Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning
Deep learning models have revolutionized numerous fields, yet their decision-making
processes often remain opaque, earning them the characterization of “black-box” models …
processes often remain opaque, earning them the characterization of “black-box” models …
Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models
As a significant global concern, air pollution triggers enormous challenges in public health
and ecological sustainability, necessitating the development of precise algorithms to …
and ecological sustainability, necessitating the development of precise algorithms to …
Novel MIA-LSTM Deep Learning Hybrid Model with Data Preprocessing for Forecasting of PM2.5
Day by day pollution in cities is increasing due to urbanization. One of the biggest
challenges posed by the rapid migration of inhabitants into cities is increased air pollution …
challenges posed by the rapid migration of inhabitants into cities is increased air pollution …
A Comprehensive Bibliometric Analysis of Missing Value Imputation
Data quality plays a crucial role in tasks, such as enhancing the accuracy of data analytics
and avoiding the accumulation of redundant data. One of the significant challenges in data …
and avoiding the accumulation of redundant data. One of the significant challenges in data …
[HTML][HTML] Improving Air Quality Data Reliability through Bi-Directional Univariate Imputation with the Random Forest Algorithm
Forecasting the future levels of air pollution provides valuable information that holds
importance for the general public, vulnerable populations, and policymakers. High-quality …
importance for the general public, vulnerable populations, and policymakers. High-quality …
Development of an integrated machine learning model to improve the secondary inorganic aerosol simulation over the Bei**g–Tian**–Hebei region
Secondary inorganic aerosols (sulfate, nitrate, and ammonium, SNA) are the key
components of PM 2.5 in China. Accurate and seamless SNA concentration data therefore …
components of PM 2.5 in China. Accurate and seamless SNA concentration data therefore …
A complete air pollution monitoring and prediction framework
The issue of air pollution is increasingly prominent and represents a significant
environmental challenge, particularly in urban areas affected by rising migration rates. Air …
environmental challenge, particularly in urban areas affected by rising migration rates. Air …
A new imputation technique based a multi-Spike Neural Network to handle missing data in the Internet of Things Network (IoT)
Over the past decade, the Internet of Thing (IoT) devices have been deployed in wide-scale
several applications to collect vast amount of data from different locations in a time-series …
several applications to collect vast amount of data from different locations in a time-series …
An electronic sense-based machine learning model to predict formulas and processes for vegetable-fruit beverages
HB Ren, BL Feng, HY Wang, JJ Zhang, XS Bai… - … and Electronics in …, 2023 - Elsevier
Develo** vegetable-fruit beverages is complicated, requiring redundant formula design
and continuous process adjustment and hindering rapid intervention. This study aimed to …
and continuous process adjustment and hindering rapid intervention. This study aimed to …
Mortality prediction using medical time series on TBI patients
Abstract Background and objective Traumatic Brain Injury (TBI) is one of the leading causes
of injury-related mortality in the world, with severe cases reaching mortality rates of 30-40 …
of injury-related mortality in the world, with severe cases reaching mortality rates of 30-40 …