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1
artículo
The companies increasingly interact with clients and providers. This situation requires adequate risk ma-nagement to prevent situations of financial distress. A company is technically insolvent when it has enough cash to make immediate payments. Therefore, one of the points to study is the financial solvency and risk to the bankruptcy of its customer base. To this end, there are techniques to measure the possibility of insolvency of a company. The most reliable is the Altman Z model, which is based on the statistical technique of Multiple Discriminant Analysis. This model uses financial ratios to determine the financial risk and predict whether a company is healthy from a financial point of view, or is on its way to become insolvent. The results found by Altman and revision of the original model proposed by him is presented.
2
artículo
Publicado 1999
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ARIMA univariate time series analysis were used for modeling and forecasting future energy production and consumption in Asturias-Spain. Initially, each series was recorder monthly from 1980 to 1996. These data include trend and seasonal variations wich allow the use of ARIMA (AutoRegressive Integrated Moving Average) univariate models for predictions of future behavioral patterns. The optimum forecasting models obtained for each energetic series, have a satisfactory degree of statistical validity (Low approximation errors) and are suitable for use as reference inputs in the Regional Energetic Plan of Asturias.
3
artículo
Publicado 2019
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Purpose – Personal bankruptcy is on the rise in Malaysia. The Insolvency Department of Malaysia reported that personal bankruptcy has increased since 2007 and the total accumulated personal bankruptcy cases stood at 131282 in 2014. This is indeed an alarming Issue because the increasing number of personal bankruptcy cases will have a negative impact on the Malaysian economy as well as on the society. From the aspect of individual’s personal economy bankruptcy minimizes their chances of securing a job. Apart from that their account will be frozen lost control on their assets and properties andnot allowed to start any business nor be a part of any company’s management. Bankrupts also will be denied from any loan application restricted from travelling overseas and cannot act as a guarantor. This paper aims to investigate this problem by developing the personal bankruptcy prediction mo...
4
artículo
Publicado 2021
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The purpose of the study was to describe the analytical bioevaluation of the predictive model of science in aquatic ecotoxicology. From the Sciencedirect website, 18 scientific reviews, 72 scientific articles, six encyclopedias and 32 book chapters corresponding to 11 scientific journals were analyzed. Two descriptors were proposed: 1st) of the field conditions which referred to the natural development of organisms and, 2nd) of the laboratory conditions where three types of tests were considered: A) potential of toxicity, B) of growth and, C) transformation. Although, the advantage of field conditions is the disadvantage in laboratory conditions, it is essential that bio-assessments are combined for ecosystem services to be sustainable in society. From various bioevaluations of field and laboratory conditions, data that have statistical significance and its argumentation constitute new p...
5
artículo
Publicado 2021
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The purpose of the study was to describe the analytical bioevaluation of the predictive model of science in aquatic ecotoxicology. From the Sciencedirect website, 18 scientific reviews, 72 scientific articles, six encyclopedias and 32 book chapters corresponding to 11 scientific journals were analyzed. Two descriptors were proposed: 1st) of the field conditions which referred to the natural development of organisms and, 2nd) of the laboratory conditions where three types of tests were considered: A) potential of toxicity, B) of growth and, C) transformation. Although, the advantage of field conditions is the disadvantage in laboratory conditions, it is essential that bio-assessments are combined for ecosystem services to be sustainable in society. From various bioevaluations of field and laboratory conditions, data that have statistical significance and its argumentation constitute new p...
6
artículo
Publicado 2022
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In order to determine the contribution of the sociodemographic, psychosocial and health variables to a prediction model of dementia in the elderly population, a secondary analysis was carried out with the data from the “Health, Well-being and Aging. Bogotá, 2012”, with 2000 men and women over 60 years of age from urban and rural areas of Bogotá. To select the sample, a probabilistic, multistage, conglomerate and stratified sampling was carried out, based on the 2005 National Census. The SABE questionnaire adapted for Colombia was used. According to the level of measurement of each variable and the distribution of the data, univariate and bivariate analyzes were performed, with dementia as a criterion variable and sociodemographic and health variables as predictors; 30 variables were included. It was found that 40.1% of the variance of dementia is explained by age, educational ...
7
artículo
Desertion is a problem that affects public and private universities, and leads to a series of negative consequences for both institutions and students. Therefore, the objective of this study was to determine how the use of predictive models in low pass-rate courses helps to identify students at risk of desertion. Seven predictive models were designed using CRISP (Cross- Industry Standard Process for Data Mining) methodology and students’ academic records to be applied in seven low pass-rate courses. Among the main results, it can be noted that predictive models contributed to the reduction of fail rates by 25% and 40%, and that the variables that best forecast desertion were career choice (vocation), number of times students enrolled in the course, and grades obtained in mathematics or language arts when students attended the fifth year of high school.
