Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor. / Haus, Benedikt; Yap, Jin Siang; Schaefer, Lennart; Mercorelli, Paolo.

Soft Computing: Theories and Applications - Proceedings of SoCTA 2021. ed. / Rajesh Kumar; Chang Wook Ahn; Tarun K. Sharma; Om Prakash Verma; Anand Agarwal. Cham : Springer Science and Business Media Deutschland GmbH, 2022. p. 527-537 (Lecture Notes in Networks and Systems; Vol. 425).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Haus, B, Yap, JS, Schaefer, L & Mercorelli, P 2022, Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor. in R Kumar, CW Ahn, TK Sharma, OP Verma & A Agarwal (eds), Soft Computing: Theories and Applications - Proceedings of SoCTA 2021. Lecture Notes in Networks and Systems, vol. 425, Springer Science and Business Media Deutschland GmbH, Cham, pp. 527-537, 6th International Conference on Soft Computing: Theories and Applications, SoCTA 2021, Kota, India, 17.12.21. https://doi.org/10.1007/978-981-19-0707-4_48

APA

Haus, B., Yap, J. S., Schaefer, L., & Mercorelli, P. (2022). Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor. In R. Kumar, C. W. Ahn, T. K. Sharma, O. P. Verma, & A. Agarwal (Eds.), Soft Computing: Theories and Applications - Proceedings of SoCTA 2021 (pp. 527-537). (Lecture Notes in Networks and Systems; Vol. 425). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-0707-4_48

Vancouver

Haus B, Yap JS, Schaefer L, Mercorelli P. Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor. In Kumar R, Ahn CW, Sharma TK, Verma OP, Agarwal A, editors, Soft Computing: Theories and Applications - Proceedings of SoCTA 2021. Cham: Springer Science and Business Media Deutschland GmbH. 2022. p. 527-537. (Lecture Notes in Networks and Systems). https://doi.org/10.1007/978-981-19-0707-4_48

Bibtex

@inbook{71587219c4a14ee59a5855adfb2d5ca3,
title = "Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor",
abstract = "This contribution deals with the identification of gloss as a function of roughness using particle swarm optimization (PSO) methods. The proposed PSO methods use a least squares method (LSM) as a cost function to be optimized. The nonparametric identification structure uses a Gaussian regressor characterized by three parameters to be estimated. Three different algorithms are proposed: a global classical PSO, an intertwined PSO structure and a PSO structure combined with a linear regression method obtained using a logarithmical transformation. Results using measured data are shown at the end of this analysis to compare the three different techniques.",
keywords = "Manufacturing applications, Nonparametric identification, Particle swarm optimization, Engineering",
author = "Benedikt Haus and Yap, {Jin Siang} and Lennart Schaefer and Paolo Mercorelli",
year = "2022",
doi = "10.1007/978-981-19-0707-4_48",
language = "English",
isbn = "978-981-19-0706-7",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "527--537",
editor = "Rajesh Kumar and Ahn, {Chang Wook} and Sharma, {Tarun K.} and Verma, {Om Prakash} and Anand Agarwal",
booktitle = "Soft Computing",
address = "Germany",
note = "6th International Conference on Soft Computing: Theories and Applications, SoCTA 2021, SoCTA 2021 ; Conference date: 17-12-2021 Through 19-12-2021",

}

RIS

TY - CHAP

T1 - Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor

AU - Haus, Benedikt

AU - Yap, Jin Siang

AU - Schaefer, Lennart

AU - Mercorelli, Paolo

N1 - Conference code: 6

PY - 2022

Y1 - 2022

N2 - This contribution deals with the identification of gloss as a function of roughness using particle swarm optimization (PSO) methods. The proposed PSO methods use a least squares method (LSM) as a cost function to be optimized. The nonparametric identification structure uses a Gaussian regressor characterized by three parameters to be estimated. Three different algorithms are proposed: a global classical PSO, an intertwined PSO structure and a PSO structure combined with a linear regression method obtained using a logarithmical transformation. Results using measured data are shown at the end of this analysis to compare the three different techniques.

AB - This contribution deals with the identification of gloss as a function of roughness using particle swarm optimization (PSO) methods. The proposed PSO methods use a least squares method (LSM) as a cost function to be optimized. The nonparametric identification structure uses a Gaussian regressor characterized by three parameters to be estimated. Three different algorithms are proposed: a global classical PSO, an intertwined PSO structure and a PSO structure combined with a linear regression method obtained using a logarithmical transformation. Results using measured data are shown at the end of this analysis to compare the three different techniques.

KW - Manufacturing applications

KW - Nonparametric identification

KW - Particle swarm optimization

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85132044524&partnerID=8YFLogxK

U2 - 10.1007/978-981-19-0707-4_48

DO - 10.1007/978-981-19-0707-4_48

M3 - Article in conference proceedings

AN - SCOPUS:85132044524

SN - 978-981-19-0706-7

T3 - Lecture Notes in Networks and Systems

SP - 527

EP - 537

BT - Soft Computing

A2 - Kumar, Rajesh

A2 - Ahn, Chang Wook

A2 - Sharma, Tarun K.

A2 - Verma, Om Prakash

A2 - Agarwal, Anand

PB - Springer Science and Business Media Deutschland GmbH

CY - Cham

T2 - 6th International Conference on Soft Computing: Theories and Applications, SoCTA 2021

Y2 - 17 December 2021 through 19 December 2021

ER -