Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Michael Conner

dblp:88/3082 · DBLP profile ↗
← Back
5ranked-venue papers
2as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1 · 1 first-authorComputer networks · 1Theory of computation · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Automata and formal languages · 50% Combinatorics and discrete mathematics · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Combinatorics and discrete mathematics › representation theory
group representation theory
0.011990
Sequential Machines Realized by Group Representations · Inf. Comput. 1990
Automata and formal languages › finite automata
sequential machines
0.011990
Sequential Machines Realized by Group Representations · Inf. Comput. 1990
YearPublicationVenuePosition
2010 Markov Chain Models for Genetic Algorithm Based Topology Control in MANETs
Cem Safak Sahin, Stephen Gundry, Elkin Urrea, M. Ümit Uyar, Michael Conner, Giorgio Bertoli, Christian Pizzo
EvoApplications (2)5
2009 Bio-inspired topology control for knowledge sharing mobile agents
Elkin Urrea, Cem Safak Sahin, Ibrahim Hökelek, M. Ümit Uyar, Michael Conner, Giorgio Bertoli, Christian Pizzo
Ad Hoc Networks5
2008 Genetic algorithms for self-spreading nodes in MANETs
abstract
We present a force-based genetic algorithm for self-spreading mobile nodes uniformly over a geographical area. Wireless mobile nodes adjust their speed and direction using a genetic algorithm, where each mobile node exchanges its genetic information of speed and direction encoded in its chromosomes with the neighboring nodes. Simulation experiments show encouraging results for the performance of our force-based genetic algorithm with respect to normalized area coverage..
Cem Safak Sahin, Elkin Urrea, M. Ümit Uyar, Michael Conner, Ibrahim Hökelek, Giorgio Bertoli, Christian Pizzo
GECCO4
1994 Special Purpose Hardware for Discrete Fourier Transform Implementation
Michael Conner, Richard Tolimieri
Parallel Comput.1
1990 Sequential Machines Realized by Group Representations
Michael Conner
Inf. Comput.1