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LION
2009
Springer
129views Optimization» more  LION 2009»
14 years 3 months ago
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
APWEB
2006
Springer
14 years 18 days ago
Energy-Efficient Deployment of Mobile Sensor Networks by PSO
Abstract. Sensor deployment is an important issue in designing sensor networks. In this paper, particle swarm optimization (PSO) approach is applied to maximize the coverage based ...
Xiaoling Wu, Shu Lei, Jin Wang, Jinsung Cho, Sungy...
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
14 years 16 days ago
Filter approximation using explicit time and frequency domain specifications
We demonstrate that enhanced particle swarm optimization (PSO) can be successfully used to evolve high performance filter approximations. These evolved approximations use sets of ...
Varun Aggarwal, Wesley O. Jin, Una-May O'Reilly
TIFS
2010
123views more  TIFS 2010»
13 years 7 months ago
A new framework for adaptive multimodal biometrics management
This paper presents a new evolutionary approach for adaptive combination of multiple biometrics to ensure the optimal performance for the desired level of security. The adaptive c...
Ajay Kumar, Vivek Kanhangad, David Zhang
HPCC
2007
Springer
14 years 22 days ago
A New Method for Multi-objective TDMA Scheduling in Wireless Sensor Networks Using Pareto-Based PSO and Fuzzy Comprehensive Judg
In wireless sensor networks with many-to-one transmission mode, a multi-objective TDMA (Time Division Multiple Access) scheduling model is presented, which concerns about the packe...
Tao Wang, Zhiming Wu, Jianlin Mao