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UniversidaddeCádiz
TEP024 Modelado Inteligente de Sistemas


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

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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

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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

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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

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Efficient goods inspection demand at ports: a comparative forecasting approach

2019 | JOURNAL_ARTICLE

DOI: 10.1111/itor.12397

EID: 2-s2.0-85014082095

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

2019 | JOURNAL_ARTICLE

EID: 2-s2.0-85067468363

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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

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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

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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

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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

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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

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

2017 | JOURNAL_ARTICLE

DOI: 10.2495/AIR170141

EID: 2-s2.0-85029809920

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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

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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

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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

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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

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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

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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

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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

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Pitting potential modelling of en 1.4404 stainless steel

2014 | JOURNAL_ARTICLE

DOI: 10.1002/maco.201307037

EID: 2-s2.0-84897637349

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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

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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

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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

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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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