TY - BOOK ID - 134716400 TI - Evolutionary Algorithms in Intelligent Systems AU - Milani, Alfredo AU - Carpi, Arturo AU - Poggioni, Valentina PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - multi-objective optimization problems KW - particle swarm optimization (PSO) KW - Gaussian mutation KW - improved learning strategy KW - big data KW - interval concept lattice KW - horizontal union KW - sequence traversal KW - evolutionary algorithms KW - multi-objective optimization KW - parameter puning KW - parameter analysis KW - particle swarm optimization KW - differential evolution KW - global continuous optimization KW - wireless sensor networks KW - task allocation KW - stochastic optimization KW - social network optimization KW - memetic particle swarm optimization KW - adaptive local search operator KW - co-evolution KW - PSO KW - formal methods in evolutionary algorithms KW - self-adaptive differential evolutionary algorithms KW - constrained optimization KW - ensemble of constraint handling techniques KW - hybrid algorithms KW - association rules KW - mining algorithm KW - vertical union KW - neuroevolution KW - neural networks KW - n/a UR - https://www.unicat.be/uniCat?func=search&query=sysid:134716400 AB - Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approximate solutions to computationally hard optimization problems. With the widespread use of intelligent systems in recent years, evolutionary algorithms have been applied, beyond classical optimization problems, to AI system parameter optimization and the design of artificial neural networks and feature selection in machine learning systems. This volume will present recent results of applications of the most successful metaheuristics, from differential evolution and particle swarm optimization to artificial neural networks, loT allocation, and multi-objective optimization problems. It will also provide a broad view of the role and the potential of evolutionary algorithms as service components in Al systems. ER -