2 results about "Fcm clustering" patented technology

This invention claims protection for a task offloading method for selecting and optimizing energy consumption of trusted edge servers, comprising the following main steps: S1, constructing a system model based on server and device related information data; S2, standardizing task information and MEC cache task classes and performing FCM clustering, followed by encoding matching to obtain the MEC server to be preferentially selected for offloading for each task class; S3, using set pair analysis theory to measure and analyze the reliability relationship in S2; S4, based on the results of S2, dividing the task into subtasks and offloading them in a multi-access point network while calculating energy consumption. Using the WOA algorithm, energy consumption is optimized within the tolerable latency range to obtain the offloading decision for each subtask; S5, based on S4, offloading the subtasks to the corresponding edge nodes or processing them locally. This invention considers issues such as trusted edge server selection and energy consumption optimization during task offloading, meeting user needs and reducing system energy consumption within the tolerable latency range.

This invention discloses a bridge health monitoring method based on fuzzy clustering envelope generative adversarial network (GAN). The method uses FCEGAN to augment imbalanced samples in bridge structural health monitoring. FCEGAN converts time-series data of different modes from sensor data acquired in the bridge health monitoring system into time-frequency image data. Then, based on the time-frequency image data, a multi-level clustering consensus mechanism is employed to jointly optimize multi-level FCM clustering, sample distribution consistency, and dimensionality, generating data samples with better separability and diversity, i.e., envelope samples. Next, the envelope samples are integrated into a GAN for training. Finally, the trained envelope GAN is used to generate new data samples to balance the different mode categories in structural health monitoring. The method of this invention can generate highly separable and diverse samples, thereby improving the ability to identify and classify anomalies.