In this paper, a synergy of two mutation based immune multi-objective automatic fuzzy clustering algorithm (STMIMAFC) is proposed for the task of automatically evolving the number of clusters as well as a proper parti...
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In this paper, a synergy of two mutation based immune multi-objective automatic fuzzy clustering algorithm (STMIMAFC) is proposed for the task of automatically evolving the number of clusters as well as a proper partitioning of data set. In the proposed algorithm, firstly, two new mutation operators, which are designed for the different structures of chromosomes respectively, are cooperated with each other to generate the new individuals. Secondly, we propose an exponential function based compactness validity index. The proposed method has been extensively compared with a synergy of genetic algorithm and multi-objective differential evolution, multi-objective modified differential evolution based fuzzy clustering, multi-objective clustering with automatic -determination over a test suit of several real life data sets and synthetic data sets. Experimental results indicate the superiority of the STMIMAFC over other three compared clustering algorithms on clustering accuracy and running time.
Aiming at the solving problem of improved nonhomogeneous Poisson process( NHPP) model in engineering application,the immuneclone maximum likelihood estimation( MLE)method for solving model parameters was proposed. Th...
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Aiming at the solving problem of improved nonhomogeneous Poisson process( NHPP) model in engineering application,the immuneclone maximum likelihood estimation( MLE)method for solving model parameters was proposed. The minimum negative log-likelihood function was used as the objective function to optimize instead of using iterative method to solve complex system of equations,and the problem of parameter estimation of improved NHPP model was solved by immune clone algorithm. And the interval estimation of reliability indices was given by using fisher information matrix method and delta method. An example of failure truncated data from multiple numerical control( NC) machine tools was taken to prove the method. and the results show that the algorithm has a higher convergence rate and computational accuracy, which demonstrates the feasibility of the method.
This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satell...
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This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.
作者：
Jin YongqiangZhao ErfengHoHai Univ
Coll Water Conservancy & Hydropower Eng Nanjing Peoples R China HoHai Univ
Natl Eng Res Ctr Water Resource Efficient Utilizat & Eng Safety Nanjing Peoples R China
Aiming at the correlation among variables, the non-linearity between independent variables and dependent variables, and the deficiency of traditional BP neural network in monitoring data analysis, a new model is propo...
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ISBN:
(纸本)9781424421077
Aiming at the correlation among variables, the non-linearity between independent variables and dependent variables, and the deficiency of traditional BP neural network in monitoring data analysis, a new model is proposed based on partial least squares regression method, BP neural network and immune clone algorithm. The model deals with the correlation according to least squares regression, settles the non-linearity with BP neural network, and moreover it applies immune clone algorithm to search of BP neural network. Take rock mass deformation as the dependent variable and six factors of rock mass as the independent variables, a practical project are analyzed based on the model. The analysis result shows that the model is effective in overcoming the effects of correlation and nonlinearities, with a speedy and stable convergence. Therefore it has superiority in practical applications.
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