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Wyniki wyszukiwania dla: PREDICTIVE MACHINE LEARNING-BASED TOOLS
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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THE INFLUENCE OF QUESTION SET ON STUDENT QUIZ RESULTS
PublikacjaThe advent of e-Learning tools allowing for automated online test grading will probably increase the frequency of using tests in technical education. The same tools may provide for measures of test question quality. By purposely crafting question sets, test grading may serve different goals. The paper contains examples and test study with score histograms.
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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublikacjaPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublikacjaSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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A Concept of Automatic Film Color Grading Based on Music Recognition and Evoked Emotions
PublikacjaThe article presents the aspects of the final selection of the color of shots in film production based on the psychology of color. First of all, the elements of color processing, contrast, saturation or white balance in the film shots were presented and the definition of color grading was given. In the second part of the article the analysis of film music was conducted in the context of stimulating appropriate emotions while watching...
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Engineering education for smart grid systems in the quasi-industrial environment of the LINTE^2 laboratory
PublikacjaSmart grid systems are revolutionising the electric power sector, integrating advanced technologies to enhance efficiency, reliability and sustainability. It is important for higher education to equip the prospective smart grid professional with the competencies enabling them to navigate through the related complexities and drive innovation. To achieve this, interdisciplinary education programmes are necessary, addressing inter...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublikacjaThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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Prediction of cutting forces during micro end milling considering chip thickness accumulation
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The estimation of cutting forces and specific force coefficients during finishing ball end milling of inclined surfaces
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Augmenting digital documents with negotiation capability
PublikacjaActive digital documents are not only capable of performing various operations using their internal functionality and external services, accessible in the environment in which they operate, but can also migrate on their own over a network of mobile devices that provide dynamically changing execution contexts. They may imply conflicts between preferences of the active document and the device the former wishes to execute on. In the...
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Using Moodle as a Solution to Interdisciplinary E-collaboration Issues
PublikacjaRapid technological development in recent years has contributed to numerous changes in many areas of life, including education and communication. Establishing interdisciplinary collaboration brings many benefits, however, it is often associated with numerous problems and inconveniences, as well as the need of constant improvement, lifelong learning, professional development (CPD) and finding an effective way of information transferring....
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Factors Affecting the Effectiveness of Military Training in Virtual Reality Environment
PublikacjaIn this paper, we explored the factors influencing the effectiveness of military trainings performed in a virtual reality environment. The rationale for taking up the topic is the fact that such trainings are often conducted under specific operational procedures. These procedures may create rigorous frameworks for all elements of the learning environment, including the teacher’s performance. Therefore, to ensure the most conducive...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Scenario-planning solutions for waterfront flood-prone areas
PublikacjaThe aim of this article is to discuss the potential of applying scenario planning to achieve resilient and future-oriented solutions for flood-prone areas. The authors have proposed additions to scenario-planning processes based on the introduction of research-by-design architectural inquiries. Examined in this article is the insight into the testing of such a modified scenario-planning methodology during two courses that accompanied...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublikacjaBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Topological-numerical analysis of a two-dimensional discrete neuron model
PublikacjaWe conduct computer-assisted analysis of a two-dimensional model of a neuron introduced by Chialvo in 1995 [Chaos, Solitons Fractals 5, 461–479]. We apply the method of rigorous analysis of global dynamics based on a set-oriented topological approach, introduced by Arai et al. in 2009 [SIAM J. Appl. Dyn. Syst. 8, 757–789] and improved and expanded afterward. Additionally, we introduce a new algorithm to analyze the return times...
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Double Fed Induction Machine Drives
PublikacjaContents of the Chapter 22:Machine model.Properties of the DFM.Steady state machine operation.Control rules and decoupled control.Decoupling based on MM machine model.Decoupling based on vector model.Decoupling based on rotor current equation.Overall control system.Control system based on MM model.Control system based on vector model.Estimation of variables.Calculation of the angle between stator and rotor.Remarks about digital...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublikacjaW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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The reduction of vibrations in circular sawing machines
PublikacjaThe presented in this paper the main objectives of the research were to explore vibrations signals of the main spindle system, the machine tool body and a circular saw to extract informative features for assessment of the designs of the panel saw Fx3 and its follower Fx550.Even though the main spindle of the new table sliding saw Fx550 has its rotational speeds larger about 20% in comparison to the Fx3, peak values of the vibrational...
