Parcourir par sujet "Neural-networks"
Voici les éléments 1-17 de 17
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Clustering Informed MLP Models for Fast and Accurate Short-Term Load Forecasting
(2022)The stable and efficient operation of power systems requires them to be optimized, which, given the growing availability of load data, relies on load forecasting methods. Fast and highly accurate Short-Term Load Forecasting ... -
Day-ahead natural gas demand forecasting in hourly resolution
(2021)Natural Gas (NG) demand forecasting is a research topic that starts to gather the attention of scholars, research institutions, utilities, retailers and other interested parties. Accurate predictions of future needs for ... -
A Deep Reinforcement Learning Motion Control Strategy of a Multi-rotor UAV for Payload Transportation with Minimum Swing
(2022)This paper addresses the problem of controlling a multirotor UAV with a cable-suspended load. In order to ensure the safe transportation of the load, the swinging motion, induced by the strongly coupled dynamics, has to ... -
Elements of TinyML on Constrained Resource Hardware
(2022)The next phase of intelligent computing could be entirely reliant on the Internet of Things (IoT). The IoT is critical in changing industries into smarter entities capable of providing high-quality services and products. ... -
Error Compensation Enhanced Day-Ahead Electricity Price Forecasting
(2022)The evolution of electricity markets has led to increasingly complex energy trading dynamics and the integration of renewable energy sources as well as the influence of several external market factors contributed towards ... -
Feed Forward Neural Network Sparsification with Dynamic Pruning
(2021)A recent hot research topic in deep learning concerns the reduction of the model size of a neural network by pruning, in order to minimize its training and inference cost and thus, being capable of running on devices with ... -
A Generalised Approach on Kerf Geometry Prediction during CO2 Laser cut of PMMA Thin Plates using Neural Networks
(2021)This study presents an application of feedforward and backpropagation neural network (FFBP-NN) for predicting the kerf characteristics, i.e. the kerf width in three different distances from the surface (upper, middle and ... -
Hidden neural networks for transmembrane protein topology prediction
(2021)Hidden Markov Models (HMMs) are amongst the most successful methods for predicting protein features in biological sequence analysis. However, there are biological problems where the Markovian assumption is not sufficient ... -
Hyper-parameters Tuning of Artificial Neural Networks: An Application in the Field of Recommender Systems
(2022)In this work, we carry out the hyper-parameters tuning of a Machine Learning (ML) Recommender Systems (RS) which utilizes an Artificial Neural Network (ANN), called CATA++. We have performed tuning of the activation function, ... -
Knowledge distillation on neural networks for evolving graphs
(2021)Graph representation learning on dynamic graphs has become an important task on several real-world applications, such as recommender systems, email spam detection, and so on. To efficiently capture the evolution of a graph, ... -
A meta-modeling power consumption forecasting approach combining client similarity and causality
(2021)Power forecasting models offer valuable insights on the electricity consumption patterns of clients, enabling the development of advanced strategies and applications aimed at energy saving, increased energy efficiency, and ... -
Model reduction of feed forward neural networks for resource-constrained devices
(2022)Multilayer neural architectures with a complete bipartite topology have very high training time and memory requirements. Solid evidence suggests that not every connection contributes to the performance; thus, network ... -
Overlapped Sound Event Classification via Multi-Channel Sound Separation Network
(2021)Overlapped sound event classification (SEC) can be a challenging task, especially in scenarios where the number of possible event classes or the number of simultaneous events occurring (polyphony level) are large. In such ... -
Renewable energy sources generation forecasting in aggregated energy system level
(2021)Renewable Energy Sources (RES) generation forecasting is an approach to handle the stochasticity of RES. This concept is very crucial to transform RES plants into dispatchable and integrated them for contemporary energy ... -
A Review of Machine Learning and TinyML in Healthcare
(2021)Healthcare is the field that can benefit from the large amount of raw data generated from portable and wearable devices. This data must be sent to the Cloud for processing due to the computationally intensive nature of ... -
Sensor Placement for Lifetime Extension by Applying Neural Network Configuration under Coverage and Energy Constraints
(2022)In deployments of Wireless Sensor Networks (WSNs), sensor placement, coverage, connectivity and energy constraints determine the overall network lifetime. In large-size WSNs it is difficult to maintain a trade-off among ... -
Short-term Electric Load Forecasting using Engineering and Deep Learning techniques
(2022)Load forecasting in the energy sector is an integral part of the electrical system as it is a criterion for its smooth and sustainable operation. The liberalization of electricity, the entry of RES into production and the ...