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procesos predictive » procesos productivo (Expander búsqueda), procesos productivos (Expander búsqueda), process preventive (Expander búsqueda)
procesos predictive » procesos productivo (Expander búsqueda), procesos productivos (Expander búsqueda), process preventive (Expander búsqueda)
1
artículo
Publicado 2008
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The predictive control (MPC) is an advanced control strategy widely used in industrial processes. MPC is also one of the most active areas of research in the theory of control. Subjects such as optimality, stability and robustness are well known, especially for linear systems. However, despite this large adoption, both in the media industry and academics, little has been written about how these drivers are implemented in practice. This article tries to fill this gap, introducing the development of systems optimization and MPC, and discussing their integration into a hierarchical control structure. The proposed integrated control scheme is applied to the Tennessee Eastman plant, and the results show the effectiveness of the proposed strategy for optimal control of processes.
2
artículo
Publicado 2008
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The predictive control (MPC) is an advanced control strategy widely used in industrial processes. MPC is also one of the most active areas of research in the theory of control. Subjects such as optimality, stability and robustness are well known, especially for linear systems. However, despite this large adoption, both in the media industry and academics, little has been written about how these drivers are implemented in practice. This article tries to fill this gap, introducing the development of systems optimization and MPC, and discussing their integration into a hierarchical control structure. The proposed integrated control scheme is applied to the Tennessee Eastman plant, and the results show the effectiveness of the proposed strategy for optimal control of processes.
3
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.
4
artículo
Publicado 2015
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Strategic consensus in work teams is a group process related to the shared comprehension among team members of the strategies defined to attain work goals. This study aimedto verify the predictive power of strategic consensus in relation to team performance. The prediction model was constructed based on data collected from teachers and coordi-nators of 70 educational institutions in Ecuador. The individual data were aggregated per institution to obtain group level scores. The results indicate that strategic consensus predicts about 6% of the team performance as rated by the coordinator. We concluded that more studies are required to gain a better understanding of the role of strategic consensus in workteams.
5
artículo
The objective of this research work is to provide a new predictive approach to fragmentation in the rock blasting processes, developed based on the Kuz-Ram model, Multivariate Analysis techniques (MVA) and Artificial Neural Network techniques (ANN).The objective of the new approach predictive approach to (X50), fragmentation is based on the fact that this research, would provide us with an optimization in the metallurgical mining operations, because delivering an optimal fragmentation requerid for the grinding processes, it could minimize their times and maximize their productivity.
6
artículo
The objective of the study was to determine the predictive value of personality traits according to the Mexican model of the Five Personality Factors in the Burnout Syndrome (BOS) and its dimensions from the Gil-Monte model. Three hundred and seventy-five basic education teachers from Mexico City took part in it. The sampling was intentional, non-probabilistic with cross-sectional and correlational design. The Spanish Burnout Syndrome inventory and the Mexican Five Personality Factors scale were used. Pearson's Correlation Test and a stepwise linear regression model were employed for the analysis. With the exception of Emotional Control and Enthusiasm towards work (r2=.087; p>0.05), the results found significant correlations of the Five Mexican personality factors and BOS, negative in the case of personality traits and Psychic Burnout, Indolence, and Guilt; and positive among personal...
7
artículo
Publicado 2023
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Early mathematical competencies have a great impact on academic performance and on the development of more complex mathematical skills, especially in early education. Several authors have highlighted the importance of working memory and inhibition in the development of these mathematical skills; however, there is no agreement regarding the explanatory capacity of these executive domains with respect to differentiated performance in mathematics. The aim of this research was to evaluate the predictive capacity of verbal and visuospatial working memory and of behavioral and cognitive inhibition in mathematical competencies of relational logic and numerical type in 106 Chilean children of early education between 4 and 6 years old, who were evaluated with four executive tasks and an early mathematical assessment test. For data analysis, correlations and multiple linear regressions were perfor...
