002/maco.201407788

EID: 2-s2.0-85028203530

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A comparison of forecasting methods for Ro-Ro traffic: A case study in the strait of gibraltar

2014 | BOOK

DOI: 10.1007/978-3-319-07013-1_33

EID: 2-s2.0-84917680503

Mostrar Detalles

A comprehensive approach based on SVM to model pitting corrosion behaviour of en 1.4404 stainless steel

2014 | JOURNAL_ARTICLE

DOI: 10.1002/maco.201307252

EID: 2-s2.0-84908210962

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An automatic pitting corrosion detection approach for 316L stainless steel

2014 | JOURNAL_ARTICLE

DOI: 10.1016/j.matdes.2013.11.045

EID: 2-s2.0-84890343240

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Breakdown potential modelling of austenitic stainless steel

2014 | JOURNAL_ARTICLE

DOI: 10.1002/cem.2591

EID: 2-s2.0-84897665708

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Hybrid approaches based on SARIMA and artificial neural networks for inspection time series forecasting

2014 | JOURNAL_ARTICLE

DOI: 10.1016/j.tre.2014.03.009

EID: 2-s2.0-84899860927

Mostrar Detalles

Hybrid approaches of support vector regression and SARIMA models to forecast the inspections volume

2014 | BOOK

DOI: 10.1007/978-3-319-07617-1_44

EID: 2-s2.0-84902477673

Mostrar Detalles

Pitting potential modelling of en 1.4404 stainless steel

2014 | JOURNAL_ARTICLE

DOI: 10.1002/maco.201307037

EID: 2-s2.0-84897637349

Mostrar Detalles

Prediction of PM10 and SO2 exceedances to control air pollution in the Bay of Algeciras, Spain

2014 | JOURNAL_ARTICLE

DOI: 10.1007/s00477-013-0827-6

EID: 2-s2.0-84903537824

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A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel

2013 | JOURNAL_ARTICLE

Mostrar Detalles

A constructive neural network to predict pitting corrosion status of stainless steel

2013 | BOOK

DOI: 10.1007/978-3-642-38679-4_7

EID: 2-s2.0-84880060719

Mostrar Detalles

Pitting potential modeling using Bayesian neural networks

2013 | JOURNAL_ARTICLE

DOI: 10.1016/j.elecom.2013.07.039

EID: 2-s2.0-84884469780

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Pitting Corrosion Detection of Austenitic Stainless Steel EN 1.4404 in MgCl2 solutions using a Machine Learning Approach

2012 | JOURNAL_ARTICLE

DOI: 10.1063/1.4707652

EID: 2-s2.0-84863336308

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Pitting corrosion behaviour of austenitic stainless steel using artificial intelligence techniques

2012 | JOURNAL_ARTICLE

DOI: 10.1016/j.jal.2012.07.005

EID: 2-s2.0-84869509101

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Austenitic Stainless Steel EN 1.4404 Corrosion Detection Using Classification Techniques

2011 | JOURNAL_ARTICLE

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Austenitic stainless steel en 1.4404 corrosion detection using classification techniques

2011 | BOOK

DOI: 10.1007/978-3-642-19644-7_21

EID: 2-s2.0-80052922101

Mostrar Detalles

Improved likelihood ratio test based voice activity detector applied to speech recognition

2010 | JOURNAL_ARTICLE

DOI: 10.1016/j.specom.2010.03.003

EID: 2-s2.0-79851470718

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Prediction models of CO, SPM and SO(2) concentrations in the Campo de Gibraltar Region, Spain: A multiple comparison strategy

2008 | JOURNAL_ARTICLE

DOI: 10.1007/s10661-007-9963-0

EID: 2-s2.0-47349111557

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Prediction of CO maximum ground level concentrations in the Bay of Algeciras, Spain using artificial neural networks

2008 | JOURNAL_ARTICLE

DOI: 10.1016/j.chemosphere.2007.08.039

EID: 2-s2.0-37549000626

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An efficient VAD based on a generalized Gaussian PDF

