Titlebook: Applications of Evolutionary Computing; EvoWorkshops 2009: E Mario Giacobini,Anthony Brabazon,Penousal Machado Conference proceedings 2009

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書目名稱Applications of Evolutionary Computing影響因子(影響力)




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書目名稱Applications of Evolutionary Computing網(wǎng)絡公開度學科排名




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書目名稱Applications of Evolutionary Computing年度引用學科排名




書目名稱Applications of Evolutionary Computing讀者反饋




書目名稱Applications of Evolutionary Computing讀者反饋學科排名

Terrace

Location Discovery in Wireless Sensor Networks Using a Two-Stage Simulated Annealingle in many of the applications where WSN are used. A widely used self-locating mechanism consists in equipping a small subset of the nodes with GPS hardware, while the rest of the nodes employ reference estimations (received signal strength, time of arrival, etc.) in order to determine their locatio

缺陷

misshapen

Small-Intestine

上流社會

CESS

A Framework for Evolutionary Peer-to-Peer Overlay Schemesount basically two dimensions: the dispersion degree of information about shared resources (centralized, decentralized, hybrid), and the logical organization (unstructured, structured). On the other side, there is a lack of common understanding about adaptive peer-to-peer sytems. In our view, peers’

effrontery

Multiuser Scheduling in HSDPA with Particle Swarm Optimizationhannel state information (CSI) feedback, which is required for this problem, in the form of a finite set of Channel Quality Indicator (CQI) values is assumed, as specified in the HSDPA standard [1]. A global optimal approach and a particle swarm optimization approach are used to solve the problem. S

非實體

Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networksd. The node-level decision unit is based on Adaptive Resonance Theory (ART), which is a simple kind of neural networks. The Fuzzy ART neural network used in this work is an ART neural network that accepts analog inputs. A Fuzzy ART neural network represents an adaptive memory that can store a predef

flex336

Peer-to-Peer Optimization in Large Unreliable Networks with Branch-and-Bound and Particle Swarmsting platform. So far, little is known about the scaling and reliability of optimization algorithms in P2P environments. In this paper we present empirical results comparing two P2P algorithms for real-valued search spaces in large-scale and unreliable networks. Some interesting, and perhaps counter