8
tesis de maestría
Publicado 2025
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Este trabajo aborda el problema de las interrupciones en el funcionamiento de antenas de telecomunicaciones en Perú, situación que impacta negativamente en lo económico y la calidad de servicio hacia los usuarios. Estas interrupciones, impactan en un promedio mensual de inactividad que se traduce en pérdidas estimadas de 28,000 gigabytes de datos y, 170,000 minutos de voz. El objetivo de la investigación es predecir fallos y optimizar el mantenimiento predictivo de las antenas para mitigar tiempos de inactividad por medio de la búsqueda del mejor modelo de clasificación. El estudio se centró en los problemas de software de antenas terrestres con tecnología 4G operadas por un proveedor, debido a su significativa participación en el mercado y consistencia de datos. Para abordar esta situación, se evaluaron clasificadores tales como Random Forest, Gradient Boosting, Bagging Decis...
9
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 (...
10
artículo
Publicado 2019
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Cervical cancer is currently the fourth most frequent type of cancer in women. A large number of techniques from the Artificial Intelligence (AI) such as Neuronal Networks, Support Vector Machines (SVM), Decision Trees and others; have been used to deal with the problem of predicting this disease. The following paper shows the cervical cancer risk prediction, by implementing a probabilistic model based on Bayesian Networks and using 322 instances where we could retrieve 15 different features that are known information from each patient. The tests were made using the 40% of the whole dataset, confusion matrix and AUC indicator. The results show that this work has raised a 96% of success rate as well as 0.9864 in terms of the AUC indicator, in addition to this, the results suggest that Bayesian Networks are able to reach a high performance and provide transparency during the inference proc...
11
tesis de grado
Publicado 2025
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La presente tesis propone la implementación del algoritmo Practical Non-linear Model Predictive Control (PNMPC) para controlar el lazo de nivel del Módulo de laboratorio FESTO, el cual se compone de un sistema de dos tanques en cascada conectados por un circuito cerrado donde fluye agua. El PNMPC es un algoritmo de control que soluciona el problema de la no linealidad de los sistemas de nivel sin comprometer el rendimiento del proceso control. Para llevar a efecto esta estrategia de control se ha escrito un código en MATLAB que envía y recibe datos de la planta mediante la arquitectura de comunicación OPC UA a un PLC, que se encarga de operar los componentes del Módulo FESTO. También, se aplicó técnicas de control, usualmente, vistas en los cursos de automatización tales como el controlador PI y el controlador Generalize Predictive Control (GPC) para comparar su rendimiento con...
12
artículo
Publicado 2024
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Gentrification is an urban phenomenon that displaces the original inhabitants of a neighborhood due to regeneration processes. In this analysis carried out in the historic center of the heritage city of Cuenca, the beginning of the process does not necessarily respond to a significant transformation of the architecture. It has been proven that the phenomenon arises invisibly due to changes in the demographic composition of the neighborhood. The methodology of this research requires the correlation of census data for each minimum applicable unit known as a block. This information is contrasted with historical photographs available on the Google platform. The significant contribution to the concept of gentrification results in a method that allows identifying and predicting the phenomenon, more important than its visual-late diagnosis.
13
artículo
Publicado 2022
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Solid waste management is one of the main environmental challenges in cities around the world due to factors such as population growth and consumption habits. One of the main tools for the design of waste management projects is the estimation of per capita generation, however, the traditional method to obtain this information demands a lot of effort and time, therefore this research proposes an alternative approach to estimate per capita generation based on socioeconomic factors. For this purpose, socioeconomic demographic information and information on the per capita generation of solid waste of 50 families was collected, subsequently the variables that have significant influence were determined from the correlation coefficient ρ of Spearman for numerical variables and an ANOVA for categorical variables with an acceptance threshold of 0.4 and 0.05 respectively. The selected variables w...
