Weighted Fuzzy Production Rule Extraction Using Modified Harmony Search Algorithm and BP Neural Network Framework

Li, Hang-Cheng; Zhou, Kai-Qing; Mo, Liping; Zain, Azlan Mohd; Qin, Feng

doi:10.1109/access.2020.3029966

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…The efficacy of the LAGA-BPNNs approach was demonstrated through a case study involving the Wisconsin breast cancer dataset. Meanwhile, in Li et al (2020a), the authors also investigated the applicability of the harmonic search algorithm to this knowledge extraction framework.…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

Advances on intelligent algorithms for scientific computing: an overview

et al. 2023

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The field of computer science has undergone rapid expansion due to the increasing interest in improving system performance. This has resulted in the emergence of advanced techniques, such as neural networks, intelligent systems, optimization algorithms, and optimization strategies. These innovations have created novel opportunities and challenges in various domains. This paper presents a thorough examination of three intelligent methods: neural networks, intelligent systems, and optimization algorithms and strategies. It discusses the fundamental principles and techniques employed in these fields, as well as the recent advancements and future prospects. Additionally, this paper analyzes the advantages and limitations of these intelligent approaches. Ultimately, it serves as a comprehensive summary and overview of these critical and rapidly evolving fields, offering an informative guide for novices and researchers interested in these areas.

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Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

Advances on intelligent algorithms for scientific computing: an overview

et al. 2023

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“…The above discussed algorithms achieve a better controller performance compared to classic fuzzy PID control technique and also suffer from the drawbacks as discussed previously. In [33] a global optimal adaptive HAS is employed to optimize the performance of the neural network and thereby enhance the training efficiency of the model. Results show that the adaptive HAS enhanced the accuracy of the neural network.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Dual fuzzy logic PID controller based regulating of dc motor speed control with optimization using Harmony Search algorithm

Khather,

Ibrahim,

Ibrahim

2023

EEJET

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This paper discusses the implementation of a Proportional-Integral-Derivative (PID) controller for regulating the speed of a closed loop four quadrant chopper fed DC motor. The PID controller is combined with a Dual Fuzzy Logic Controller to form a DFPID controller for enhancing the performance of speed control of the DC motor. The DFLC is optimized using a metaheuristic algorithm known as Harmony Search Algorithm (HSA). The major aim of this research is to gain an effective control over the speed of the motor in the closed loop environment. For achieving this, the parameters for the DFPID are selected through time domain analysis which aims to satisfy the requisites such as settling time and peak overshoot. Initially, the fuzzy logic controller in the DFPID controls the coefficients of the PID achievement gain an effective control over the system error and rate of error change. Further, the DFPID is improved by the HAS for obtaining a precise correction. The solutions obtained by tuning the DFPID controller are evaluated from simulation analysis conducted on a MATLAB/SIMULINK platform. The closed loop performance is analyzed in both time and frequency domain analysis and the performance of DFPID is optimized using the HSA algorithm to obtain precise value of the control process. As observed from the Simulation analysis, the DFPID-HSA generates optimized control signals to the DC motor for controlling the speed. The performance of the intended speed control approach is analyzed in terms of different evaluation metrics such as motor speed, torque and armature current. Experimental outcomes show that the proposed approach achieves better control performance and faster speed of DC motor compared to conventional PID controllers and SMC controllers

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“…Li et al artificially minimized the thrust of bovine cortical bone VAD, and proposed an information feedback adaptive harmony search (IFSHS) algorithm, which evaluated the optimization parameters and fed back the evaluation information into the dynamic adjustment of the parameters 33 . Li et al proposed an improved harmonic search algorithm, called the global optimal adaptive harmony search algorithm (AGOHS), which overcomes the problem of traditional HS parameter setting 34 . Mahmoudi et al adjusted the bandwidth (BW), pitch adjustment rate (PAR) and other parameters of the harmonic search algorithm through the membership function and fuzzy rules designed to improve the performance of the algorithm 35 .…”

Section: Introductionmentioning

confidence: 99%

A novel intelligent global harmony search algorithm based on improved search stability strategy

Wang

Ouyang

Zhang

et al. 2023

Sci Rep

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Harmony search (HS) is a new swarm intelligent algorithm inspired by the process of music improvisation. Over the past decade, HS algorithm has been applied to many practical engineering problems. However, for some complex practical problems, there are some remaining issues such as premature convergence, low optimization accuracy and slow convergence speed. To address these issues, this paper proposes a novel intelligent global harmony search algorithm based on improved search stability strategy (NIGHS). In the search process, NIGHS uses the adaptive mean of harmony memory library to build a stable trust region around the global best harmony, and proposes a new coupling operation based on linear proportional relation, so that the algorithm can adaptively adjust the ability of exploration and exploitation in the search process and avoid premature convergence. In addition, the dynamic Gauss fine-tuning is adopted in the stable trust region to accelerate the convergence speed and improve the optimization accuracy. The common CEC2017 test functions are employed to test the proposed algorithm, the results show that NIGHS algorithm has a faster convergence speed and better optimization accuracy compared to the HS algorithm and its improved versions.

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Weighted Fuzzy Production Rule Extraction Using Modified Harmony Search Algorithm and BP Neural Network Framework

Cited by 11 publications

References 33 publications

Advances on intelligent algorithms for scientific computing: an overview

Advances on intelligent algorithms for scientific computing: an overview

Dual fuzzy logic PID controller based regulating of dc motor speed control with optimization using Harmony Search algorithm

A novel intelligent global harmony search algorithm based on improved search stability strategy

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