MARC details
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04091ntm a2200337 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20251125110902.0 |
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t||||fr|||| 000 0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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ta |
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240605t20242024my a|||fr|||| 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0009876 (Local) |
| Qualifying information |
Hardback |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMPSA |
| Language of cataloging |
eng |
| Transcribing agency |
UMP |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FTKEE .H45 2024 r Thesis |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Mohd Helmi Bin Suid, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
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| Title |
Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems / |
| Statement of responsibility, etc. |
Mohd Helmi Bin Suid, |
| 260 #1 - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Kuantan, Pahang : |
| Name of publisher, distributor, etc. |
UMPSA, |
| Date of publication, distribution, etc. |
2024 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Date of production, publication, distribution, manufacture, or copyright notice |
© 2024 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xiv, 212 pages : |
| Other physical details |
illustrations (some color) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
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| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
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| Source |
rdacarrier |
| Carrier type term |
volume |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
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| Source |
rda |
| File type |
text file |
| Encoding format |
PDF |
| 500 ## - GENERAL NOTE |
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| General note |
Faculty of Electrical & Electronics Engineering Technology |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2024 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
In the rapidly developing landscape of control engineering within electrical and electronics engineering, the study addresses critical challenges posed by the escalating complexity of system designs. As technology continues to advance, the demand for effective methodologies to design, analyse, and synthesize complex system models becomes vital. In response to this imperative, researchers have increasingly turned to optimization-based approaches, with the Sine Cosine Algorithm (SCA) emerging as a prominent solution. However, existing limitations in terms of convergence accuracy and local optima stagnation have prompted the introduction of innovative improvements in this study. The Nonlinear Sine Cosine Algorithm (NSCA) is introduced as a key extension, incorporating a versatile nonlinear decreasing gain into the transition parameter mechanism. This enhancement offers a tailored balance between exploration and exploitation, aligning with the specific requirements of complex electrical and electronics engineering problems. Moreover, the Nonlinear Sine Cosine Algorithm-Safe Experimentation Dynamic (NSCA-SED) introduces a hybridization of multi-agent and single-agent algorithms, presenting a dynamic approach with random perturbation to navigate search trajectories effectively, and release design parameters that might be trapped in local optima. The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). The applications extend beyond established optimization problems, addressing contemporary experiments in control engineering, including Model Order Reduction, Nonlinear System Identification, and Data-driven Control. Simulation results underscore the robustness and superiority of the NSCA and NSCA-SED algorithms in these contexts, showcasing improvements ranging from 13.97% to 97.17% for Model Order Reduction, 17.76% to 99.37% for Nonlinear System Identification, and 84.51% to 89.47% for Data-driven Control when compared to the standard SCA. In summary, this study not only contributes advancements to optimization algorithms but also directly addresses and enhances methodologies in electrical and electronics engineering. By overcoming the limitations of existing approaches, the NSCA and NSCA-SED algorithms stand as valuable tools in the collection of control engineers, facilitating the design and optimization of complex systems in contemporary electrical and electronics applications. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
Faculty of Electrical & Electronics Engineering Technology |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Theses |
| General subdivision |
Dissertations |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |