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To deal with the problems of topological structure cannot adjust adaptively, easy to trap into the local minimum and diversity losing in traditional particle swarm optimization algorithm, a newly adaptive PSO algorithm based on dynamic link matrix was proposed, which build the neighborhoods though link matrix and divide them into the sub-swarm based on feature clustering. The algorithm can adjust...
We developed an automatic cover design supporting system for non-professional users to create their preferred cover designs in a user-oriented way by using Interactive Genetic Algorithm(IGA). Different from the template design pattern, our system allows an interaction between the algorithm and the Decision Maker(DM). It allows the users to take into account their preferences at each generation of...
Matrix factorization techniques have been frequently applied in data representation and pattern recognition. One of them is Concept Factorization (CF), which is a new matrix decomposition technique for data representation. In this paper, we propose a novel semi-supervised matrix factorization algorithm, called Constrained Graph Concept Factorization (CGCF), which incorporates the label information...
In order to solve the problem which robot swarm isn't easy to form and maintain stable formations, a formation control algorithm based on community division and multilevel topology is proposed by introducing the ideas of hierarchical clustering and pining control. Firstly, based on the hierarchical clustering algorithm, a large group of robots is divided into some communities and a pining robot is...
This paper analyses and studies genetic algorithm and classical clustering algorithms, and then the demand analysis and design of the personnel management system of Shenyang Administration College. The adaptive crossover probability and adaptive mutation probability are proposed, which consider the influence of every generation to algorithm and the effect of different individual fitness in every generation...
Brain disease is one of common diseases that threaten human health, which is becoming one of hot researches in society and medical profession. After a variety of image segmentation methods in the brain MR image segmentation are studied, it is found that FCM algorithm and SVM algorithm have a lot of advantages and good application prospection. Then a combination of unsupervised classification algorithm...
Wireless sensor network is typically used to detect and monitor various types of objects in real-time monitoring area in which security is one major challenge. Evaluation of nodes' trust is proven to be an effective solution of improving security, supporting decision-making and nodes collaboration in both wired and wireless networks. However, existing approaches of trust management emphasize mostly...
Aiming at the construction and reconstruction of dynamic cluster for target tracking with wireless sensor network, a sensor Scheduling target tracking-oriented algorithm based on prediction is proposed in this thesis, in which construction and reconstruction of dynamic cluster depends on prediction of nodes' location. Selection of cluster head is achieved by weighted algorithm considering residual...
RCRSS (RoboCup Rescue Simulation System, RCRSS) is a typical multi-agent system. In order to solve the task allocation problem for police multi-agents of this system, this paper presents a novel partitioning-based task allocation strategy. It is carried out through the use of clustering, namely the K-means clustering algorithm, to divide the map into several regions. Then the dynamic adjustment system...
Wireless sensor network (WSN) is a kind of dynamic self-organizing network. It can be applied to military, environmental monitoring, industry and transportation fields. According to the characteristics of energy constrained wireless sensor networks, it is more significant to design an energy efficient wireless sensor networks in practice application. The affinity propagation clustering algorithm,...
In wireless sensor networks, the energy supply is limited and the node will be dead while the energy is out of use. In order to solve the energy consumption problem about the sizes of clusters, a novel grid clustering algorithm based on location information is proposed in the paper: the node is planned to the corresponding grid according to the location information.While we can get the sizes of clusters...
For enhancing the cluster accuracy, this paper presents a novel algorithm called L3/2 Sparsity Constrained Graph Non-negative Matrix Factorization (FGNMF), which based on the convex and smooth L3/2 norm. When original data is factorized in lower dimensional space using NMF, FGNMF preserves the local structure and intrinsic geometry of data, using the convex and smooth L3/2 norm as sparse constrains...
This paper presents a kind of constraint to ensure first-order contiguity of Traffic Analysis Zone delineation problem. Based on k-median facility location model, a 0–1 integer programming mathematical presentation of the problem, with objective of minimizing heterogeneity, is given. The proposed model is compared with other three ones in terms of model complexity and time consuming. The other three...
Clustering is such an algorithm which merges the most similar pair of samples into the same classification at every iteration. The traditional similarity evaluation function is manually designed, but the recent interest focuses on supervised or semi-supervised learning where the ground-truth clustered data can be available for training. This paper will first describes how to train a similarity function...
A new Fuzzy Identification Method for T-S model identification algorithm is proposed, based on cats swarm and least squares method. T-S model identification is divided into structural and parameter identification. In the structure identification using cats warm can effectively overcome the traditional clustering algorithms exist slow convergence and easily fall into fall into local optimal solution,...
Image segmentation is a fundamental process in computer vision applications. This paper presents a novel method to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized...
Energy consumption has always been a hot research topic in wireless sensor networks, in this paper, a novel energy-saving routing protocol based on two-layers routing mechanism is proposed, in which, the first layer adopts the remaining energy centroid algorithm to form clusters and elect the cluster heads, and the second layer adopts multi-hop transmission to guarantee that the cluster heads can...
Node localization of wireless sensor network is a hot topic, but current algorithms of 3D wireless sensor node localization are not accurate enough. In this paper, the DR-MDS algorithm is proposed, DR-MDS algorithm mainly calibrates the coordinates of nodes and the ranging of nodes based on multidimensional scaling, it calculates the distance between any nodes exactly according to the hexahedral measurement,...
The FCM algorithm based on invasive weed optimization algorithm (IWO-FCW) has stronger global optimization ability and higher clustering precision than the basic FCM algorithm, but the IWO-FCW algorithm exists some questions that the convergence become slow and the clustering precision is not high for high and complex testing data sets. So an improved IWO-FCM algorithm is proposed in this paper. This...
Outlier detection is an important procedure in industrial dataset preprocess to guarantee the industrial process operating normally. This paper proposed a new local density definition in the basis of the minimum hyper sphere for outlier mining algorithm. First, the novel local k-density definition of an object is proposed by using the minimum enclosing hyper sphere algorithm. After this, the new k-density...
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