Data selection for system identification (DS4SID) from logged process records of continuously operated plants

2020 ◽  
Vol 68 (5) ◽  
pp. 347-359
Author(s):  
David Arengas ◽  
Andreas Kroll
Keyword(s):  
System Identification ◽  
Negative Impact ◽  
Information Matrix ◽  
Process Data ◽  
Large Databases ◽  
Selection For ◽  
Autocorrelated Noise ◽  
Source Of Information ◽  
Selection Of

AbstractUse of historical logged data can be considered for system identification if performing dedicated experiments is not possible. Continuously operated plants are examples of processes where experiments for system identification are typically restricted due to a possibly negative impact on production. However, process variables are logged for long periods of time which results in large databases that are a valuable source of information for model estimation. Automatic selection of informative data intervals can support system identification when use of logged process data is addressed. A new method is presented that differs in several aspects from current approaches. Firstly, interval bounding is performed using the gradient of a norm associated to the resulting information matrix which decreases interval misdetection. Secondly, process data do not need to be normalized for change detection. Thirdly, an instrumental variables identification method is used which offers robustness to autocorrelated noise. Lastly, the proposed selection technique can be applied to multivariate processes. The performance of the proposed method is demonstrated in a case study implemented in a lab-scale chemical plant.

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.

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.

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.

Mathematics Exercise Generator

2020 ◽  
pp. 264-282
Author(s):  
Maria Paula Oliveira ◽  
Paula Carvalho
Keyword(s):  
Learning Strategies ◽  
Teaching And Learning ◽  
First Year ◽  
Learning Needs ◽  
First Year Students ◽  
Support Students ◽  
Source Of Information ◽  
Series Of Functions ◽  
Selection Of

Nowadays, the process of teaching and learning is changing from a traditional model in which teachers were the source of information to a model in which teachers appear as advisors who carefully observe students, assist in the selection of information by identifying their learning needs, and support students in their autonomous study. In this chapter, the authors describe an approach used in curricular units of first year in science and engineer degrees, which results from a connection of three projects born in University of Aveiro—MEGUA, SIACUA, and PmatE—and the interconnections of their informatics platforms. Although any scientific area besides mathematics can use this tool, the authors focus in a case study using an example on a specific topic of calculus courses for first year students on Engineering: Sequences and Series of Functions. The methodology described allows teachers to achieve further goals on learning strategies and students to have enough material to practice.

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.

scholarly journals DYNAMIC PROBABILITY SELECTION FOR FLOWER POLLINATION ALGORITHM BASED ON METROPOLISHASTINGS CRITERIA

2020 ◽  
Vol 20 ◽  
Author(s):  
Kamal Zuhairi Zamli ◽  
Fakhrud Din ◽  
Abdullah Nasser ◽  
Nazirah Ramli ◽  
Noraini Mohamed
Keyword(s):  
Heuristic Algorithms ◽  
Flower Pollination Algorithm ◽  
Adaptive Selection ◽  
Dynamic Selection ◽  
Flower Pollination ◽  
Selection For ◽  
Test Suite Generation ◽  
Selection Of

Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. However, FPA still suffers from variability of its performance as there is no one size that fits all values for pa, depending on the characteristics of the optimisation function. This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. Adopting the problem of t-way test suite generation as the case study and with the comparative evaluation with the original FPA, FPA-MH gave promising results owing to its dynamic and adaptive selection of search operators based on the need of the current search.  

Identifying Measurement Invariant Item Sets in Cross-Cultural Settings Using an Automated Item Selection Procedure

Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 177-188 ◽  
Author(s):  
Martin Schultze ◽  
Michael Eid
Keyword(s):  
Measurement Invariance ◽  
Optimal Solution ◽  
Selection Procedure ◽  
Cross Cultural ◽  
Item Selection ◽  
Ant System ◽  
Item Quality ◽  
Ant System Algorithm ◽  
Selection For ◽  
Selection Of

Abstract. In the construction of scales intended for the use in cross-cultural studies, the selection of items needs to be guided not only by traditional criteria of item quality, but has to take information about the measurement invariance of the scale into account. We present an approach to automated item selection which depicts the process as a combinatorial optimization problem and aims at finding a scale which fulfils predefined target criteria – such as measurement invariance across cultures. The search for an optimal solution is performed using an adaptation of the [Formula: see text] Ant System algorithm. The approach is illustrated using an application to item selection for a personality scale assuming measurement invariance across multiple countries.

Sign in / Sign up

Export Citation Format

Share Document