Optimization : principles and algorithmsQue sais-je ?JeanBaptiste HiriartUrruty
With deregulation, market rules and economic principles dictate that commodities be priced at the marginal value of their production. As a result, it's necessary to work with ever-more-sophisticated algorithms using optimization techniques-either for the optimal dispatch of the system itself, or for...
In common with other applications of machine learning, mathematical formula- tions of the learning problem in speech and language processing depend on models constructed from statistical principles, loss functions that quantify misfit between observed data and pre- dictions, parameters for the models, ...
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Presents the principles of multiobjective or multicriteria optimization Describes ist main methods Evaluates the efficiency of different methods and considers the choice of an algorithm for a given problem The methods are illustrated by case studies from different fields of engineering Part of the book...
The role of adaptation, learning and optimization are becoming increasingly essential and intertwined. The capability of a system to adapt either through ...
In the last decade, we observe an increasing number of nature-inspired optimization algorithms, with authors often claiming their novelty and their capabil
Exploiting graph theory principles can address challenges related to model complexity, training efficiency and generalization capabilities. In Neural networks, especially deep learning models have demonstrated remarkable success in various tasks such as image recognition, natural language processing and speech ...
It is of great importance noting that dealing with PSO has some advantages when compared with other optimization algorithms, once it has fewer parameters to adjust, and the ones that must be set are widely discussed in the literature [3]. Advertisement 2. Particle swarm optimization: an ...