| 词条 | Grapheur |
| 释义 |
| name = Grapheur | screenshot = Animazione debito pubblico disoccupazione ricerca(small).gif | screenshot_size = 300 | caption = 3D visualization with Grapheur | developer= Reactive Search srl | latest release version = 2.1.33 | latest release date = {{release date and age|2014|06|16}} | latest preview version = | latest preview date = | operating system = Windows , Mac OS X, Unix | language= English | genre = Technical computing | license = Proprietary software | website = {{URL|http://grapheur.com/}} }} Grapheur is a data mining, modeling, optimization and interactive visualization package implementing the "Learning and Intelligent Optimization" (LION)[1] and LIONsolver approach.[2] OverviewGrapheur originates from research principles in Reactive Search Optimization[3][4] advocating the use of self-tuning schemes acting while a software system is running. Version 2.1.33 of the software was released on June 16, 2014. With version 2.1, Grapheur includes business intelligence, Interactive visualization, modeling, optimization. The software architecture of Grapheur 2.1[5] permits interactive multi-objective optimization, with a user interface for visualizing the results and facilitating the solution analysis and decision making process. The architecture allows for problem-specific extensions, and it is applicable as a post-processing tool for all optimization schemes with a number of different potential solutions. When the architecture is tightly coupled to a specific problem-solving or optimization method, effective interactive schemes where the final decision maker is in the loop can be developed.[6] References1. ^{{cite book|title=The LION way. Machine Learning plus Intelligent Optimization |last=Battiti|first=Roberto|authorlink=|author2=Mauro Brunato|year=2014|publisher=LIONlab, University of Trento|location= Trento, Italy|isbn=978-1-4960-3402-1|url=http://intelligent-optimization.org/LIONbook/}} 2. ^Roberto Battiti and Mauro Brunato, Reactive Business Intelligence. From Data to Models to Insight, Reactive Search Srl, Italy, February 2011. {{ISBN|978-88-905795-0-9}}. 3. ^{{cite journal |last=Battiti |first=Roberto |author2=Gianpietro Tecchiolli |year=1994 |title=The reactive tabu search |journal=ORSA Journal on Computing| volume=6 |issue =2 |pages=126–140 |doi=10.1287/ijoc.6.2.126| bibcode=| oclc=| id =| url=http://rtm.science.unitn.it/~battiti/archive/TheReactiveTabuSearch.PDF |format=PDF}} 4. ^{{cite book|title=Reactive Search and Intelligent Optimization|last=Battiti|first=Roberto|author2=Mauro Brunato|author3=Franco Mascia|year=2008|publisher=Springer Verlag|location=|isbn=978-0-387-09623-0}} 5. ^{{cite journal| last=Battiti| first =Roberto|author2=Mauro Brunato| year=2010| title =Grapheur: A Software Architecture for Reactive and Interactive Optimization |trans-title=Proceedings Learning and Intelligent OptimizatioN LION 4, Jan 18–22, 2010, Venice, Italy |journal=Lecture Notes in Computer Science| volume=6073| pages =232–246| doi= 10.1007/978-3-642-13800-3 |url=http://rtm.science.unitn.it/~battiti/archive/grapheur-lion4.pdf| format=PDF}} 6. ^{{cite journal| last=Battiti| first=Roberto|author2=Andrea Passerini | year=2010| title=Brain-Computer Evolutionary Multi-Objective Optimization (BC-EMO): a genetic algorithm adapting to the decision maker | journal=IEEE Transactions on Evolutionary Computation| volume=14| issue=15| pages=671–687| doi=10.1109/TEVC.2010.2058118 | url=http://rtm.science.unitn.it/~battiti/archive/bcemo.pdf| format=PDF}} External links
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