8
artículo
Obesity is a public health problem that affects the world population, that is why the present work is oriented to present a computer solution for the estimation and prediction of obesity levels, making it possible for a person to know their current physical condition for this we used a dataset of people with obesity from different countries like Peru, Mexico and Colombia based on their eating habits and their physical condition, creating a decision tree with all these data.
9
artículo
It is a fact well documented by economic theory that high and durable inflation has a negative effect on economic growth, but that as the effects on the latter decline, they are non-linear. This work answers two research questions related to the works that have studied this empirical relationship in the last three decades. The first is about its external validity: How useful are they to predict the economic evolution of emerging countries? Simulating the growth of a sample of emerging markets for the past 20 years from these models, we found high and disparate prediction errors and therefore certain drawbacks when generalizing their conclusions. Understanding why this happens gives rise to the second question, linked to the internal validity of the models: What unresolved problems exist in the estimates carried out by the authors? the answer is that there are problems of specification,...
10
artículo
Publicado 2021
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The results of 4 predictive models, logistic regression, decision trees, KNN and a neural network are compared to predict the academic dropout of students at the National Intercultural University of the Amazon, applied to a dataset extracted from the system's database. of academic management of the university, which contains socioeconomic and academic performance data which were processed and formatted using onehotencoding techniques in order to apply the predictive models already mentioned. For data processing and formatting, Transac Sql queries were used and the application of predictive models was done through Knime Software and using Python through Google Colab. The results obtained by applying 4 predictive models are very good since they all exceeded 80% of Accuracy, which guarantees that they can be put into production for the benefit of the university and thus can make better deci...
11
artículo
Publicado 2024
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The persistent issue of student dropout negatively impacts the educational sector and society at large. This study presents a machine learning model that leverages data from the National Household Survey to predict student dropout in Peru, integrating a wide range of socio-demographic variables. The research fills a gap in existing literature by providing a model that incorporates socio-demographic variables, an area not fully explored in previous studies. The predictive model aims to identify factors associated with student dropout, aiding educational stakeholders in implementing effective interventions. The findings underscore the model's potential to enhance educational outcomes by enabling early identification of at-risk students, thereby facilitating targeted support. This work contributes to refining predictive models of university dropout rates and sug- gests the use of ensemble m...
12
tesis doctoral
Publicado 2023
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State-of-the-art control and robotics challenges have long been tackled using model-based control methods like model predictive control (MPC) and reinforcement learning (RL). These methods excel in complex dynamic domains, such as manipulation tasks, but struggle with real-world issues like wear-and-tear, uncalibrated sensors, and misspecifications. These factors often perturb system dynamics, leading to the 'reality gap' problem when robots transition from simulations to real-world environments. This work aims to bridge this gap by combining RL and control in a learning framework that adapts MPC to robot decisions, optimizing performance despite uncertainties in dynamics model parameters. This thesis presents three key contributions to robotics control. The first is a novel reward-based framework for refining stochastic Model Predictive Control (MPC). It utilizes Bayesian Optimization (...
13
artículo
Publicado 2022
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This article highlights the impact and criticism of the theoretical assumptions of prediction in the EGDE models, in addition to its scope and limits in terms of economic policy carried out by central banks. We have chosen various topics to explain predictive phenomena in social sciences and mainly in economics, based on econophysics, econometrics and macroeconometrics applied to EGDE models, but they revolve around the mind-brain problem and the “theory of cognition of predictive coding”. We conceptualize their contributions through epistemological problems and relate them to their application to EGDE models. Thus, we intend to emphasize the task of our criticism to open the field of analysis of prediction theories towards complex systems in social sciences and other epistemic debates. Therefore, the thesis of limitations in prediction is defended under the concept of the brain as a...
14
artículo
Publicado 2025
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Objective: This study analyzes how predictive models and AI algorithms influence fashion electronic trade optimization, assessing their impact on personalizing the user experience and increasing sales. Materials and methods: A quantitative approach with a non-experimental, cross-sectional, and correlational design was used, applying surveys to 50 fashion retail companies with an online presence, and to 500 consumers active on electronic trade platforms. Data were collected through surveys and databases, analyzing factors such as the implementation of artificial intelligence, the conversion rate, and the customer loyalty. For the analysis, descriptive and inferential statistics tests, including correlation and regression analysis, were used for the analysis. Results: The results evidence that AI has a significant impact on sales and customer loyalty, with a positive correlation (r = 0.87;...
