14 Result(s)
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Chapter and Conference Paper
Data Analysis Applied to Driver Profile Data Obtained Through Vehicle Telemetry and Classification Algorithms
In the present days, considering the enormous amount of unused data available, one of the most challenging tasks is extracting meaningful information from data obtained or stored; for the automotive industry, ...
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Chapter and Conference Paper
Urban Digital Twins for Synthetic Data of Individuals with Mobility Aids in Curitiba, Brazil, to Drive Highly Accurate AI Models for Inclusivity
This article delves into the significance of urban digital twins in generating synthetic data specifically tailored for individuals with disabilities. It explores how this data can be effectively utilized to c...
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Chapter and Conference Paper
A Multicriteria Framework Proposition for Project Management Approaches
One of the primary challenges in project management is to establish an effective methodology that can lead to both successful planning and stakeholder satisfaction. This is a critical decision that needs to be...
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Chapter and Conference Paper
A Proposal of a Fair Voting Ensemble Classifier Using Multi-objective Optimization
Current fair machine learning techniques attempt to maintain the trained pipeline accuracy while improving the fairness of its predictions through a myriad of mathematical definitions. Often, proposed methods ...
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Chapter and Conference Paper
Correction to: Data Science Applied to Vehicle Telemetry Data to Identify Driving Behavior Profiles
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Chapter and Conference Paper
Classification of Leukocytes: Comparison of Different Feature Extraction and Machine Learning Approaches
Blood cells can be separated into three types: erythrocytes, leukocytes and platelets, and to evaluate the health of a patient, a Complete Blood Count (CBC) is necessary. CBC is amongst the most performed test...
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Chapter and Conference Paper
Data Science Applied to Vehicle Telemetry Data to Identify Driving Behavior Profiles
Currently, vehicles have a vast number of sensors, which are important for their operation. To have greater control over the actions of vehicles, the sensors can be combined with telemetry, so that the data re...
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Chapter and Conference Paper
Multi-objective Fault Detection in Ball Bearings
Machine learning techniques are useful for maintenance scheduling, given their capabilities to detect failures or anomaly situations in mechanical equipment. Increasing the accuracy of any mechanical fault det...
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Chapter and Conference Paper
TimeStacking: An Improved Ensemble Learning Method for Continuous Time Series Classification
Machine learning has gained great attention for solving time series classification problems. However, usual machine learning algorithms rely on learning from tabular data, and additional signal processing and ...
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Chapter and Conference Paper
Multi-objective Logistic Regression for Anomaly Detection in Water Distribution Systems
Providing clean and safe drinking water is a crucial task for any water supply company. In such an activity, automatic anomaly detection plays a critical role in drinking water quality monitoring. Recent anoma...
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Chapter and Conference Paper
Spanish Control Engineering Challenge: An Educational Experience
The Concurso de Ingeniería de Control (CIC) (Engineering Control Challenge) is a student challenge organized by the Comité Español de Automática - CEA (Spanish Committee of Automation) from Spain. It was set as a...
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Chapter and Conference Paper
An Evolutionary Multiobjective Optimization Approach for HEV Energy Management System
Hybrid vehicles have become a promising solution to mitigate the negative effects of pollution and fossil fuel dependency, consequences (among other causes) of an increasing demand on mobility of people and go...
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Chapter and Conference Paper
Design of Continuous Controllers Using a Multiobjective Differential Evolution Algorithm with Spherical Pruning
Controller design has evolved to a multiobjective task, i.e., today is necessary to take into account, besides any performance requirement, robustness requisites, frequency domain specifications and uncertain mod...
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Chapter and Conference Paper
An Adaptive Parameter Control for the Differential Evolution Algorithm
The Differential Evolution is a floating-point evolutionary algorithm that has demonstrated good performance on locating the global optima in a wide variety of problems and applications. It has mainly three tu...
