His primary areas of study are Differential evolution, Evolutionary algorithm, Mathematical optimization, Memetic algorithm and Optimization problem. His work investigates the relationship between Differential evolution and topics such as Continuous optimization that intersect with problems in Tree and Curse of dimensionality. The Evolutionary algorithm study combines topics in areas such as Probabilistic logic and Crossover.
His study brings together the fields of Algorithm and Mathematical optimization. Memetic algorithm is a subfield of Local search that Ferrante Neri tackles. As a member of one scientific family, Ferrante Neri mostly works in the field of Optimization problem, focusing on Artificial intelligence and, on occasion, Structure, Machine learning and P system.
His main research concerns Mathematical optimization, Differential evolution, Algorithm, Local search and Artificial intelligence. His Mathematical optimization research focuses on Evolutionary computation, Metaheuristic, Optimization problem and Evolutionary algorithm. His work carried out in the field of Differential evolution brings together such families of science as Curse of dimensionality, Particle swarm optimization, Crossover, Fitness landscape and Scale factor.
His research investigates the connection with Algorithm and areas like Control theory which intersect with concerns in Stationary Reference Frame. Ferrante Neri works in the field of Local search, namely Memetic algorithm. His Artificial intelligence research includes themes of Structure and Machine learning.
Ferrante Neri focuses on Algorithm, Differential evolution, Local search, Artificial intelligence and Metaheuristic. The Rotational invariance research Ferrante Neri does as part of his general Algorithm study is frequently linked to other disciplines of science, such as Invariant, therefore creating a link between diverse domains of science. His research integrates issues of Correlation, Curse of dimensionality, Mutation and Rotation in his study of Differential evolution.
His research on Local search focuses in particular on Memetic algorithm. His studies examine the connections between Artificial intelligence and genetics, as well as such issues in Machine learning, with regards to Structure and Heuristic. As part of one scientific family, Ferrante Neri deals mainly with the area of Metaheuristic, narrowing it down to issues related to the Key, and often Genetic algorithm and Function.
Ferrante Neri mainly investigates Artificial intelligence, Algorithm, Differential evolution, Metaheuristic and Rapidly exploring random tree. His Spiking neural network and Bio-inspired computing study in the realm of Artificial intelligence interacts with subjects such as Artificial Eyes and Image processing. His Algorithm study combines topics in areas such as Exponential function, Correlation and Curse of dimensionality.
Ferrante Neri has included themes like Evolutionary algorithm, Genetic algorithm, Function and Crossover in his Differential evolution study. His Metaheuristic research incorporates elements of Orthogonalization, CMA-ES and Search algorithm. His Rapidly exploring random tree study is concerned with Motion planning in general.
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Recent advances in differential evolution: a survey and experimental analysis
Ferrante Neri;Ville Tirronen.
Artificial Intelligence Review (2010)
Memetic algorithms and memetic computing optimization: A literature review
Ferrante Neri;Carlos Cotta.
Swarm and evolutionary computation (2012)
Handbook of Memetic Algorithms
Ferrante Neri;Carlos Cotta;Pablo Moscato.
Handbook of Memetic Algorithms (2011)
A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives
A. Caponio;G.L. Cascella;F. Neri;N. Salvatore.
systems man and cybernetics (2007)
An optimization spiking neural p system for approximately solving combinatorial optimization problems.
Gexiang Zhang;Haina Rong;Ferrante Neri;Mario J. Pérez-Jiménez.
International Journal of Neural Systems (2014)
Compact Differential Evolution
E Mininno;F Neri;F Cupertino;D Naso.
IEEE Transactions on Evolutionary Computation (2011)
Super-fit control adaptation in memetic differential evolution frameworks
Andrea Caponio;Ferrante Neri;Ville Tirronen.
soft computing (2009)
Scale factor local search in differential evolution
Ferrante Neri;Ville Tirronen.
Memetic Computing (2009)
Memetic Compact Differential Evolution for Cartesian Robot Control
Ferrante Neri;Ernesto Mininno.
IEEE Computational Intelligence Magazine (2010)
An Adaptive Multimeme Algorithm for Designing HIV Multidrug Therapies
Ferrante Neri;Jari Toivanen;Giuseppe Leonardo Cascella;Yew-Soon Ong.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2007)
Profile was last updated on December 6th, 2021.
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