15
artículo
Publicado 2020
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The models of growth and allometry of grasslands allow to know growth and development phenomena. Consequently, the aim of this study was to develop a multi-species allometric model to estimate biomass in three grasses in the High Andean Zone of Jauja, Peru, at an altitude of 3600 m above sea level. The native grasses were Festuca dolichophylla (J. Presl) tall (50-90 cm), Festuca humilior (Nees & Meyen) medium (20-35 cm) and Calamagrostis vicugnarum (Weddell) Pilger short (5- 25 cm). The measured variables were biomass (g, YB), basal diameter (cm, XD), canopy diameter (cm, XC) and height (cm, XH). The potential regression was used by choosing the strength of the models by the Akaike criterion (IAC) and the adjusted coefficient of determination (adjusted R2). The multispecies allometric model was Y = 1,238 * XD2,231, due to its lower IAC (383.795) and higher adjusted R2 (85.4%). C. vic...
16
artículo
Publicado 2020
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The models of growth and allometry of grasslands allow to know growth and development phenomena. Consequently, the aim of this study was to develop a multi-species allometric model to estimate biomass in three grasses in the High Andean Zone of Jauja, Peru, at an altitude of 3600 m above sea level. The native grasses were Festuca dolichophylla (J. Presl) tall (50-90 cm), Festuca humilior (Nees & Meyen) medium (20-35 cm) and Calamagrostis vicugnarum (Weddell) Pilger short (5- 25 cm). The measured variables were biomass (g, YB), basal diameter (cm, XD), canopy diameter (cm, XC) and height (cm, XH). The potential regression was used by choosing the strength of the models by the Akaike criterion (IAC) and the adjusted coefficient of determination (adjusted R2). The multispecies allometric model was Y = 1,238 * XD2,231, due to its lower IAC (383.795) and higher adjusted R2 (85.4%). C. vic...
17
artículo
Publicado 2022
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The objective of this work was to use the decision tree technique to define a model capable of predicting water potability. To evaluate the performance of the decision tree classification, a dataset extracted from Kaggle was used, which has 3276 water samples divided by the potability variable. Applying the Pandas and Scikit Learn libraries, a model based on a decision tree evaluated with the metrics of precision, accuracy, completeness, and F1 score was defined, achieving 0.77, 0.80, 0.85, and 0.81, respectively.
18
artículo
Publicado 2014
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Introduction: The spermatogram is used as a test of seminal quality. Recently, the sperm fragmentation test has demonstrated importance as sperm DNA integrity would affect clinical results in assisted reproduction treatments. Objectives: To determine spermatogram variables that would independently predict sperm DNA fragmentation index (SFI). Design: Retrospective, comparative study. Settings: Grupo PRANOR, Reprogenetics Latinoamerica, Clinica Concebir, Lima, Peru. Biologic material: Sperm. Methods: Individual variables and two models were compared: the first model considered percentage of sperm viability and patient’s age; the second model included percentage of motile sperms and age. Logistic regression analysis was done. Main outcome measures: Sperm viability, age. Results: Multivariate analysis showed that both models were significantly superior to individuals variables (p<0.01). Th...
19
artículo
Publicado 2014
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Introduction: The spermatogram is used as a test of seminal quality. Recently, the sperm fragmentation test has demonstrated importance as sperm DNA integrity would affect clinical results in assisted reproduction treatments. Objectives: To determine spermatogram variables that would independently predict sperm DNA fragmentation index (SFI). Design: Retrospective, comparative study. Settings: Grupo PRANOR, Reprogenetics Latinoamerica, Clinica Concebir, Lima, Peru. Biologic material: Sperm. Methods: Individual variables and two models were compared: the first model considered percentage of sperm viability and patient’s age; the second model included percentage of motile sperms and age. Logistic regression analysis was done. Main outcome measures: Sperm viability, age. Results: Multivariate analysis showed that both models were significantly superior to individuals variables (p<0.01)....
20
artículo
Publicado 2022
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Background: It is essential to identify the epidemiological and clinical characteristics of patients infected with COVID-19 associated with disease progression leading to ICU admission. The objective was to systematically review the models or scores for predicting admission to the intensive care unit (ICU) available to date for patients with COVID-19. Methods: The study is a systematic review. PubMed, Scopus, Web of Science, Ovid-Medline, and Embase were searched until July 13, 2022. We included studies that have developed and validated a model or scoring system to predict ICU admission in patients with COVID-19. The primary outcome was ICU admission. Risk of bias assessment was performed using the PROBAST tool which is based on four domains: participants, predictors, outcome and analysis. Results: Two studies were included for data extraction and critical appraisal. Predictive models of...
