Aki Sorsa

Aki Sorsa

Oulun yliopisto

H-index: 17

Europe-Finland

About Aki Sorsa

Aki Sorsa, With an exceptional h-index of 17 and a recent h-index of 12 (since 2020), a distinguished researcher at Oulun yliopisto, specializes in the field of Barkhausen noise, evolutionary algorithms, intelligent systems.

His recent articles reflect a diverse array of research interests and contributions to the field:

Machine learning assisted identification of grey-box hot metal desulfurization model

Offset-free model predictive control using Koopman-Wiener models

Grinding burn classification with surface Barkhausen noise measurements

Data-Based Modelling of Chemical Oxygen Demand for Industrial Wastewater Treatment

Upstream purification, Catalyst Development and Kinetic Modeling for the Production of Lignocellulosic Bio-based Furanics

Neural Network Model Identification Studies to Predict Residual Stress of a Steel Plate Based on a Non-destructive Barkhausen Noise Measurement

Sub-Surface analysis of grinding burns with Barkhausen noise measurements

Systematic data-driven modeling of bimetallic catalyst performance for the hydrogenation of 5-ethoxymethylfurfural with variable selection and regularization

Aki Sorsa Information

University

Position

Research Scientist of Control Engineering

Citations(all)

983

Citations(since 2020)

510

Cited By

644

hIndex(all)

17

hIndex(since 2020)

12

i10Index(all)

30

i10Index(since 2020)

17

Email

University Profile Page

Oulun yliopisto

Google Scholar

View Google Scholar Profile

Aki Sorsa Skills & Research Interests

Barkhausen noise

evolutionary algorithms

intelligent systems

Top articles of Aki Sorsa

Title

Journal

Author(s)

Publication Date

Machine learning assisted identification of grey-box hot metal desulfurization model

Materials and Manufacturing Processes

Tero Vuolio

Ville–Valtteri Visuri

Aki Sorsa

Timo Paananen

Sakari Tuomikoski

...

2023/11/18

Offset-free model predictive control using Koopman-Wiener models

Kristian Tiiro

2023/9/19

Grinding burn classification with surface Barkhausen noise measurements

Suvi Santa-aho

Minnamari Vippola

Aki Sorsa

Mika Ruusunen

2023/8/1

Data-Based Modelling of Chemical Oxygen Demand for Industrial Wastewater Treatment

Applied Sciences

Henri Pörhö

Jani Tomperi

Aki Sorsa

Esko Juuso

Jari Ruuska

...

2023/7/4

Upstream purification, Catalyst Development and Kinetic Modeling for the Production of Lignocellulosic Bio-based Furanics

ACHEMA Congress

A Jakob

M Grilc

B Likozar

H Valkama

B Rathnayake

...

2022

Neural Network Model Identification Studies to Predict Residual Stress of a Steel Plate Based on a Non-destructive Barkhausen Noise Measurement

Machine Learning in Industry

Tero Vuolio

Olli Pesonen

Aki Sorsa

Suvi Santa-aho

2022

Sub-Surface analysis of grinding burns with Barkhausen noise measurements

Materials

Aki Sorsa

Mika Ruusunen

Suvi Santa-Aho

Minnamari Vippola

2022/12/24

Systematic data-driven modeling of bimetallic catalyst performance for the hydrogenation of 5-ethoxymethylfurfural with variable selection and regularization

Industrial & Engineering Chemistry Research

Pekka Uusitalo

Aki Sorsa

Fernando Russo Abegão

Markku Ohenoja

Mika Ruusunen

2022/3/31

Mathematical analysis and update of ADM1 model for biomethane production by anaerobic digestion

Fermentation

Stefano Bertacchi

Mika Ruusunen

Aki Sorsa

Anu Sirviö

Paola Branduardi

2021/10/21

Application of a genetic algorithm based model selection algorithm for identification of carbide-based hot metal desulfurization

Applied Soft Computing

Tero Vuolio

Ville-Valtteri Visuri

Aki Sorsa

Seppo Ollila

Timo Fabritius

2020/7/1

Detailed Barkhausen noise and microscopy characterization of Jominy end-quench test sample of CF53 steel

Journal of materials science

Suvi Santa-aho

Aki Sorsa

Mari Honkanen

Minnamari Vippola

2020/4

See List of Professors in Aki Sorsa University(Oulun yliopisto)