What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Artificial neural network
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.
His most cited work include:
- A survey of multiple classifier systems as hybrid systems (612 citations)
- Hybrid Artificial Intelligent Systems (176 citations)
- Intelligent Data Engineering and Automated Learning – IDEAL 2006 (167 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (43.39%)
- Data mining (27.30%)
- Machine learning (21.55%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (43.39%)
- Data mining (27.30%)
- Soft computing (16.95%)
In recent papers he was focusing on the following fields of study:
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.
Between 2015 and 2021, his most popular works were:
- An intelligent fault detection system for a heat pump installation based on a geothermal heat exchanger (27 citations)
- Gaining deep knowledge of Android malware families through dimensionality reduction techniques (22 citations)
- Beta Hebbian Learning as a New Method for Exploratory Projection Pursuit (19 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Artificial neural network
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.
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