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[Lecture Notes in Computer Science] Intelligence Science and Big Data Engineering Volume 11266 (8th International Conference, IScIDE 2018, Lanzhou, China, August 18–19, 2018, Revised Selected Papers) || An Improved Spectral Clustering Algorithm Based on Dynamic Tissue-Like Membrane System
摘要： With vast amount of data generated, it is becoming a main aspect to mine useful information from such data. Clustering research is an important task of data mining. Traditional clustering algorithms such as K-means algorithm are too old to propose high-dimensional data, so an ef?cient clustering algorithm, spectral clustering is generated. In recent years, more and more scholars has been ?rmly committing to studying spectral clustering algorithm for its solid theoretical foundation and excellent clustering results. In this paper we propose an improved spectral clustering algorithm based on Dynamic Tissue-like P System abbreviated as ISC-DTP. ISC-DTP algorithm takes use of the advantages of maximal parallelism in tissue-like membrane system. Experiment is conducted on an arti?cial data set and four UCI data sets. And we compare the ISC-DTP algorithm with original spectral clustering algorithm and K-means algorithm. The experiments demonstrate the effectiveness and robustness of the proposed algorithm.
关键词： Spectral clustering algorithm,Tissue-like membrane system,Data mining,ISC-DTP algorithm
更新于2025-09-23 15:21:21
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Clusters partition and zonal voltage regulation for distribution networks with high penetration of PVs
摘要： Integration of distributed generation (DG) at large scale with high penetration challenges the radial structure of the traditional distribution networks and the effectiveness of the conventional voltage regulation methods. In this study, the clusters partitioning and voltage regulation are researched. The modified electrical distance is introduced. An effective method, based on spectral clustering algorithm, is proposed for the partitioning of the DG network via the judgement of critical load buses. Two-stage voltage regulation optimisation is realised in each sub-community. The optimal objects are the minimal voltage fluctuation and the network loss of the distributed network. The independent variables are reactive-power absorption and active-power curtailment for each controllable photovoltaic node. An advanced particle swarm optimisation algorithm is applied to the voltage regulation for the sub-communities. After a case study of the IEEE 33-bus system, a regional distribution network in Anhui province of China is analysed. Simulation results indicate that the node voltages are stabilised with the improvement of power quality employing the proposed clusters partitioning method and zonal power control scheme.
关键词： spectral clustering,particle swarm optimisation,voltage regulation,distributed generation,photovoltaic
更新于2025-09-04 15:30:14