Abstract. The paper presents and compares different methods for estimating the speed of a train from the measurement of the velocity of two.
The authors noted that, while the fuzzy logic and neural network approaches provided superior results to the heuristic approach, the difficulty in formally ...
Training speed and accuracy are significantly improved by applying second order gradient methods, such as Levenberg Marquardt algorithm [12] and neuron-by- ...
A comparison of machine learning models for speed estimation ...
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... speed estimation, including loess, support vector regression, and neural networks. ... Comparison of Neural and Conventional Approaches to Mode Choice Analysis.
In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport.
Nov 16, 2020 · This paper proposes an evaluation method based on a TS fuzzy neural network for evaluating the speed grade of public-transport lines.
The paper describes and compares some applications of neuro- fuzzy (NF) systems to estimate the speed of a train from the measure- ment of the velocity of ...
Dec 18, 2024 · This study investigates the insights obtained from traditional and DL-based acoustic detectors using the Mediterranean sperm whale as a case ...
This paper studies Deep Convolutional Neural Networks (DCNNs) for the accurate estimation of space–time traffic speeds given sparse data on freeways.
The main difference between both is that for the first one there is a dataset with inputs and the outputs are known, while unsupervised learning is a type of ...