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Generation and adaptation of neural networks by evolutionary techniques (GANNET)

https://doi.org/10.1007/bf01411372
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf00993252openalex-snapshot
Dynamic Parameter Encoding for Genetic Algorithms
inferredcites →https://doi.org/10.1016/b978-0-934613-64-4.50021-9openalex-snapshot
Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms
inferredcites →https://doi.org/10.1109/37.55119openalex-snapshot
Neural networks for self-learning control systems
inferredcites →https://doi.org/10.13140/2.1.3459.2329openalex-snapshot
Learning to Tell Two Spirals Apart
inferredcites →https://doi.org/10.5860/choice.27-0936openalex-snapshot
Genetic algorithms in search, optimization, and machine learning
inferredcites →https://doi.org/10.7551/mitpress/1090.001.0001openalex-snapshot
Adaptation in Natural and Artificial Systems
inferredcites →https://doi.org/10.7551/mitpress/5236.001.0001openalex-snapshot
Parallel Distributed Processing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-1-4471-0427-8_8openalex-snapshot
Designing Neural Networks using a Genetic Rule-based System
inferred← citeshttps://doi.org/10.1007/978-3-7091-7535-4_27openalex-snapshot
Evolving Neural Network Structures: An Evaluation of Encoding Techniques
inferred← citeshttps://doi.org/10.1007/978-981-15-0994-0_6openalex-snapshot
A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization
inferred← citeshttps://doi.org/10.1007/bf01411373openalex-snapshot
Genetic algorithms and their applications to the design of neural networks
inferred← citeshttps://doi.org/10.1007/s00521-003-0364-1openalex-snapshot
Cooperative binary-real coded genetic algorithms for generating and adapting artificial neural networks
inferred← citeshttps://doi.org/10.1007/s10462-021-10049-5openalex-snapshot
Evolutionary design of neural network architectures: a review of three decades of research
inferred← citeshttps://doi.org/10.1016/0893-6080(94)90004-3openalex-snapshot
Self-organizing maps: Local competition and evolutionary optimization
inferred← citeshttps://doi.org/10.1016/j.neucom.2005.06.018openalex-snapshot
Evolutionary system for automatically constructing and adapting radial basis function networks
inferred← citeshttps://doi.org/10.1016/s1874-5946(98)80031-xopenalex-snapshot
Algorithmic techniques and their applications
inferred← citeshttps://doi.org/10.1023/a:1012337000887openalex-snapshot
An Algebraic Model for Generating and Adapting Neural Networks by Means of Optimization Methods
inferred← citeshttps://doi.org/10.1080/10629369308028829openalex-snapshot
Estimating Pesticide Field Half-lives from a Backpropagation Neural Network
inferred← citeshttps://doi.org/10.1109/kes.2000.884178openalex-snapshot
Optimum binary codification for genetic design of artificial neural networks
inferred← citeshttps://doi.org/10.1109/tnn.2003.809427openalex-snapshot
Lattice algebra approach to single-neuron computation
inferred← citeshttps://doi.org/10.18576/amis/110602openalex-snapshot
Neural Networks Optimization through Genetic Algorithm Searches: A Review
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