An Improved Particle Swarm Optimization Algorithm for Traveling Salesman Problems

Yan, Xuesong; Yang, Fan; Liang, Qingzhong; Liu, Chao

doi:10.14257/ijca.2017.10.2.16

Cited by 3 publications

(5 citation statements)

References 21 publications

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“…Table 1: Objective function and optimal threshold based on Kapur's entropy criteria. For PSO, other control parameters w_max =0.4, w_min=0.1, c1=1, c2=2 were used as defined in [38]. Table 1 provides the maximum entropy evaluated for the entire test images and the value of the optimal thresholds corresponding to best entropy by both the algorithms.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…(n=1.2…, N:m=1.2…m) (8) where, when Xm,n[0,1], and 0< µ ≤ 4, the system is in a chaos state and its track is with favorable ergodicity [38].…”

Section: A Generating the Initial Population By Using Chaos Methodsmentioning

confidence: 99%

“…The standard bat algorithm has many advantages; one of them is that it can get quick convergence at initial stages by switching from exploration to exploitation. This makes it an efficient algorithm when a quick solution is needed [31][32] [37][38][39]. In order to improve the performance, many modifications have been added to increase the diversity of the solution and to enhance the performance of the standard Bat algorithm as mentioned previously.…”

Section: Update Process Of Loudness and Pulse Emission Ratementioning

confidence: 99%

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A Novel Improved Bat Algorithm Based Image Multi-Thresholding

Mokhtari¹,

Kimour²

2019

IJEEI

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Image segmentation is a very important activity in computer vision, where critical applications are highly dependent on the efficacy of such activity. To enhance the efficiency of such automated activity, meta-heuristic algorithms to optimally elucidate multi-level image segmentation problems have been proposed in the literature. Because of the advantages in terms of efficiency and convergence speed of the bat algorithm, this paper presents a novel improvement of such algorithm for solving the image multi-thresholding problem. The algorithm leads to speed up the convergence and increase diversity through the utilization of an appropriate crossover operator and chaotic sequences, with the use of Kapur's entropy as the optimized objective function. The proposed method produces segmented images with optimal values for the threshold in few iterations. Through the comparative analysis based on standard deviation, peak signal to noise ratio (PSNR) and segmented image quality, it is observed that the effectiveness of the proposed method, validated using different standard test images, outperforms well-known metaheuristic-based optimization techniques.

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Section: Experiments and Discussionmentioning

confidence: 99%

“…(n=1.2…, N:m=1.2…m) (8) where, when Xm,n[0,1], and 0< µ ≤ 4, the system is in a chaos state and its track is with favorable ergodicity [38].…”

Section: A Generating the Initial Population By Using Chaos Methodsmentioning

confidence: 99%

Section: Update Process Of Loudness and Pulse Emission Ratementioning

confidence: 99%

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A Novel Improved Bat Algorithm Based Image Multi-Thresholding

Mokhtari¹,

Kimour²

2019

IJEEI

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“…Fuzzy three-dimensional logic, also known as 3D fuzzy logic [8][9][10][11][12][13][14][15][16], is an extension of traditional fuzzy logic that allows for modelling three-dimensional systems using threedimensional fuzzy sets.…”

Section: Tree-dimensional Fuzzy Logicmentioning

confidence: 99%

“…In 1992, Kaoru Hirota proposed a solution to this problem in a paper titled "Three-Dimensional Fuzzy Control." [12][13][14][15] Hirota's approach involved dividing a three-dimensional fuzzy set into a series of two-dimensional slices, each of which represented a different level of membership in the set. By representing the fuzzy set in this way, it was possible to perform calculations more efficiently and accurately.…”

Section: Tree-dimensional Fuzzy Logicmentioning

confidence: 99%

Three-Dimensional Fuzzy Logic Applied to DC Voltage Regulation in Active Power Filter of PV System

2023

ijSmartGrid

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This paper deals with the application of three-dimensional fuzzy logic to DC voltage regulation in active power filters exploration, the benefits of this approach, and examples of its application on power quality improvement of PV smart grid system installation. APF are important components of power systems that are used to minimize harmonic distortion and improve power quality. DC voltage regulation is a critical component of active power filters, and traditional control systems have limitations in their ability to account for complex and nuanced conditions, leading to less accurate control and less efficient use of resources. Three-dimensional fuzzy logic is an advanced approach to control systems that allows for more precise and nuanced evaluations of conditions, compering to classical fuzzy logic or the type 2, leading to more accurate control and more efficient use of resources, Three-dimensional fuzzy logic algorithm will be proposed and programed under MATLAB Simulink to control the APF and simulation results are represented and analysed.

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