A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets

2017 ◽  
Vol 27 (06) ◽  
pp. 1750028 ◽  
Author(s):  
Alberto Fernández ◽  
Cristobal José Carmona ◽  
María José del Jesus ◽  
Francisco Herrera
Keyword(s):  
Search Space ◽  
Learning Task ◽  
Ensemble Of Classifiers ◽  
Imbalanced Classification ◽  
Multi Objective ◽  
Wrapper Approach ◽  
C4.5 Decision Tree ◽  
Selection For ◽  
Selection Of

Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

scholarly journals A REAL PERSONNEL SELECTION PROBLEM USING THE GENERALIZED CHOQUET INTEGRAL METHODOLOGY

2018 ◽  
Vol 6 (2) ◽  
pp. 694-716
Author(s):  
Yavuz ÖZDEMİR ◽  
Kemal Gökhan NALBANT
Keyword(s):  
Human Resources ◽  
Personnel Selection ◽  
Selection Criteria ◽  
Choquet Integral ◽  
Human Resources Management ◽  
Selection Problem ◽  
Resources Management ◽  
Selection For ◽  
Selection Of

The main objective in the selection of personnel is to select the most appropriate candidate for a job. Personnel selection for human resources management is a very important issue.The aim of this paper is to determine the best-performing personnel for promotion using an application of a Multi Criteria Decision Making(MCDM) method, generalized Choquet integral, to a real personnel selection problem of a case study in Turkey and 17 alternatives are ranked according to personnel selection criteria (22 subcriteria are classified under 5 main criteria). The main contribution of this paper is to determine the interdependency among main criteria and subcriteria, the nonlinear relationship among them and the environmental uncertainties while selecting personnel alternatives using the generalized Choquet integral method with the experts’ view. To the authors’ knowledge, this will be the first study which uses the generalized Choquet Integral methodology for human resources. 

scholarly journals A REAL PERSONNEL SELECTION PROBLEM USING THE GENERALIZED CHOQUET INTEGRAL METHODOLOGY

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Yavuz ÖZDEMİR ◽  
Kemal Gökhan NALBANT
Keyword(s):  
Human Resources ◽  
Personnel Selection ◽  
Selection Criteria ◽  
Choquet Integral ◽  
Human Resources Management ◽  
Selection Problem ◽  
Resources Management ◽  
Selection For ◽  
Selection Of

The main objective in the selection of personnel is to select the most appropriate candidate for a job. Personnel selection for human resources management is a very important issue.The aim of this paper is to determine the best-performing personnel for promotion using an application of a Multi Criteria Decision Making(MCDM) method, generalized Choquet integral, to a real personnel selection problem of a case study in Turkey and 17 alternatives are ranked according to personnel selection criteria (22 subcriteria are classified under 5 main criteria). The main contribution of this paper is to determine the interdependency among main criteria and subcriteria, the nonlinear relationship among them and the environmental uncertainties while selecting personnel alternatives using the generalized Choquet integral method with the experts’ view. To the authors’ knowledge, this will be the first study which uses the generalized Choquet Integral methodology for human resources. 

scholarly journals GREEN SUPPLER SELECTION BY AN INTEGRATED METHOD WITH STOCHASTIC ACCEPTABILITY ANALYSIS AND MULTIMOORA

2020 ◽  
Vol 26 (3) ◽  
pp. 549-572
Author(s):  
Xiaomei Mi ◽  
Huchang Liao ◽  
Yi Liao ◽  
Qi Lin ◽  
Benjamin Lev ◽  
...  
Keyword(s):  
Supplier Selection ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Uncertain Information ◽  
Integrated Method ◽  
Selection For ◽  
Green Suppliers ◽  
Multimoora Method ◽  
Selection Of

In the process of supplier selection for green supply chain management, uncertain information may appear in alternatives’ performances or experts’ preferences. The stochastic multicriteria acceptability analysis (SMAA) is a beneficial technique to tackling the uncertain information in such a problem and the MULTIMOORA is a robust technique to aggregate alternatives’ utilities. This study dedicates to proposing an SMAA-MULTIMOORA method by considering the advantages of both methods. The integrated method can accept uncertain information as inputs. The steps of the SMAA-MULTIMOORA are illustrated. A case study about the selection of green suppliers is given to show the validity and robustness of the SMAA-MULTIMOORA method.

scholarly journals Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm

Aerospace ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 71
Author(s):  
Victor Gomez ◽  
Nicolas Gomez ◽  
Jorge Rodas ◽  
Enrique Paiva ◽  
Maarouf Saad ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Unmanned Aerial Vehicles ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Pid Tuning ◽  
Aerial Vehicles ◽  
The Stability ◽  
Selection Of