2007 | BOOK

EID: 2-s2.0-38549171024

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An efficient VAD based on a generalized gaussian PDF

2007 | BOOK_CHAPTER

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An efficient VAD based on a hang-over scheme and a likelihood ratio test

2007 | BOOK_CHAPTER

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An efficient VAD based on a hang-over scheme and a likelihood ratio test

2007 | BOOK

EID: 2-s2.0-38049141436

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Improved likelihood ratio test detector using a jointly Gaussian probability distribution function

2007 | BOOK_CHAPTER

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Improved likelihood ratio test detector using a jointly Gaussian probability distribution function

2007 | BOOK

EID: 2-s2.0-38149040986

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A competitive neural network approach for meteorological situation clustering

2006 | JOURNAL_ARTICLE

DOI: 10.1016/j.atmosenv.2005.09.065

EID: 2-s2.0-29144484834

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C-means clustering applied to speech discrimination

2006 | BOOK_CHAPTER

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C-means clustering applied to speech discrimination

2006 | BOOK

EID: 2-s2.0-33746594790

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Modelling the effective thermal conductivity of an unidirectional composite by the use of artificial neural networks

2005 | JOURNAL_ARTICLE

DOI: 10.1016/j.compscitech.2004.09.018

EID: 2-s2.0-11344288986

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Pattern recognition approach to quantitative description of the microstructure of disordered composites for estimation of thermal conductivity

2002 | JOURNAL_ARTICLE

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Pattern recognition approach to quantitative description of the microstructure of disordered composites for estimation of thermal conductivity

2002 | JOURNAL_ARTICLE

EID: 2-s2.0-0036411164

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Información ORCID de TURIAS DOMINGUEZ, IGNACIO JOSE

Biografía

Empleo

Full Professor - Dr. Industrial Engineering (Computer Science Departament)

Obras

Air Pollution PM10 Forecasting Maps in the Maritime Area of the Bay of Algeciras (Spain)

Application of Computational Contact tools of Finite Element Analysis to Predict Ground‐Borne Vibrations Generated by Trains in Ballasted Tracks

A Machine Learning Approach for Modelling Cold-Rolling Curves for Various Stainless Steels

Forecasting air pollutants using classification models: a case study in the Bay of Algeciras (Spain)

Application of Multivariate Statistical Techniques as an Indicator of Variability of the Effects of COVID-19 on the Paris Memorandum of Understanding on Port State Control

Air pollution relevance analysis in the bay of Algeciras (Spain)

Long Short-Term Memory Approach for Short-Term Air Quality Forecasting in the Bay of Algeciras (Spain)

A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data

A Virtual Sensor Approach to Estimate the Stainless Steel Final Chemical Characterisation

Deep Learning Approach for the Prediction of the Concentration of Chlorophyll ɑ in Seawater. A Case Study in El Mar Menor (Spain)

Hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier

A comparison of ranking filter methods applied to the estimation of NO2 concentrations in the Bay of Algeciras (Spain)

Evaluation of Paris MoU Maritime Inspections Using a STATIS Approach

A permutation entropy-based EMD–ANN forecasting ensemble approach for wind speed prediction

A machine learning-based forecasting system of perishable cargo flow in maritime transport

Artificial neural networks, sequence-to-sequence lstms, and exogenous variables as analytical tools for no2 (Air pollution) forecasting: A case study in the bay of Algeciras (Spain)

Deep neural networks architecture driven by problem-specific information

Hourly Air Quality Index (AQI) Forecasting Using Machine Learning Methods

A Hybrid Approach for Short-Term NO2 Forecasting: Case Study of Bay of Algeciras (Spain)

A clustering-based hybrid support vector regression model to predict container volume at seaport sanitary facilities

A freight inspection volume forecasting approach using an aggregation/disaggregation procedure, machine learning and ensemble models

Analysis of Bootstrapped Operating Efficiency in Container Ports. A Case Study in Spain and Portugal

