Results 281 to 290 of about 3,048,704 (321)

Policy Evolution with Grammatical Evolution

2008
Security policies are becoming more sophisticated. Operational forces will often be faced with making tricky risk decisions and policies must be flexible enough to allow appropriate actions to be facilitated. Access requests are no longer simple subject access object matters. There is often a great deal of context to be taken into account.
Yow Tzu Lim, Pau-Chen Cheng, John Andrew Clark, Pankaj Rohatgi   +3 more
openaire   +1 more source

Interpretable Solutions for Breast Cancer Diagnosis with Grammatical Evolution and Data Augmentation

EvoApplications@EvoStar
Medical imaging diagnosis increasingly relies on Machine Learning (ML) models. This is a task that is often hampered by severely imbalanced datasets, where positive cases can be quite rare.
Yumnah Hasan, Allan de Lima, Fatemeh Amerehi, Darian Reyes Fernández de Bulnes, Patrick Healy, Conor Ryan   +5 more
semanticscholar   +1 more source

An improved grammatical evolution approach for generating perturbative heuristics to solve combinatorial optimization problems

Expert systems with applications, 2021
Search methodologies such as hyper-heuristics have been successfully used to automate the generation of perturbative heuristics to solve combinatorial optimization problems.
George Mweshi, N. Pillay
semanticscholar   +1 more source

Grammatical Evolution

, 2009
Grammatical evolution (GE) is a recent grammar-based approach to genetic programming that allows development of solutions in an arbitrary programming language.
Ian Dempsey, Michael O’Neill, Anthony Brabazon   +2 more
openaire   +2 more sources

Multi-objective Grammatical Evolution of Decision Trees for Mobile Marketing user conversion prediction

Expert systems with applications, 2020
The worldwide adoption of mobile devices is raising the value of Mobile Performance Marketing, which is supported by Demand-Side Platforms (DSP) that match mobile users to advertisements.
P. Pereira, P. Cortez, R. Mendes
semanticscholar   +1 more source

Grammatical evolution of a robot controller

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009
An autonomous mobile robot requires an onboard controller that allows it to perform its tasks for long periods in isolation. One possibility is for the robot to adapt to its environment using some form of artificial intelligence. Evolutionary techniques such as genetic programming (GP) offer the possibility of automatically programming the controller ...
Robert Burbidge, Joanne H. Walker, Myra S. Wilson   +2 more
openaire   +1 more source

Adaptive Trading With Grammatical Evolution

2006 IEEE International Conference on Evolutionary Computation, 2006
This study reports on the performance of an on-line evolutionary automatic programming methodology for uncovering technical trading rules for the S& P 500 and Nikkei 225 indices. The system adopts a variable sized investment strategy based on the strength of the signals produced by the trading rules.
Ian Dempsey, Michael O'Neill 0001, Anthony Brabazon   +2 more
openaire   +1 more source

Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution

EvoApplications, 2020
The deployment of Machine Learning (ML) models is a difficult and time-consuming job that comprises a series of sequential and correlated tasks that go from the data pre-processing, and the design and extraction of features, to the choice of the ML ...
Filipe Assunção, Nuno Lourenço, B. Ribeiro, Penousal Machado   +3 more
semanticscholar   +1 more source

Analyzing Grammatical Evolution and $$\pi $$ π Grammatical Evolution with Grammar Model

2016
Grammatical evolution (GE) is an important automatic programming technique developed on the basis of genetic algorithm and context-free grammar. Making changes with either its chromosome structure or decoding method, we will obtain a great many GE variants such as \(\pi \)GE, model-based GE, etc.
Pei He, Zelin Deng, Chongzhi Gao, Liang Chang 0003, Achun Hu   +4 more
openaire   +1 more source

Improving Module Identification and Use in Grammatical Evolution

IEEE Congress on Evolutionary Computation, 2020
Exploiting patterns within a solution or reusing certain functionality is often necessary to solve certain problems. This paper proposes a new method for identifying useful modules.
Aidan Murphy, C. Ryan
semanticscholar   +1 more source