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The continuous growth of wireless sensor networks demands new approaches to efficiently manage and service them. We present an approximation solution to the facility location problem for sensor network maintenance based on static sensors and mobile facilities. The main goal is to increase the network lifetime by recharging or redeploying sensors with the help of mobile multi-purpose maintenance facilities...
The K-Modes algorithm is one of the most popular clustering algorithms in dealing with categorical data. But the random selection of starting centers in this algorithm may lead to different clustering results and falling into local optima. In this paper we proposed a swarm-based K-Modes algorithm. The experimental results over two well known Soybean and Congressional voting categorical data sets show...
Data Mining Technology from the huge amount of data found in the potential of useful information and knowledge, Ant colony algorithm in dealing with combinatorial optimization problem has also been made a better results, this makes the ant colony algorithm applied to data mining prospects. In order to overcome the defects of K-means algorithm such as the local optima and sensitivity to initialization...
Innovation ability of Industrial clusters is an important measure of regional innovation. Industrial clusters with strong innovation ability can promote the development of innovative enterprises, which are the key element of regional innovation. Therefore, it is important to establish models to evaluate innovation ability for industry clusters. In this paper, an improved BP neural network model was...
The discovery and construction of inherent regions in large spatial datasets is an important task for many research domains such as climate zoning, eco-region analysis, public health mapping, and political redistricting. From the perspective of cluster analysis, it requires that each cluster is geographically contiguous. This paper presents a contiguity constrained hierarchical clustering and optimization...
Inspired by the competition of sport teams in a sport league, an algorithm is presented for optimizing nonlinear continuous functions. A number of individuals as sport teams compete in an artificial league for several weeks (iterations). Based on the league schedule in each week, teams play in pairs and the outcome is determined in terms of win or loss, given known the team's playing strength (fitness...
The application of intelligent optimization algorithm in data mining has become widespread already. However, it's still a brand new research area in the application of Ant Colony Algorithm(ACA) in data mining. This paper thus proposes a fuzzy data mining algorithm which is based on MAX-MIN Ant System(MMAS). In this algorithm, the membership functions which are extracted from the classification rule...
Recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. In this paper, we consider for the first time the projective clustering ensemble (PCE) problem, whose main goal is to derive a proper projective consensus partition from an ensemble of projective clustering solutions. We formalize PCE as an optimization...
In this paper, we propose a framework to make the text clustering process, as a whole, efficient. In a real text clustering task, an analyst usually has some expectation on the results in mind. However, a single run of a clustering algorithm on the preprocessed data would not satisfy the expectation. Then the analyst faces labor-intensive trials for improving the results that involve repetitive feature...
Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct temporal causal graphical models. However, how to best understand and conceptualize these complicated causal relationships is still an open problem. In this paper, we propose a decomposition approach to simplify the temporal...
Entities of the real world require partition into groups based on even feature of each entity. Clusters are analyzed to make the groups homologous and well separated. Many algorithms have been developed to tackle clustering problems and are very much needed in our application area of gene expression profile analysis in bioinformatics. It is often difficult to group the data in the real world clearly...
Artificial neural networks (ANN) and fuzzy systems are the widely preferred artificial intelligence techniques for biological computational applications. While ANN is less accurate than fuzzy logic systems, fuzzy theory needs expertise knowledge to guarantee high accuracy. Since both the methodologies possess certain advantages and disadvantages, it is primarily important to compare and contrast these...
This paper intends to propose a novel clustering method based on ant colony (AC) algorithm. A new approach called TT-transform based time frequency analysis is used in processing the non-stationary power signal disturbances. The time-time transform is the inverse Fourier transform of S-transform. The proposed model is demonstrated using feature vector from the domain of power signal analysis, yielding...
The main objective of sensor deployment problem in Wireless Sensor Network (WSN) is to use minimum number of sensor nodes with given sensing range that can cover any target in the coverage area to monitor the environment. The optimal sensor deployment enables accurate sensing information on target behavior with minimum sensing range and number of sensor nodes. The target coverage terrain in a locality...
Wireless Mesh Networks (WMNs) have the potential for improving network capacity by employing multiple radios and multiple channels (MRMC). Channel Assignment (CA) is a key issue that plays vital role in defining WMN throughput by efficient utilization of available multiple radios and channels there by minimizing network interference. The two important issues that are needed to be addressed by CA algorithm...
Ant colony clustering was first proposed by Deneubourg in 1990, it is a bionic clustering method and has been widely used in cluster analysis. In this paper, an ant colony clustering algorithm based on appropriate retention of the elites is presented. Based on the general ant colony clustering algorithm, the mechanism to retain the elites is introduced, in each of the iterative algorithm always retain...
This paper introduces an efficient incremental clustering method based on Ants' Chemical Recognition System Algorithm (ACRSA). We apply it to Web user clustering and compare the accuracy rate of personalized recommendation with ACRSA. This paper also introduces a new cluster-dissolution mechanism into ACRSA to make the result more natural. The experimental results show that this method can achieve...
Cluster algorithm is one of the hotspots for studying routing protocol in mobile Ad Hoc networks, which is benefit for enlarging the network topology and utilizing the capacity of channel efficiently. This thesis researches the cluster algorithm of maximum node degree and modifies the update mechanism of cluster header. When the changing of node degree is within a range, the state of header is not...
China wireless content service is at the beginning years of establishment, and will keep growing at top speed in the future. Pheromone of wireless content services can scatter by wireless uses, and gets effect of ant colony clustering. Basically, the process of customer segmentation is the process of ant looking for food. This paper presents ACO market segmenting algorithm of wireless content services...
In wireless sensor networks, proposed an energy efficient routing strategy based on ant colony algorithm. The algorithm combined residual energy of nodes, and accorded to transition probability to choose the next node. When ants passed a node, updated the path list and node information table .Through the node information table, nodes in the network are divided into ordinary nodes and aggregation nodes,...
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