Container demand forecasting at border posts of ports: A hybrid SARIMA-SOM-SVR approach

Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance

Spatial and Meteorological Behaviour of Daily Ozone Air Pollution in the Bay of Algeciras (2010–2015)

Clasificación de los puertos españoles mediante análisis cluster

Spatial and meteorological relevance in NO2 estimations: a case study in the Bay of Algeciras (Spain)

A Deep Ensemble Neural Network Approach to Improve Predictions of Container Inspection Volume

A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations

A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel

A two-stage forecasting approach for short-term intermodal freight prediction

Addition of Pathway-Based Information to Improve Predictions in Transcriptomics

An artificial neural network ensemble approach to generate air pollution maps

Bootstrapped operating efficiency in container ports: a case study in Spain and Portugal

ESTIMATION OF NO2 CONCENTRATION VALUES IN A MONITORING SENSOR NETWORK USING A FUSION APPROACH

Efficient goods inspection demand at ports: a comparative forecasting approach

Estimation of NO2 concentration values in a monitoring sensor network using a fusion approach

Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar

Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks

SVR-Ensemble Forecasting Approach for Ro-Ro Freight at Port of Algeciras (Spain)

Data dimension and structure effects in predictive performance of deep neural networks

Efficiency evolution of largest Iberian peninsula container ports: An application of malmquist productivity index

Forecasting freight inspection volume using bayesian regularization artificial neural networks: An aggregation-disaggregation procedure

Prediction of pitting corrosion status of EN 1.4404 stainless steel by using a 2‐stage procedure based on support vector machines

Una comparativa entre redes neuronales artificiales y métodos clásicos para la predicción de la movilidad entre zonas de transporte. Aplicación práctica en el Campo de Gibraltar, España

Prediction of carbon monoxide (CO) atmospheric pollution concentrations using meterological variables

Solving scheduling problems with genetic algorithms using a priority encoding scheme

Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain)

A two-stage model based on artificial neural networks to determine pitting corrosion status of 316L stainless steel

Classification of Spanish Ports by studying Operational Indicators using Cluster Analysis

Comparison of international normalized ratio audit parameters in patients enrolled in GARFIELD-AF and treated with vitamin K antagonists

Short-term Forecasting of Intermodal Freight Using ANNs and SVR: Case of the Port of Algeciras Bay

Short-term forecasting of intermodal freight using ANNs and SVR: Case of the Port of Algeciras Bay

Time Analysis of the Containerized Cargo Flow in the Logistic Chain Using Simulation Tools: The Case of the Port of Seville (Spain)

Time analysis of the containerized cargo flow in the logistic chain using simulation tools: the case of the Port of Seville (Spain)

A novel three-step procedure to forecast the inspection volume

A two-stage procedure for forecasting freight inspections at Border Inspection Posts using SOMs and support vector regression

Analysis of the global and technical efficiencies of major Spanish container ports

Characterization of pitting corrosion of stainless steel using artificial neural networks

Pitting corrosion behaviour modelling of stainless steel with support vector machines

A comparison of forecasting methods for Ro-Ro traffic: A case study in the strait of gibraltar

A comprehensive approach based on SVM to model pitting corrosion behaviour of en 1.4404 stainless steel

An automatic pitting corrosion detection approach for 316L stainless steel

Breakdown potential modelling of austenitic stainless steel

Hybrid approaches based on SARIMA and artificial neural networks for inspection time series forecasting

Hybrid approaches of support vector regression and SARIMA models to forecast the inspections volume

Pitting potential modelling of en 1.4404 stainless steel

Prediction of PM10 and SO2 exceedances to control air pollution in the Bay of Algeciras, Spain

A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel

A constructive neural network to predict pitting corrosion status of stainless steel

Pitting potential modeling using Bayesian neural networks

Pitting Corrosion Detection of Austenitic Stainless Steel EN 1.4404 in MgCl2 solutions using a Machine Learning Approach

Pitting corrosion behaviour of austenitic stainless steel using artificial intelligence techniques