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Relevant bibliographies by topics / FUZZY-GSA

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Journal articles

Academic literature on the topic 'FUZZY-GSA'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "FUZZY-GSA"

1

Shyla, S. Immaculate, and S. S. Sujatha. "An Efficient Automatic Intrusion Detection in Cloud Using Optimized Fuzzy Inference System." International Journal of Information Security and Privacy 14, no. 4 (2020): 22–41. http://dx.doi.org/10.4018/ijisp.2020100102.

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Security incidents such as denial of service (DoS), scanning, malware code injection, viruses, worms, and password cracking are becoming common in a cloud environment that affects companies and may produce a financial loss if not detected in time. Such problems are handled by presenting an intrusion detection system (IDS) into the cloud. The existing cloud IDSs affect low detection accuracy, high false detection rate, and execution time. To overcome this problem, in this article, a gravitational search algorithm-based fuzzy inference system (GSA-FIS) is developed as intrusion detection. In thi

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2

Chao, Chun-Tang, Ming-Tang Liu, Juing-Shian Chiou, Yi-Jung Huang, and Chi-Jo Wang. "A GSA-based adaptive fuzzy PID-controller for an active suspension system." Engineering Computations 33, no. 6 (2016): 1659–67. http://dx.doi.org/10.1108/ec-08-2015-0240.

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Purpose – The purpose of this paper is to propose a novel design for determining the optimal hybrid fuzzy PID-controller of an active automobile suspension system, employing the gravitational search algorithm (GSA). Design/methodology/approach – The hybrid fuzzy PID-controller structure is an improvement to fuzzy PID-controller by incorporating a fast learning PID-controller. Findings – The GSA can adjust the parameters of the PID-controller to achieve the optimal performance. Research limitations/implications – The GSA may have the advantage of quick convergence, but the required computation

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3

Bardamova, Marina, Anton Konev, Ilya Hodashinsky, and Alexander Shelupanov. "A Fuzzy Classifier with Feature Selection Based on the Gravitational Search Algorithm." Symmetry 10, no. 11 (2018): 609. http://dx.doi.org/10.3390/sym10110609.

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This paper concerns several important topics of the Symmetry journal, namely, pattern recognition, computer-aided design, diversity and similarity. We also take advantage of the symmetric and asymmetric structure of a transfer function, which is responsible to map a continuous search space to a binary search space. A new method for design of a fuzzy-rule-based classifier using metaheuristics called Gravitational Search Algorithm (GSA) is discussed. The paper identifies three basic stages of the classifier construction: feature selection, creating of a fuzzy rule base and optimization of the an

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Yu, Xiaobing, Xianrui Yu, and Xueying Zhang. "Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 11007–22. http://dx.doi.org/10.3233/jifs-202132.

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Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system.

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Pramana, Setia, and Imam Habib Pamungkas. "Improvement Method of Fuzzy Geographically Weighted Clustering using Gravitational Search Algorithm." Jurnal Ilmu Komputer dan Informasi 11, no. 1 (2018): 10. http://dx.doi.org/10.21609/jiki.v11i1.580.

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Geo-demographic analysis (GDA) is a useful method to analyze information based on location, utilizing several spatial analysis explicitly. One of the most efficient and commonly used method is Fuzzy Geographically Weighted Clustering (FGWC). However, it has a limitation in obtaining local optimal solution in the centroid initialization. A novel approach integrating Gravitational Search Algorithm (GSA) with FGWC is proposed to obtain global optimal solution leading to better cluster quality. Several cluster validity indexes are used to compare the proposed methods with the FGWC using other opti

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6

Mashfufah, Syayidati, Indah Manfaati Nur, and Moh Yamin Darsyah. "Fuzzy Geographically Weighted Clustering dengan Gravitational Search Algorithm pada Kasus Penyandang Masalah Kesejahteraan Sosial di Provinsi Jawa Tengah." Jurnal Litbang Edusaintech 2, no. 1 (2021): 27–36. http://dx.doi.org/10.51402/jle.v2i1.10.

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One of the indicators of the success of social welfare development in Central Java was decreasing the population of people with social welfare problems (PMKS). One exertion that can be done was grouping or clustering the areas in Central Java-based on 26 indicators of PMKS. Fuzzy Geographically Weighted Clustering (FGWC) algorithm is a clustering analysis that observing the effect of the area. However, FGWC has a limitation in the initialization centroid phase that makes it trapped to local optimal. The limitation can be addressed with the Gravitational Search Algorithm (GSA) approach. The pur

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7

Hashim, H. A., and M. A. Abido. "Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study." Computational Intelligence and Neuroscience 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/704301.

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This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel h

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Kherabadi, Hossein Azadi, Sepehr Ebrahimi Mood, and Mohammad Masoud Javidi. "Mutation: A New Operator in Gravitational Search Algorithm Using Fuzzy Controller." Cybernetics and Information Technologies 17, no. 1 (2017): 72–86. http://dx.doi.org/10.1515/cait-2017-0006.

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Abstract Gravitational Search Algorithm (GSA) isanovel meta-heuristic algorithm. Despite it has high exploring ability, this algorithm faces premature convergence and gets trapped in some problems, therefore it has difficulty in finding the optimum solution for problems, which is considered as one of the disadvantages of GSA. In this paper, this problem has been solved through definingamutation function which uses fuzzy controller to control mutation parameter. The proposed method has been evaluated on standard benchmark functions including unimodal and multimodal functions; the obtained resul

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9

Javanbakht, Mohammad, and Mohammad Javad Mahmoodabadi. "Achieving More Stringent Levels of Comfort via an Adaptive Fuzzy Controller Optimized by the Gravitational Search Algorithm for a Half-Body Car Model." Volume 24, No 3, September 2019 24, no. 3 (2019): 567–77. http://dx.doi.org/10.20855/jav.2019.24.31399.

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An optimal adaptive fuzzy controller is designed to achieve more stringent levels of comfort for a half-body car model. This aim will be fulfilled by reducing road disturbances and decreasing the acceleration of the body. The proposed controller consists of two adaptive fuzzy controllers with two fuzzy systems. Each one has two inputs, one output and twenty five linguistic fuzzy IF-THEN rules. Every input has five Gaussian membership functions and uses the product inference engine, singleton fuzzifier and the centre average defuzzifier. In order to determine the optimal parameters for the Adap

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10

Bounar, N., S. Labdai, and A. Boulkroune. "PSO–GSA based fuzzy sliding mode controller for DFIG-based wind turbine." ISA Transactions 85 (February 2019): 177–88. http://dx.doi.org/10.1016/j.isatra.2018.10.020.

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