Results 51 to 60 of about 116,877 (316)
Tactics Exploration Framework based on Genetic Programming
International Journal of Computational Intelligence Systems, 2017 Engagement-level simulation is a quantitative way to evaluate the effectiveness of weapon systems before construction and acquisition, minimizing the risk of investment. Though contractors have built simulation systems with high fidelity models of weapon
Jian Yao +4 more
doaj +1 more source
Open Computer Science, 2014 Abstract We present evolutionary approach to program development based on absorption of genetic strings at different metalevels. Introducing the principles of software evolution as processes of semantical stability, expansion and contraction, we continue with an example illustrating how it is possible to integrate metalevel with base ...
Ján Kollár, Emília Pietriková
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Ensemble Genetic Programming [PDF]
, 2020 Ensemble learning is a powerful paradigm that has been usedin the top state-of-the-art machine learning methods like Random Forestsand XGBoost. Inspired by the success of such methods, we have devel-oped a new Genetic Programming method called Ensemble GP. The evo-lutionary cycle of Ensemble GP follows the same steps as other GeneticProgramming systems,
Nuno M. Rodrigues +2 more
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Supporting Survivor‐Centered Care Through Digital Health Integration
Pediatric Blood &Cancer, EarlyView.ABSTRACT Survivors of childhood cancer face barriers to receiving guideline‐based, long‐term follow‐up care. Two digital tools, Passport for Care (PFC) and Cancer SurvivorLink (SurvivorLink), address complementary gaps by enabling tailored survivorship care plan (SCP) generation, updating, storage, and sharing.
Jordan G. Marchak +15 more
wiley +1 more source
Genetic Algorithms and Genetic Programming for Control
, 1997 The use of genetic algorithms and genetic programming in control engineering has started to expand in the last few years. This is mainly for two reasons: the physical cost of implementing a known control algorithm and the difficulty to find such an ...
Dracopoulos, D.
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Finding efficient nonlinear functions by means of genetic programming [PDF]
, 2003 7th International Conference, KES 2003. Proceedings, Part I. Oxford, UK, September 3-5, 2003The design of highly nonlinear functions is relevant for a number of different applications, ranging from database hashing to message authentication.
Pedro Isasi Viñuela +6 more
core +1 more source
Genetic Programming to Optimize 3D Trajectories
ISPRS International Journal of Geo-InformationTrajectory optimization is a method of finding the optimal route connecting a start and end point. The suitability of a trajectory depends on not intersecting any obstacles, as well as predefined performance metrics.
André Kotze +3 more
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Scientific Reports, 2023 Formation damage poses a widespread challenge in the oil and gas industry, leading to diminished permeability, flow rates, and overall well productivity. Acidizing is a commonly employed technique aimed at mitigating damage and enhancing permeability. In
Matin Dargi +2 more
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Hydropower Unit Commitment Using a Genetic Algorithm with Dynamic Programming
Energies, 2023 This study presents a genetic algorithm integrated with dynamic programming to address the challenges of the hydropower unit commitment problem, which is a nonlinear, nonconvex, and discrete optimization, involving the hourly scheduling of generators in ...
Shuangquan Liu +6 more
doaj +1 more source
Polytypic Genetic Programming [PDF]
, 2017 Program synthesis via heuristic search often requires a great deal of ‘boilerplate’ code to adapt program APIs to the search mechanism. In addition, the majority of existing approaches are not type-safe: i.e. they can fail at runtime because the search mechanisms lack the strict type information often available to the compiler.
Jerry Swan +2 more
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