Seppo J. Ovaska

What is he best known for?

The fields of study he is best known for:

• Artificial intelligence
• Electrical engineering
• Machine learning

His main research concerns Artificial intelligence, Control theory, Filter, Machine learning and Digital filter. In his study, Sampling and Signal is strongly linked to Algorithm, which falls under the umbrella field of Artificial intelligence. He studies Adaptive filter which is a part of Control theory.

His work carried out in the field of Filter brings together such families of science as Rayleigh fading, Quadrature and Power control. His Machine learning research includes themes of Iris flower data set and Fuzzy classification systems. His Infinite impulse response study in the realm of Digital filter interacts with subjects such as Median filter.

His most cited work include:

• Noise reduction in zero crossing detection by predictive digital filtering (147 citations)
• Industrial applications of soft computing: a review (131 citations)
• Angular acceleration measurement: a review (102 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Control theory, Artificial intelligence, Artificial neural network, Soft computing and Algorithm. His Control theory study incorporates themes from Digital filter, Polynomial and Filter. His research integrates issues of Low-pass filter, Linear filter and Signal processing in his study of Digital filter.

His Artificial intelligence study frequently links to other fields, such as Machine learning. His Artificial neural network research is multidisciplinary, relying on both Fault, Fault detection and isolation, Nonlinear system and Power control. His studies in Soft computing integrate themes in fields like Computational intelligence, Genetic algorithm, Hybrid system, Intelligent control and Intelligent decision support system.

He most often published in these fields:

• Control theory (32.13%)
• Artificial intelligence (22.38%)
• Artificial neural network (17.33%)

What were the highlights of his more recent work (between 2007-2019)?

• Artificial intelligence (22.38%)
• Mathematical optimization (10.11%)
• Harmony search (4.69%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Mathematical optimization, Harmony search, Artificial immune system and Electronic engineering. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition. His work investigates the relationship between Artificial immune system and topics such as Fault detection and isolation that intersect with problems in Anomaly detection.

His studies deal with areas such as Control theory, Pulse generator, Active filter and Electrical engineering as well as Electronic engineering. In his work, Fundamental frequency is strongly intertwined with Signal generator, which is a subfield of Control theory. Artificial neural network is closely attributed to Algorithm in his work.

Between 2007 and 2019, his most popular works were:

• A general framework for statistical performance comparison of evolutionary computation algorithms (92 citations)
• Real-Time Systems Design and Analysis : Tools for the Practitioner (63 citations)
• UNI-MODAL AND MULTI-MODAL OPTIMIZATION USING MODIFIED HARMONY SEARCH METHODS (53 citations)

In his most recent research, the most cited papers focused on:

• Artificial intelligence
• Electrical engineering
• Machine learning

His primary areas of investigation include Harmony search, Artificial intelligence, Mathematical optimization, Artificial immune system and Metaheuristic. His Harmony search research incorporates themes from Optimization algorithm, Optimization problem and Nonlinear system. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Pattern recognition.

His research is interdisciplinary, bridging the disciplines of Fuzzy logic and Machine learning. As part of one scientific family, Seppo J. Ovaska deals mainly with the area of Artificial immune system, narrowing it down to issues related to the Detector, and often Algorithm, Fault and Artificial neural network. The Metaheuristic study which covers Evolutionary computation that intersects with Genetic algorithm and Variety.