An appraisal of incremental learning methods
As a special case of machine learning, incremental learning can acquire useful knowledge
from incoming data continuously while it does not need to access the original data. It is …
from incoming data continuously while it does not need to access the original data. It is …
A taxonomy of food supply chain problems from a computational intelligence perspective
JS Angarita-Zapata, A Alonso-Vicario, AD Masegosa… - Sensors, 2021 - mdpi.com
In the last few years, the Internet of Things, and other enabling technologies, have been
progressively used for digitizing Food Supply Chains (FSC). These and other digitalization …
progressively used for digitizing Food Supply Chains (FSC). These and other digitalization …
An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes
Customer churn is a complex challenge for burgeoning competitive organizations,
especially in telecommunication. It refers to customers that swiftly leave a company for a …
especially in telecommunication. It refers to customers that swiftly leave a company for a …
Smart user consumption profiling: Incremental learning-based OTT service degradation
Data caps and service degradation are techniques used to control subscribers' data
consumption. These techniques have emerged mainly due to the growing demands placed …
consumption. These techniques have emerged mainly due to the growing demands placed …
Using stream data processing for real-time occupancy detection in smart buildings
Controlling active and passive systems in buildings with the aim of optimizing energy
efficiency and maintaining occupants' comfort is the major task of building management …
efficiency and maintaining occupants' comfort is the major task of building management …
Integration of the Machine Learning Algorithms and I-MR Statistical Process Control for Solar Energy
The importance of solar power generation facilities, as one of the renewable energy types, is
increasing daily. This study proposes a two-way validation approach to verify the validity of …
increasing daily. This study proposes a two-way validation approach to verify the validity of …
Investigating the terrain of class-incremental continual learning: A brief survey
Continual learning, a crucial facet of machine learning, involves the perpetual acquisition of
valuable insights from incoming data, sans the necessity for full dataset access. Esteemed …
valuable insights from incoming data, sans the necessity for full dataset access. Esteemed …
A bibliometric analysis and benchmark of machine learning and automl in crash severity prediction: The case study of three colombian cities
Traffic accidents are of worldwide concern, as they are one of the leading causes of death
globally. One policy designed to cope with them is the design and deployment of road safety …
globally. One policy designed to cope with them is the design and deployment of road safety …
An incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic
Several works have proposed predictive models of the SEIRD (Susceptible, Exposed,
Infected, Recovered, and Dead) variables to characterize the pandemic of COVID-19. One of …
Infected, Recovered, and Dead) variables to characterize the pandemic of COVID-19. One of …
[HTML][HTML] A review and perspective on hybrid modelling methodologies
The term hybrid modeling refers to the combination of parametric models (typically derived
from knowledge about the system) and nonparametric models (typically deduced from data) …
from knowledge about the system) and nonparametric models (typically deduced from data) …