Improved Type2-NPCM Fuzzy Clustering Algorithm Based on Adaptive Particle Swarm Optimization for Takagi–Sugeno Fuzzy Modeling Identification

Houcine, Lassad; Mohamed, Bouzbida; Châari, Abdelkader

doi:10.1007/s40815-020-00881-2

Cited by 7 publications

(4 citation statements)

References 28 publications

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“…e traditional FCM algorithm is sensitive to the initial value of the cluster center, and the clustering effect is different with the number of clusters, and it is easy to fall into the local extremum. In order to solve this problem effectively, the improved magnetic optimization algorithm (IMOA) is used to optimize FCM [13], that is, the IMOA-FCM algorithm. IMOA-FCM algorithm is the main idea is to make data in a multidimensional space object as a fixed point and the magnetic particles as movable point, and the magnetic particles are no longer in von Neumann neighborhood structure configuration, but spread randomly in the search space, and each magnetic particle has a coding dimension of (1, c × Dim) and clustering center on behalf of all of the initial value, and the code is shown in Figure 1.…”

Section: Data Mining Based On Improved Fuzzy Clusteringmentioning

confidence: 99%

Research on Comprehensive Evaluation of Economic Management Performance Based on Improved Fuzzy Clustering Algorithm

Shi

2022

Security and Communication Networks

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In order to solve the problems of low recall rate and precision rate, high error rate, and long evaluation time in traditional evaluation methods, a comprehensive evaluation of economic management performance based on an improved fuzzy clustering algorithm is designed. The improved magnetic optimization algorithm was used to optimize the fuzzy C-mean algorithm, the improved fuzzy clustering algorithm was completed, and the improved fuzzy clustering algorithm was used to mine the economic management performance data. Using data mining findings and AHP’s weighting formula, a complete method for evaluating economic management effectiveness was developed. The BP neural network was improved using a genetic algorithm based on the index weight calculation findings, and the full-assessment model of economic management performance was constructed. Using this approach, it is possible to accurately and quickly assess the economic management performance of a company with a high rate of recall and accuracy; the error rate of a thorough assessment ranges between −3 percent and 4 percent; the average duration for an assessment is 0.81 seconds.

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Section: Data Mining Based On Improved Fuzzy Clusteringmentioning

confidence: 99%

Research on Comprehensive Evaluation of Economic Management Performance Based on Improved Fuzzy Clustering Algorithm

Shi

2022

Security and Communication Networks

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“…They used the LMBP neural network to establish a flexo spot color matching model and found that the algorithm has higher accuracy and a better approximation effect. However, the final color matching error is still relatively large, and this method needs to be improved [ 15 ]. Liu et al proposed five algorithm models for flexo spot color matching, namely, LMBP neural network algorithm model, Bayesian regularization algorithm model, conjugate gradient-based algorithm model, BFGS quasi-Newton algorithm model, and tangent quasi-Newton algorithm model, and discuss them separately.…”

Section: Literature Reviewmentioning

confidence: 99%

“…ey used the LMBP neural network to establish a flexo spot color matching model and found that the algorithm has higher accuracy and a better approximation effect. However, the final color matching error is still relatively large, and this method needs to be improved [15]. e color matching accuracy and accuracy have been improved, and they have certain practicability.…”

Section: Literature Reviewmentioning

confidence: 99%

Extraction and Dyeing Techniques of Traditional Vegetable Dyestuffs

2022

International Journal of Analytical Chemistry

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In order to explore the influencing factors of the extraction of vegetable dyes, a research method for the extraction and dyeing of traditional vegetable dyes was proposed. In this paper, the effects of extraction temperature, extraction time, and the ratio of solid to liquid on the extraction effect were discussed through orthogonal experiments. The dyeing process of silk extract was used in this study. The silk fabric was directly dyed with natural dye from peach leaves, compared with the three dyeing methods of premordant, same-bath mordant, and postmordant, and the color fastness to soaping of the dyed fabric was tested. The results show that the color fastness to soaping of leaf-dyed fabrics conforms to the national standard of superior grades, which effectively proves the correctness of the algorithm and model nature and superiority.

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“…The versatility of these algorithms had led to the development of hybrid algorithms. To name a few, genetic algorithm with fuzzy for multi objective optimization [40], Particle Swarm Optimization with clustering algorithm for system modeling and identification [23], facility location-network design model using Firefly and Invasive Weed Optimization based fuzzy system [39]. For the inverse kinematics issue considered in this paper, various meta-heuristic algorithms such as Genetic Algorithm [34,6], Particle Swarm Optimization Algorithm [10,15], Cuckoo Optimization Al-gorithm [4], Genetic Algorithm, Gravitational Search Algorithm [2], Artificial Bee Colony [14], Fire Fly Algorithm [38], Modified Firefly [22], Bat Algorithm [28], were employed.…”

Section: Introductionmentioning

confidence: 99%

Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

Kanagaraj

Masthan

2022

mendel

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In robot-assisted manufacturing or assembly, following a predefined path became a critical aspect. In general, inverse kinematics offers the solution to control the movement of manipulator while following the trajectory. The main problem with the inverse kinematics approach is that inverse kinematics are computationally complex. For a redundant manipulator, this complexity is further increased. Instead of employing inverse kinematics, the complexity can be reduced by using a heuristic algorithm. Therefore, a heuristic-based approach can be used to solve the inverse kinematics of the robot manipulator end effector, guaranteeing that the desired paths are accurately followed. This paper compares the performance of four such heuristic-based approaches to solving the inverse kinematics problem. They are Bat Algorithm (BAT), Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA). The performance of these algorithms is evaluated based on their ability to accurately follow a predefined trajectory. Extensive simulations show that BAT and GSA outperform PSO and WOA in all aspects considered in this work related to inverse kinematic problems.

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Improved Type2-NPCM Fuzzy Clustering Algorithm Based on Adaptive Particle Swarm Optimization for Takagi–Sugeno Fuzzy Modeling Identification

Cited by 7 publications

References 28 publications

Research on Comprehensive Evaluation of Economic Management Performance Based on Improved Fuzzy Clustering Algorithm

Research on Comprehensive Evaluation of Economic Management Performance Based on Improved Fuzzy Clustering Algorithm

Extraction and Dyeing Techniques of Traditional Vegetable Dyestuffs

Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

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