Ensemble Neuroevolution-Based Approach for Multivariate Time Series Anomaly Detection [PDF]
Entropy, 2021 Multivariate time series anomaly detection is a widespread problem in the field of failure prevention. Fast prevention means lower repair costs and losses.
Kamil Faber +2 more
exaly +4 more sources
Neuroevolution on the Edge of Chaos [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference, 2017 Echo state networks represent a special type of recurrent neural networks. Recent papers stated that the echo state networks maximize their computational performance on the transition between order and chaos, the so-called edge of chaos.
Beggs John M +2 more
core +2 more sources
Improving the performance of mutation-based evolving artificial neural networks with self-adaptive mutations. [PDF]
PLoS ONENeuroevolution is a promising approach for designing artificial neural networks using an evolutionary algorithm. Unlike recent trending methods that rely on gradient-based algorithms, neuroevolution can simultaneously evolve the topology and weights of ...
Motoaki Hiraga +4 more
doaj +2 more sources
Towards the Neuroevolution of Low-level artificial general intelligence [PDF]
Frontiers in Robotics and AI, 2022 In this work, we argue that the search for Artificial General Intelligence should start from a much lower level than human-level intelligence. The circumstances of intelligent behavior in nature resulted from an organism interacting with its surrounding ...
Sidney Pontes-Filho +14 more
doaj +2 more sources
Neuroevolution Guided Hybrid Spiking Neural Network Training [PDF]
Frontiers in Neuroscience, 2022 Neuromorphic computing algorithms based on Spiking Neural Networks (SNNs) are evolving to be a disruptive technology driving machine learning research.
Sen Lu, Abhronil Sengupta
doaj +2 more sources
Neuroevolution for Parameter Adaptation in Differential Evolution
Algorithms, 2022 Parameter adaptation is one of the key research fields in the area of evolutionary computation. In this study, the application of neuroevolution of augmented topologies to design efficient parameter adaptation techniques for differential evolution is ...
Vladimir Stanovov +2 more
exaly +3 more sources
Incentivising cooperation by judging a group’s performance by its weakest member in neuroevolution and reinforcement learning [PDF]
Frontiers in Robotics and AIIntroductionAutonomous agents increasingly interact within social domains such as customer service, transportation, and healthcare, often acting collectively on behalf of humans.
Jory Schossau +3 more
doaj +2 more sources
Real Time Predictive and Adaptive Hybrid Powertrain Control Development via Neuroevolution
Vehicles, 2022 The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains.
Frederic Jacquelin +6 more
doaj +1 more source
IEEE Access, 2021 Neural architecture search has proven to be highly effective in the design of efficient convolutional neural networks that are better suited for mobile deployment than hand-designed networks.
William McNally +3 more
doaj +1 more source
NeuroSCA: Evolving Activation Functions for Side-Channel Analysis
IEEE Access, 2023 The choice of activation functions can significantly impact the performance of neural networks. Due to an ever-increasing number of new activation functions being proposed in the literature, selecting the appropriate activation function becomes even more
Karlo Knezevic +4 more
doaj +1 more source