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In order to achieve the goal of economic and environmental mutual optimization of micro-grid system operation, a general model of multi-objective dynamic optimal scheduling is established, which takes the independent system simulation module and the operation optimization module as the core. The simulation module uses energy model to evaluate economic and environmental indexes of the system scheduling...
Aim at the problem that it is difficult to detect reciprocating compressor early fault data with complex shape clusters, a novel fault detection algorithm is put forward based on antibody clonal selection and immune memory principle. Firstly, high dimension space of raw feature signals is constructed by multivariate statistical analysis, and then the local tangent space alignment (LTSA) algorithm...
In this study, a novel dynamic agglomerative hierarchical clustering algorithm which combines Boltzmann theory of thermodynamics and a graph-theoretic representation of data objects is put forward for data with non-sphere shape clusters. The new algorithm employs neighbors searching operator and vertices spanning operator to construct the linkage paths between vertices. Additionally, in order to obtain...
In this paper, a mutation with cycle probability is designed by simulating the evolutionary rule of the earth creature, and a genetic algorithm based on the cycle mutation, presents the ability in improving search efficiency and overcoming premature to some extent. To further improve performance of the algorithm, the selection is mended according to the phenomena that optimum individual always plays...
In this paper, in order to overcome the premature convergence and low stability of the particle swarm optimization (PSO) algorithm, a particle swarm optimization algorithm based on adaptive periodic mutation (APMPSO) is introduced. In the algorithm, the fitness uniformity distribution of the objective function, which can maintain the diversity of the population, is adaptively adjusted. The strategy...
To solve the problem of on-line dynamic planning of mobile robots in unknown environments, inspired by the mechanism of idiotypic network hypothesis, a hybrid immune network algorithm (HINA) is proposed. To improve the planning efficiency of immune network algorithm (INA) and realize optimal on-line dynamic obstacle avoidance, a new adaptive artificial potential field (AAPF) method is presented by...
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