scholarly journals Standardised Predictive Linear Models of Managerial Processes and the Sustainability of Graduate Programmes (SGPs) in Universities: A Case Study

2021 ◽  
Vol 2 (1) ◽  
pp. ep21006
Author(s):  
Valentine Joseph Owan ◽  
Oni Enene Offu
Keyword(s):  
Linear Models

Model predictive control of a CSTR: A hybrid modeling approach

2010 ◽  
Vol 64 (3) ◽  
Author(s):  
Michal Kvasnica ◽  
Martin Herceg ◽  
Ľuboš Čirka ◽  
Miroslav Fikar
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Models ◽  
Nonlinear Behavior ◽  
Continuous Stirred Tank Reactor ◽  
Modeling Framework ◽  
Future Evolution ◽  
Continuous Stirred Tank ◽  
Traditional Approaches

AbstractThis paper presents a case study of model predictive control (MPC) applied to a continuous stirred tank reactor (CSTR). It is proposed to approximate nonlinear behavior of a plant by several local linear models, enabling a piecewise affine (PWA) description of the model used to predict and optimize future evolution of the reactor behavior. Main advantage of the PWA model over traditional approaches based on single linearization is a significant increase of model accuracy which leads to a better control quality. It is also illustrated that, by adopting the PWA modeling framework, MPC strategy can be implemented using significantly less computational power compared to nonlinear MPC setups.

scholarly journals Using the Econometric Models for Identification of Risk Factors for Albanian Smes (Case Study: Smes of Gjirokastra Region)

2021 ◽  
Vol 18 ◽  
pp. 163-170
Author(s):  
Lorenc Koçiu ◽  
Kledian Kodra
Keyword(s):  
Logistic Regression ◽  
Statistical Models ◽  
Logistic Regression Model ◽  
Qualitative Data ◽  
Linear Models ◽  
Binary Logistic Regression ◽  
Random Variable ◽  
Econometric Models ◽  
Binary Logistic Regression Model

Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sizedEnterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in theGjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likertscale was used to measure it. Finally, the data was processed through statistical software SPSS version 21,using the binary logistic regression model, which reveals the probability of occurrence of an event when allindependent variables are included. Logistic regression is an integral part of a category of statistical models,which are called General Linear Models. Logistic regression is used to analyze problems in which one or moreindependent variables interfere, which influences the dichotomous dependent variable. In such cases, the latteris seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identifyrisks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of thepaper, we conclude that Albanian SMEs can identify risk

Integral projection models

2021 ◽  
pp. 181-196
Author(s):  
Edgar J. González ◽  
Dylan Z. Childs ◽  
Pedro F. Quintana-Ascencio ◽  
Roberto Salguero-Gómez
Keyword(s):  
Population Dynamics ◽  
Environmental Variables ◽  
Linear Models ◽  
Vital Rates ◽  
Matrix Population Models ◽  
Generalised Linear Models ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Over Time

Integral projection models (IPMs) allow projecting the behaviour of a population over time using information on the vital processes of individuals, their state, and that of the environment they inhabit. As with matrix population models (MPMs), time is treated as a discrete variable, but in IPMs, state and environmental variables are continuous and are related to the vital rates via generalised linear models. Vital rates in turn integrate into the population dynamics in a mechanistic way. This chapter provides a brief description of the logic behind IPMs and their construction, and, because they share many of the analyses developed for MPMs, it only emphasises how perturbation analyses can be performed with respect to different model elements. The chapter exemplifies the construction of a simple and a more complex IPM structure with an animal and a plant case study, respectively. Finally, inverse modelling in IPMs is presented, a method that allows population projection when some vital rates are not observed.

