Harmony Search Algorithm and Fuzzy Logic Theory: An Extensive Review from Theory to Applications

Nasir, Mohammad; Sadollah, Ali; Grzegorzewski, Przemysław; Lee, Ji Eun; Geem, Zong Woo

doi:10.3390/math9212665

Cited by 12 publications

(6 citation statements)

References 135 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a result, the results of these assessments are of paramount importance to institutions of higher music education. (Nasir et al, 2021;Wu et al, 2022) Though helpful, these changes haven't addressed the real challenges that music majors face. As a result of the increased formality introduced by some music programmes in order to more easily achieve final assessment criteria, it has become increasingly difficult to make meaningful comparisons between the musical ability of students enrolled in different programmes.…”

Section: Iiliterature Reviewmentioning

confidence: 99%

Fuzzy Integrated Optimization-Based College and University Music Education Teaching System

2024

jes

View full text Add to dashboard Cite

Fuzzy integrated optimization refers to the application of fuzzy logic techniques in the optimization process to handle uncertain or imprecise information effectively. In traditional optimization problems, precise data and deterministic relationships are assumed. This paper proposes the construction of a teaching system for music education in colleges and universities based on fuzzy integrated optimization. Fuzzy logic techniques are applied to handle uncertain or imprecise information inherent in the optimization process. traditional optimization methods that assume precise data and deterministic relationships, fuzzy integrated optimization allows for the modeling of uncertainties in music education settings. By incorporating fuzzy logic into the design of the teaching system, educators can better adapt to the diverse learning needs and preferences of students. The implementation of the teaching system for music education in colleges and universities based on fuzzy integrated optimization yielded significant improvements across various performance metrics. Student engagement levels increased by an average of 25%, with a corresponding rise in satisfaction rates by 30%. Additionally, learning outcomes showed measurable enhancements, with a 20% increase in average test scores compared to traditional teaching methods. The adaptive nature of the teaching system resulted in a 15% reduction in dropout rates, indicating improved student retention and progression through music education programs. Educators reported a 40% increase in efficiency in lesson planning and delivery, attributed to the system's ability to provide personalized recommendations and insights tailored to individual student needs.

show abstract

Section: Iiliterature Reviewmentioning

confidence: 99%

Fuzzy Integrated Optimization-Based College and University Music Education Teaching System

2024

jes

View full text Add to dashboard Cite

show abstract

“…A novel iteration of particle swarm optimization (PSO) has been implemented to regulate the frequency and voltage of multi-area power systems 7 . The harmony search algorithm 8 is a meta-heuristic optimization algorithm inspired by the musical improvisation process. It's used to solve optimization problems and has been adapted for tuning PID controllers in various control applications, including LFC.…”

Section: Introductionmentioning

confidence: 99%

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Gopi,

Alluraiah,

Kumar

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as “Porpoising”. This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

show abstract

“…The word fuzzy refers to things that appear not to be adequate or ambiguous [6]. Numerous-valued logic allows an idea to have some degree of reality [7]. It can simulate human experience and decision-making.…”

Section: Introductionmentioning

confidence: 99%

Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks

Azizan

Sathasivam

Ali

et al. 2023

Axioms

View full text Add to dashboard Cite

This work proposed a new hybridised network of 3-Satisfiability structures that widens the search space and improves the effectiveness of the Hopfield network by utilising fuzzy logic and a metaheuristic algorithm. The proposed method effectively overcomes the downside of the current 3-Satisfiability structure, which uses Boolean logic by creating diversity in the search space. First, we included fuzzy logic into the system to make the bipolar structure change to continuous while keeping its logic structure. Then, a Genetic Algorithm is employed to optimise the solution. Finally, we return the answer to its initial bipolar form by casting it into the framework of the hybrid function between the two procedures. The suggested network’s performance was trained and validated using Matlab 2020b. The hybrid techniques significantly obtain better results in terms of error analysis, efficiency evaluation, energy analysis, similarity index, and computational time. The outcomes validate the significance of the results, and this comes from the fact that the proposed model has a positive impact. The information and concepts will be used to develop an efficient method of information gathering for the subsequent investigation. This new development of the Hopfield network with the 3-Satisfiability logic presents a viable strategy for logic mining applications in future.

show abstract

Harmony Search Algorithm and Fuzzy Logic Theory: An Extensive Review from Theory to Applications

Cited by 12 publications

References 135 publications

Fuzzy Integrated Optimization-Based College and University Music Education Teaching System

Fuzzy Integrated Optimization-Based College and University Music Education Teaching System

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks

Contact Info

Product

Resources

About