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This paper presents a Copula-based Estimation of Distribution Algorithm with Parameter Updating for numeric optimization problems. This model implements an estimation of distribution algorithm using a multivariate extension of the Archimedean copula (MEC-EDA) to estimate the conditional probability for generating a population of individuals. Moreover, the model uses traditional crossover and elitism...
The shortest common superstring problem has important applications in computational biology (e.g. genome assembly) and data compression. This problem is NP-hard, but several heuristic algorithms proved to be efficient for this problem. For example, for the algorithm known as GREEDY it was shown that, if the optimal superstring has the length of N, it produces an answer with length not exceeding 3...
In this paper, we propose a hybrid Multiobjective Estimation of Distribution Algorithm based on Artificial Bee Colonies and Clusters (MOEDABC) to solve multiobjective optimization problems with continuous variables. This algorithm is inspired in the organization and division of work in a bee colony and employs techniques from estimation of distribution algorithms. To improve some estimations we also...
A RSSI-based localization system on a home wireless sensor network is proposed in this work. In order to support a robot assistant in pick-and-place tasks, our current system is capable of estimating the localization of an object using the signal strength received by a mobile device in a ZigBee sensor network. Two models were utilized (a) log-distance path loss - model in which signal lost has a random...
The Minimal Learning Machine (MLM) has been recently proposed as a novel supervised learning method for regression problems aiming at reconstructing the mapping between input and output distance matrices. Estimation of the response is then achieved from the geometrical configuration of the output points. Thanks to its comprehensive formulation, the MLM is inherently capable of dealing with nonlinear...
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