14
tesis doctoral
Publicado 2020
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Descargue el texto completo en el repositorio institucional de la Universidade Estadual de Campinas: https://hdl.handle.net/20.500.12733/1641647
15
artículo
Publicado 2016
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Teachers´ engagement in change processes is closely related to their attitudes and views on education. Therefore, any successful educational change demands that teachers reevaluate their profession, as personal and professional factors are clearly relevant. The goal of this study is to test a predictive statistical model of teacher´s engagement in educational change considering personality factors and self-evaluation. The random and representative sample of Peruvian teachers comprised of 888 subjects. Results show good model fit and a strong predictive power on educational changes. The study confirms that personality and selfconcept are strong predictors on teacher´s engagement with educational change.
16
artículo
Publicado 2016
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Teachers´ engagement in change processes is closely related to their attitudes and views on education. Therefore, any successful educational change demands that teachers reevaluate their profession, as personal and professional factors are clearly relevant. The goal of this study is to test a predictive statistical model of teacher´s engagement in educational change considering personality factors and self-evaluation. The random and representative sample of Peruvian teachers comprised of 888 subjects. Results show good model fit and a strong predictive power on educational changes. The study confirms that personality and selfconcept are strong predictors on teacher´s engagement with educational change.
17
artículo
Publicado 2019
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Internal fraud is a big problem for companies since it causes significant monetary losses. Several research studies have proposed to improve the personnel selection process using data mining. The present work suggests to use applicants’ historical information in order to predict if they will commit fraud during their working period in a company. There are models with high precision level but with a higher error rate to find fraud. After several experimentations, around seven variables which contribute more to the model were found. Some of these variables match those mentioned in studies about antisocial personality disorder. The algorithm with best results was a convolutional neural network with 80% accuracy rate. It is concluded that applicants’ information is important to establish if they will commit internal fraud during their working period in a company.
18
artículo
Publicado 2019
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Internal fraud is a big problem for companies since it causes significant monetary losses. Several research studies have proposed to improve the personnel selection process using data mining. The present work suggests to use applicants’ historical information in order to predict if they will commit fraud during their working period in a company. There are models with high precision level but with a higher error rate to find fraud. After several experimentations, around seven variables which contribute more to the model were found. Some of these variables match those mentioned in studies about antisocial personality disorder. The algorithm with best results was a convolutional neural network with 80% accuracy rate. It is concluded that applicants’ information is important to establish if they will commit internal fraud during their working period in a company.
19
artículo
Publicado 2021
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Predicting the academic results of students allows the teacher to seek techniques and strategies at the indicated time during the teaching and learning process in order to improve the achievement of skills in their students. In this research, an artificial neural network (ANN) was implemented to predict the academic results of the physics course of the students of the II cycle of the Civil Engineering career of the National Intercultural University Fabiola Salazar Leguía de Bagua-Peru based on data historical. The RNA was designed and implemented in the MATLAB Software, its architecture is made up of an input layer, a hidden layer and an output layer, for the RNA training two algorithms that the MATLAB Toolbox has: the Scaled Conjugate Gradient achieving a prediction percentage of 70% and the Levenberg-Marquardt achieving a prediction percentage of 86%.
20
artículo
Publicado 2021
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Predicting the academic results of students allows the teacher to seek techniques and strategies at the indicated time during the teaching and learning process in order to improve the achievement of skills in their students. In this research, an artificial neural network (ANN) was implemented to predict the academic results of the physics course of the students of the II cycle of the Civil Engineering career of the National Intercultural University Fabiola Salazar Leguía de Bagua-Peru based on data historical. The RNA was designed and implemented in the MATLAB Software, its architecture is made up of an input layer, a hidden layer and an output layer, for the RNA training two algorithms that the MATLAB Toolbox has: the Scaled Conjugate Gradient achieving a prediction percentage of 70% and the Levenberg-Marquardt achieving a prediction percentage of 86%.
