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Finding the shortest path between two places is a well known problem in road traveling. While most of the work done up to this moment is focused on algorithmics, efficiently managing the information has received significantly less attention. Nevertheless, real world problems like road map routing present a challenge due to the impact that the immense size of the map has over the temporal complexity...
In recent years, clustering has become a hotspot in the field of data mining, as one of the key technologies of getting data distribution and observing the characteristics of class. However, some clustering algorithms depend on the selection of initial clustering centers, and the clustering results easily fall into local optimal. To solve the above problem, the paper integrates differential evolution...
Cooperative coevolution framework is an effective strategy to deal with large scale optimization problems. However, most studies on cooperative coevolution framework utilize the same optimizer for all subcomponents, which may not be effective enough. In this paper, we propose a novel multi-optimizer cooperative coevolution method for large scale optimization problems which randomly chooses an optimization...
An important application field of swarm intelligence algorithms is fuzzy rule acquisition. However, their limitations are showed in two aspects. On one hand, it takes a long process to create fuzzy rules during the iterations; on the other, the swarm intelligence algorithms obtain local optimal solution at times. To overcome these disadvantages, a dynamic hybrid swarm intelligence approach is proposed...
The slicing problem is to partition a partially-ordered collection of values into a given number of totally-ordered disjoint sets -- slices -- so that each slice contains a predefined fraction of values that are greater than those in the previous slice and smaller than those in the next slice. In this paper, we investigate a decentralized variant of the problem, which we encountered in our experiments...
Fuzzy C-Means (FCM) algorithm is one of the most popular fuzzy clustering techniques. However, it is easily trapped in local optima. Particle swarm optimization (PSO) is a stochastic global optimization model, which is used in many optimization problems. In this paper, a hybrid clustering algorithm, called HAPF, based on adaptive PSO (APSO) and FCM is proposed, in order to take advantage of the merits...
In this study we analyse complete networks derived from field survey and market research through proposing an efficient methodology based on proximity graphs and clustering techniques enhanced with a new community detection algorithm. The specific context is the charity and Not-For-Profit sector in Australia and consumer behaviours within this context. To investigate the performance of this methodology...
The performance of the Dynamic Frame Slotted Aloha (DFSA) based RFID Anti-Collision Algorithm depends on the dynamically controlled frame size with the contending tags. Many literatures exploit the tag estimation method and attempt to enhance the system performance by regulating the frame size equal to the estimated tags. Unless the contending tag population is exactly estimated and the frame size...
As the development of CMP, the size of on-chip cache increases and it consumes more and more power of the whole system. How to reduce the power consumption of cache has become a major concern nowadays. Cache partitioning techniques have been proposed to solve the cache pollution problem. The traditional cache partitioning mechanism, such as Utility-based Cache Partitioning (UCP) and IPC-based Cache...
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