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This study concerns the training of a neural network in multiple stages considering minimization of errors from multiple data/pattern resources. The paper proposed a dual stage multi-resource data training scheme using multi-objective genetic algorithm. The training scheme has been used for the design and development of efficient neural network model focusing on missing, but most informative domains...
This paper presents a comprehensive study on mono- and multi-objective approaches for electrical distribution network design using particle swarm optimization (PSO). Specifically, two distribution network design problems, i.e., static and expansion planning, are solved using PSO. The network planning involves optimization of both network topology and branch conductor sizes. Both the planning problems...
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