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Fuzzy C mean initial clustering center selection, for beginners reference
Date : 2025-08-02 Size : 54kb User : ggsdduman

subclutering initializing fcm:
Date : 2025-08-02 Size : 2kb User : ggsdduman

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Extreme K-means is put forward by yuboYuan, given the initial clustering center, and the clustering is fast.
Date : 2025-08-02 Size : 1kb User : ggsdduman

K- means clustering algorithm. The number of initial cluster centers and its coordinates can be freely entered.
Date : 2025-08-02 Size : 1kb User : ggsdduman

BP neural networks for data classification -- speech feature signal classification
Date : 2025-08-02 Size : 367kb User : 青鱼

Nonlinear system modeling of BP neural networks nonlinear function fitting
Date : 2025-08-02 Size : 47kb User : 青鱼

Genetic algorithm optimization BP neural network nonlinear function fitting
Date : 2025-08-02 Size : 51kb User : 青鱼

Data forecasting based on Elman neural network model of power load forecasting
Date : 2025-08-02 Size : 2kb User : 青鱼

Data classification of SOM neural network -- Diesel Engine Fault Diagnosis
Date : 2025-08-02 Size : 3kb User : 青鱼

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The traditional K-medoids clustering algorithm clustering results with different initial center points and volatility, and high computational complexity is not suitable for processing large data sets; K-medoids clusterin
Date : 2025-08-02 Size : 2kb User : playboyplay2

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K means clustering algorithm is first randomly selected K objects as the initial clustering center. Then calculate the distance between each object and each seed cluster center and assign each object to its nearest clust
Date : 2025-08-02 Size : 1kb User : playboyplay2

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The initial cluster centers and the iteration steps are set by clustering, the minimum clustering, the central location re calculation, and the display
Date : 2025-08-02 Size : 3kb User : playboyplay2
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