His primary areas of study are Artificial intelligence, Machine learning, Artificial neural network, Data mining and Soft computing. Emilio Corchado combines topics linked to Software engineering with his work on Artificial intelligence. The study incorporates disciplines such as Hybrid learning, Network security and Multiple classifier in addition to Machine learning.
His study looks at the intersection of Artificial neural network and topics like Pattern recognition with Versa and Connectionism. His Data mining research integrates issues from Web service and Hybrid intelligent system. His Intelligent decision support system research incorporates elements of Classifier, Margin classifier, Information fusion and Hybrid system.
Emilio Corchado mostly deals with Artificial intelligence, Data mining, Machine learning, Artificial neural network and Soft computing. His Artificial intelligence study frequently draws connections between related disciplines such as Pattern recognition. His Data mining study incorporates themes from Automatic summarization, Cluster analysis and Case-based reasoning.
His study in the field of Support vector machine also crosses realms of Process. His Soft computing research incorporates themes from Computational intelligence and Engineering management. In his research on the topic of Intrusion detection system, Connectionism is strongly related with Simple Network Management Protocol.
Emilio Corchado mainly investigates Artificial intelligence, Data mining, Soft computing, Machine learning and Artificial neural network. The concepts of his Artificial intelligence study are interwoven with issues in Quality and Pattern recognition. His Data mining research incorporates elements of Mixture model, Hybrid approach, Imputation and Cluster analysis.
His research integrates issues of Construction engineering, Computational intelligence, Industrial engineering and Data science in his study of Soft computing. His study connects Android malware and Machine learning. His studies in Artificial neural network integrate themes in fields like Visualization, Unsupervised learning and Support vector machine.
The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Data mining, Artificial neural network and Android malware. His research combines Pattern recognition and Artificial intelligence. His study on Recommender system, Meta learning and Imputation is often connected to Mars Exploration Program as part of broader study in Machine learning.
His work deals with themes such as Correlation clustering, Cluster analysis, Air quality index and Missing data, which intersect with Data mining. His research in Artificial neural network intersects with topics in Representation, Embedded system, Support vector machine and Polynomial regression. His Android malware study integrates concerns from other disciplines, such as World Wide Web and Dimensionality reduction.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A survey of multiple classifier systems as hybrid systems
Michał Woniak;Manuel Graña;Emilio Corchado.
Information Fusion (2014)
Development of CBR-BDI Agents: A Tourist Guide Application
Juan M. Corchado;Juan Pavón;Emilio Corchado;Luis Fernando Castillo.
Lecture Notes in Computer Science (2004)
Neural visualization of network traffic data for intrusion detection
Emilio Corchado;Álvaro Herrero.
soft computing (2011)
Maximum likelihood hebbian learning based Retrieval method for CBR systems
Juan M. Corchado;Emilio S. Corchado;Jim Aiken;Colin Fyfe.
international conference on case-based reasoning (2003)
A forecasting solution to the oil spill problem based on a hybrid intelligent system
Bruno Baruque;Emilio Corchado;Aitor Mata;Juan M. Corchado.
Information Sciences (2010)
Hybrid Artificial Intelligent Systems
Emilio Corchado;Vaclav Snasel;Ajith Abraham;Michał Woźniak.
Editorial: Hybrid learning machines
Ajith Abraham;Emilio Corchado;Juan M. Corchado.
IBR retrieval method based on topology preserving mappings
Emilio Corchado;Juan M. Corchado;Jim Aiken.
Journal of Experimental and Theoretical Artificial Intelligence (2004)
Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit
Emilio Corchado;Donald MacDonald;Colin Fyfe.
Data Mining and Knowledge Discovery (2004)
Quantifying the Ocean's CO2 budget with a CoHeL-IBR system
Juan M. Corchado;Jim Aiken;Emilio S. Corchado;Nathalie Lefevre.
Lecture Notes in Computer Science (2004)
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