[HTML][HTML] Early prediction of battery remaining useful life using CNN-XGBoost model and Coati optimization algorithm
Abstract Lithium-ion (Li-ion) batteries are essential for modern power systems but suffer from
performance degradation over time. Accurate prediction of the remaining useful life (RUL) of …
performance degradation over time. Accurate prediction of the remaining useful life (RUL) of …
Hyperparameter learning for deep learning-based recommender systems
Deep learning (DL)-based recommender system (RS), particularly for its advances in the
recent five years, has been startling. It reshapes the architectures of traditional RSs by lifting …
recent five years, has been startling. It reshapes the architectures of traditional RSs by lifting …
Climate change, forest fires, and territorial dynamics in the Amazon rainforest: an integrated analysis for mitigation strategies
Recent times have witnessed wildfires causing harm to both ecological communities and
urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess …
urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess …
Design of a forest fire early alert system through a deep 3D-CNN structure and a WRF-CNN bias correction
A Casallas, C Jiménez-Saenz, V Torres… - Sensors, 2022 - mdpi.com
Throughout the years, wildfires have negatively impacted ecological systems and urban
areas. Hence, reinforcing territorial risk management strategies against wildfires is essential …
areas. Hence, reinforcing territorial risk management strategies against wildfires is essential …
Stable conformal prediction sets
E Ndiaye - International Conference on Machine Learning, 2022 - proceedings.mlr.press
When one observes a sequence of variables $(x_1, y_1),\ldots,(x_n, y_n) $, Conformal
Prediction (CP) is a methodology that allows to estimate a confidence set for $ y_ {n+ 1} …
Prediction (CP) is a methodology that allows to estimate a confidence set for $ y_ {n+ 1} …
Design of an early alert system for PM2. 5 through a stochastic method and machine learning models
Abstract In Latin America, the levels of pollution have risen considerably in the last few
years. 2019, for example, had one of the largest numbers of air quality alerts. These alerts …
years. 2019, for example, had one of the largest numbers of air quality alerts. These alerts …
Fine-grained prediction of PM2. 5 concentration based on multisource data and deep learning
X Xu, T Tong, W Zhang, L Meng - Atmospheric Pollution Research, 2020 - Elsevier
With China's economic development, air pollution has become increasingly serious.
Studying the concentration of PM2. 5, as the main component of haze, is the key to control …
Studying the concentration of PM2. 5, as the main component of haze, is the key to control …
Lassobench: A high-dimensional hyperparameter optimization benchmark suite for lasso
Abstract While Weighted Lasso sparse regression has appealing statistical guarantees that
would entail a major real-world impact in finance, genomics, and brain imaging applications …
would entail a major real-world impact in finance, genomics, and brain imaging applications …
Unsuccessful story about few shot malware family classification and siamese network to the rescue
To battle the ever-increasing Android malware, malware family classification, which
classifies malware with common features into a malware family, has been proposed as an …
classifies malware with common features into a malware family, has been proposed as an …
Long short-term memory artificial neural network approach to forecast meteorology and PM2.5 local variables in Bogotá, Colombia
In places with complex topography, the reproduction of atmospheric dynamics is challenging
and resource demanding. Recently, machine learning has been successfully implemented …
and resource demanding. Recently, machine learning has been successfully implemented …