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Multi-modal optimization refers to locating not only one optimum but a set of locally optimal solutions. Niching is an important technique to solve multi-modal optimization problems. The ability of discover and maintain multiple niches is the key capability of these algorithms. In this paper, differential evolution with an ensemble of restricted tournament selection (ERTS-DE) algorithm is introduced...
As an important technique in modern sociology, social network analysis has gained a lot of attention from many disciplines, and been used as important complements to traditional statistics and data analysis. In order to make it affordable for analysts with massive and fast growing networks, we present X-RIME, a cloud-based library for large scale social network analysis. We propose an implementation-oriented...
Security issues have become a main concern in modern life. A powerful cryptosystem has to be practical, secure and able to be implemented on different platforms. The goal of this research is to develop a basis of cryptographic scheme which utilizes some advanced transform techniques for various applications. Number Theoretic Transforms (NTTs) are relatively powerful in data diffusion. A symmetric...
Recently, the sizes of networks are always very huge, and they take on distributed nature. Aiming at this kind of network clustering problem, in the sight of local view, this paper proposes a fast network clustering algorithm in which each node is regarded as an agent, and each agent tries to maximize its local function in order to optimize network modularity defined by function Q, rather than optimize...
A forecast learning method of kernel principal component analysis (KPCA) is presented for specific emitter identification (SEI) application. By constructing a symmetrical decomposition of the kernel matrix, we derived a new algorithm of incremental KPCA. Based on it, the forecast capability is developed by creating dummy samples whose kernel vectors are an extrapolation of the kernel matrix. The advance...
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