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Enterprise Gamification - Learning as a Side Effect of Competition
PublikacjaGmification in companies can be used for driving desired employees behaviour that are advantageous to their development and performance improvement. This paper presents tools acquired from online social networking services and game mechanisms to encourage managers to compete by providing extended statistics and user profiles features in e-learning system.
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Zastosowanie metody studium przypadku w kształceniu menedżerów
PublikacjaKształcenie z wykorzystaniem metod rozwiązywania problemów (problem-based learning) staje się coraz bardziej popularne na wszystkich poziomach kształcenia, również w edukacji biznesowej. Przykładem takiej metody jest studium przypadku (case study). Metoda studium przypadku pozwala na rozwijanie umiejętności i kompetencji wykorzystywanych przez menedżerów w ich pracy, np. umiejętności syntezy, identyfikacji problemów, czy podejmowania...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublikacjaThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?
PublikacjaThe estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...
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Robustness Analysis of a Distributed MPC Control System of a Turbo-Generator Set of a Nuclear Plant – Disturbance Issues
PublikacjaTypically, there are two main control loops with PI controllers operating at each turbo-generator set. In this paper, a distributed model predictive controller with local quadratic model predictive controllers for the turbine generator is proposed instead of a set of classical PI controllers. The local quadratic predictive controllers utilize step-response models for the controlled system components. The parameters of these models...
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Key activities to improve energy management in DC microgrids connected by urban traction
PublikacjaDC MicroGrids must have Energy Management Systems to guarantee efficient, dependable, and environmentally friendly electricity. The application of Model Predictive Control, proved to be helpful due to its adaptability and capacity to use non-linear models. This paper, based on an extensive literature review, identifies and discusses the three key activities to improve the characteristics of DC MicroGrids, i.e.: the use of Energy...
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublikacjaIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublikacjaComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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The Design Development of the Sliding Table Saw Towards Improving Its Dynamic Properties
PublikacjaCutting wood with circular saws is a popular machining operation in the woodworking and furniture industries. In the latter sliding table saws (panel saws) are commonly used for cutting of medium density fiberboards (MDF), high density fiberboards (HDF), laminate veneer lumber (LVL), plywood and chipboards of different structures. The most demanded requirements for machine tools are accuracy and precision, which mainly depend on...
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IFE: NN-aided Instantaneous Pitch Estimation
PublikacjaPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Mobile Activity Plan Applications for Behavioral Therapy of Autistic Children
PublikacjaThis paper concerns technological support for behavioral therapy of autistic children. A family of tools dedicated for mobile devices is presented, that allows to design and perform an activity schedule in behavioral therapy. The paper describes the main challenges, that were encountered, especially in meeting the non-functional requirements of the application: simplicity, repeatability, robustness, personalization, re-usability...
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Sensorless predictive control of three-phase parallel active filter
PublikacjaThe paper presents the control system of parallel active power filter (APF) with predictive reference current calculation and model based predictive current control. The novel estimator and predictor of grid emf is proposed for AC voltage sensorless operation of APF, regardless of distortion of this voltage. Proposed control system provides control of APF current with high precision and dynamics limited only by filter circuit parameters....
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublikacjaThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublikacjaSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Buzz-based honeybee colony fingerprint
PublikacjaNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Affective Learning Manifesto – 10 Years Later
PublikacjaIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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Triangulation-based Constrained Surrogate Modeling of Antennas
PublikacjaDesign of contemporary antenna structures is heavily based on full-wave electromagnetic (EM) simulation tools. They provide accuracy but are CPU-intensive. Reduction of EM-driven design procedure cost can be achieved by using fast replacement models (surrogates). Unfortunately, standard modeling techniques are unable to ensure sufficient predictive power for real-world antenna structures (multiple parameters, wide parameter ranges,...
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Application of IT tools in Educational Project Dissemination – Example of the INNOCASE Project
PublikacjaThe chapter presents innovative approaches (based on IT) to educational project dissemination. The appearance of the Internet and various tools based on it allowed using new methods and channels of getting to target groups and project beneficiaries. The chapter describes a great deal of dissemination means based on IT tools that are available to contemporary project manager of an educational project. These tools might be applied...
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublikacjaIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublikacjaPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection
PublikacjaAs a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublikacjaThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...