Papers by Keyword: Convergence

Abstract: The data classification is an important issue in massive data classification. This paper proposes an inter-cell classification algorithm based on phase recombination neighbor points convergence which analyzes the convergence value weights of inter-cell characteristic points and filter the interferences of the minority local optimal characteristic points. The proposed algorithm can promote the convergence of the inter-cell classification data neighbor points. The simulation experiments testify the models by three types of actually collected data sets which illustrate the models have better classification performance.

Abstract: In this paper, a modified differential evolution algorithm (MDE) developed to solve unconstrained numerical optimization problems. The MDE algorithm employed random position updating and disturbance operation to replaces the traditional mutation operation. The former can rapidly enhance the convergence of the MDE, and the latter can prevent the MDE from being trapped into the local optimum effectively. Besides, we dynamic adjust the crossover rate (CR), which is aimed at further improving algorithm performance. Based on several benchmark experiment simulations, the MDE has demonstrated stronger convergence and stability than original differential (DE) algorithm and its two improved algorithms (JADE and SaDE) that reported in recent literature.

Abstract: This paper presents a modified harmony search (MHS) algorithm for solving numerical optimization problems. MHS employs a novel self-learning strategy for generating new solution vectors that enhances accuracy and convergence rate of harmony search (HS) algorithm. In the proposed MHS algorithm, the harmony memory consideration rate (HMCR) is dynamically adapted to the changing of objective function value in the current harmony memory. The other two key parameters PAR and bw adjust dynamically with generation number. Based on a large number of experiments, MHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its two improved algorithms (IHS and GHS).

Abstract: Harmony search algorithm is a new meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments’ pitches searching for a perfect state of harmony. To enable the harmony search algorithm to transcend its limited capability of local optimum, a modified harmony search algorithm is proposed in this paper. In the modified harmony search algorithm, the mutation operation of differential evolution algorithm is introduced into MHS algorithm, which improves its convergence. Several standard benchmark optimization functions are to be test and compare the performance of the MHS. The results revealed the superiority of the proposed method to the HS and recently developed variants.

Abstract: In this paper, a Dirichlet-Neumann alternating algorithm using elliptical arc artificial boundary for boundary value problem of Poisson equation in an infinite domain with a concave angle is investigated. The convergence of the algorithm is given. The choice of the relaxation factor is discussed. Finally, some numerical examples are presented to show effectiveness of our method.

Abstract: In this paper, a Schwarz alternating algorithm using elliptical arc artificial boundary for boundary value problem of Poisson equation in an infinite domain with a concave angle is investigated. The convergence of this algorithm is given. The convergence rate is analyzed in details for a typical domain. Finally, some numerical examples are presented to show effectiveness of our method.

Abstract: There are many different types of convergence in real analysis.In this paper,the basic convergence problem of a variety of convergence was discussed.Ultimate ideology in analysis was applied flexibly,uniform convergence problem was detailed analysis in-depth from the conditions of the topics, and illustrate that corresponding results will produce with the changed of the conditions.Therefore, we can conclude that basically consistent with the convergence condition is the strongest in a variety of convergence.

Abstract: The mechanical fuzzy reliability models based on cut-set method have been applied to many fields in engineering. The reliability analysis results are affected by the cut-set distribution. In this paper, a basic mechanical fuzzy reliability model using cut-set method was established. Based on this model, the deficiency of the three previous cut-set distributions, i.e. uniform distribution, linear distribution and truncated normal distribution, was analyzed, and a new cut-set distribution named modified truncated normal distribution was proposed. The analysis results showed that when the cut-set is long enough, the reliabilities of the fuzzy models with the three previous cut-set distributions tend to a fixed value which has nothing to do with the specific mechanical structures, which makes the models have no good convergence and unreasonable. While, the fuzzy reliability model with the new cut-set distribution proposed in this paper can converge well to the classical random reliability model. Moreover, the reliabilities of a stress-strength interference problem and a resonance problem were assessed as two examples to verify the theoretical analysis results, which indicate that with this new cut-set distribution, the fuzzy reliability models have better convergence and wider applications.

Abstract: Convergence means that independently existing entities create a new entity with a larger value through chemical bonding. Such convergence requires consilience of knowledge or discipline. Green technology shows a strong nature of convergence, having strong links between technologies rather than being an independent technology. Green technology can help the energy convergence society by producing energy through renewable energy, abandoning the way of growth of inputting large amount of fossil fuel like petroleum and gas, managing energy through a smart grid, storing energy in energy storage facility, and using LED or environment-friendly vehicle. In this study, we will measure the degree of convergence in green technology field to consider which field of technology actually converges in green technology. In the result, it was found that convergence was continuously increasing in green technology field, and the link between solar energy and LED lighting technology was especially strong. This means that convergence is happening between a technology of energy production and a technology that uses energy, and that the society is going forward to energy convergence society through green technology.

Abstract: This paper presents the global convergence theory of the discrete-time uniform pseudo projection anti-monotone network with the quasi–symmetric matrix, which removes the connection matrix constraints. The theory widens the range of applications of the discrete–time uniform pseudo projection anti–monotone network and is valid for many kinds of discrete recurrent neural network models.