Unmanned aerial vehicles (UAVs) are affordable these days. For that reason, there are currently examples of the use of UAVs in recreational, professional and research applications. Most of the commercial UAVs use Px4 for their operating system. Even though Px4 allows one to change the flight controller structure, the proportional-integral-derivative (PID) format is still by far the most popular choice. A selection of the PID controller parameters is required before the UAV can be used. Although there are guidelines for the design of PID parameters, they do not guarantee the stability of the UAV, which in many cases, leads to collisions involving the UAV during the calibration process. In this paper, an offline tuning procedure based on the multi-objective particle swarm optimization (MOPSO) algorithm for the attitude and altitude control of a Px4-based UAV is proposed. A Pareto dominance concept is used for the MOPSO to find values for the PID comparing parameters of step responses (overshoot, rise time and root-mean-square). Experimental results are provided to validate the proposed tuning procedure by using a quadrotor as a case study.

Feature Selection for Helicopter Swashplate Bearing Fault Diagnosis

2017 ◽  
Author(s):  
Yong Wang ◽  
Lin Li
Keyword(s):  
Nearest Neighbor ◽  
Ball Bearing ◽  
K Nearest Neighbor ◽  
Time Frequency ◽  
Bearing Fault Diagnosis ◽  
Feature Extraction And Selection ◽  
Frequency Domains ◽  
Selection For ◽  
Selection Of

This paper provides a case study of diagnosing helicopter swashplate ball bearing faults using vibration signals. We develop and apply feature extraction and selection techniques in the time, frequency, and joint time-frequency domains to differentiate six types of swashplate bearing conditions: low-time, to-be-overhauled, corroded, cage-popping, spalled, and case-overlapping. With proper selection of the features, it is shown that even the simple k-nearest neighbor (k-NN) algorithm is able to correctly identify these six types of conditions on the tested data. The developed method is useful for helicopter swashplate condition monitoring and maintenance scheduling. It is also helpful for testing the manufactured swashplate ball bearings for quality control purposes.

scholarly journals Automated Quantum Hardware Selection for Quantum Workflows

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 984
Author(s):  
Benjamin Weder ◽  
Johanna Barzen ◽  
Frank Leymann ◽  
Marie Salm
Keyword(s):  
Quantum Computer ◽  
Quantum Algorithm ◽  
Software Tool ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Workflow Model ◽  
Selection For ◽  
Selection Of

The execution of a quantum algorithm typically requires various classical pre- and post-processing tasks. Hence, workflows are a promising means to orchestrate these tasks, benefiting from their reliability, robustness, and features, such as transactional processing. However, the implementations of the tasks may be very heterogeneous and they depend on the quantum hardware used to execute the quantum circuits of the algorithm. Additionally, today’s quantum computers are still restricted, which limits the size of the quantum circuits that can be executed. As the circuit size often depends on the input data of the algorithm, the selection of quantum hardware to execute a quantum circuit must be done at workflow runtime. However, modeling all possible alternative tasks would clutter the workflow model and require its adaptation whenever a new quantum computer or software tool is released. To overcome this problem, we introduce an approach to automatically select suitable quantum hardware for the execution of quantum circuits in workflows. Furthermore, it enables the dynamic adaptation of the workflows, depending on the selection at runtime based on reusable workflow fragments. We validate our approach with a prototypical implementation and a case study demonstrating the hardware selection for Simon’s algorithm.

scholarly journals Optimal pump selection for variable speed operation in water distribution network

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Débora Salomé Móller ◽  
Gustavo Meirelles Lima ◽  
Bruno Melo Brentan ◽  
Daniel Bezerra Barros
Keyword(s):  
Water Distribution ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Energy Costs ◽  
Variable Speed ◽  
Hydraulic Power ◽  
Pumping Stations ◽  
Selection For ◽  
Selection Of

ABSTRACT The optimization of pumping stations operation in water distribution networks has been largely studied, especially with the development of speed drivers, which allowed the machines to adjust the hydraulic power inserted to the system according to the demand requirements. Although this approach results in high benefits, the original characteristics of pumps remains the same. Consequently, the pumps can be operating in a range of suboptimal efficiency. Thus, this paper will evaluate the benefits that an optimized pump selection can bring for variable speed operation. The selection of the pumps best efficiency point and the number of pumps operating in parallel are defined applying Particle Swarm Optimization (PSO) to minimize the energy costs of the system. For the case study, the results show that there is no benefit when more pumps are operated in parallel, and that a flexible operational routine significantly reduces the energy expenses, especially when the pump is selected for this purpose.

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