Practical Methods for Imputing Follower Count Dynamics

2020 ◽  
pp. 004912412092621
Author(s):  
C. Ben Gibson ◽  
Jeannette Sutton ◽  
Sarah K. Vos ◽  
Carter T. Butts
Keyword(s):  
Missing Values ◽  
Linear Models ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Application Programming Interface ◽  
System Failures ◽  
Binomial Regression ◽  
Application Programming ◽  
Programming Interface

Microblogging sites have become important data sources for studying network dynamics and information transmission. Both areas of study, however, require accurate counts of indegree, or follower counts; unfortunately, collection of complete time series on follower counts can be limited by application programming interface constraints, system failures, or temporal constraints. In addition, there is almost always a time difference between the point at which follower counts are queried and the time a user posts a tweet. Here, we consider the use of three classes of simple, easily implemented methods for follower imputation: polynomial functions, splines, and generalized linear models. We evaluate the performance of each method via a case study of accounts from 236 health organizations during the 2014 Ebola outbreak. For accurate interpolation and extrapolation, we find that negative binomial regression, modeled separately for each account, using time as an interval variable, accurately recovers missing values while retaining narrow prediction intervals.

scholarly journals Analyzing the Performances of Water User Associations to Increase the Irrigation Sustainability: An Application of Multivariate Statistics to a Case Study in Italy

2020 ◽  
Vol 12 (16) ◽  
pp. 6327
Author(s):  
Demetrio Antonio Zema ◽  
Pasquale Filianoti ◽  
Daniela D’Agostino ◽  
Antonino Labate ◽  
Manuel Esteban Lucas-Borja ◽  
...  
Keyword(s):  
Performance Indicators ◽  
Linear Models ◽  
Regional Scale ◽  
Water Price ◽  
Water User Associations ◽  
Large Variability ◽  
Water User ◽  
Economy Of Scale ◽  
Self Sufficiency

Benchmarking techniques are useful and simple tools to analyze the performance of the collective irrigation in the Water User Associations (WUAs) towards an increase in service sustainability. Several benchmarking techniques have been proposed to process and predict performance indicators. Instead, some meaningful statistical techniques based on the distance of data samples, which overcome the limitations of the traditional benchmarking techniques, have never been applied to the collective irrigation sector. This study applies Permutational Multivariate Analysis of Variance (PERMANOVA), Multidimensional Scale Models (MDS), and Distance-Based Linear Models (DISTLM) as benchmarking techniques to evaluate the technical and financial performances of 10 WUAs in Calabria (Southern Italy). These benchmarking techniques revealed that the significant differences in the irrigated areas and financial self-sufficiency of the WUAs, shown by PERMANOVA, depend on the large variability of the remaining performance indicators. Both the MDS and DISTLM demonstrated that a higher number of associated users and larger irrigation service coverage allows an increase in the irrigated areas; this enlargement is facilitated if the water price and the size of the personnel staff decrease. The WUAs’ self-sufficiency is mainly influenced by the number of workers and the maintenance, organization, and management costs, while the impacts of the due service fees and water price are more limited; it is also convenient to increase the number of the associated farmers since this increases the economy of scale and the gross revenues of the irrigation service. Overall, from the analysis carried out for the regional case study, these benchmarking techniques seem to be powerful and easy tools to identify the problems of the irrigation service and help in planning the most suitable policies to improve the sustainability of the collective irrigation at the regional scale.

scholarly journals Linear flexural natural frequencies and stability analysis of spinning Rayleigh beams: application to clamped-clamped beams.

2018 ◽  
Vol 241 ◽  
pp. 01002
Author(s):  
Mohamed Amine Aouadi ◽  
Faouzi Lakrad
Keyword(s):  
Stability Analysis ◽  
Boundary Conditions ◽  
Linear Models ◽  
Natural Frequencies ◽  
Free Vibrations ◽  
Analytical Computation ◽  
Rayleigh Beam ◽  
Clamped Beams

In the present paper 3D bending linear free vibrations of spinning Rayleigh beams are investigated. Four linear models, that differ in the linearization process, are studied. A focus on analytical computation of natural frequencies for a broad range of boundary conditions is highlighted. Then, the conditions of occurrence of divergence and flutter instabilities are determined. Finally, a case study consisting of a clamped-clamped Rayleigh beam is studied. It is found that the free vibrations destabilization process depends on the used linearization approach.

scholarly journals Analysis of rainfall variability using generalized linear models: A case study from the west of Ireland

2002 ◽  
Vol 38 (10) ◽  
pp. 10-1-10-11 ◽  
Author(s):  
Richard E. Chandler ◽  
Howard S. Wheater
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Rainfall Variability ◽  
The West ◽  
West Of Ireland

scholarly journals Environmental factors influencing the distribution of agricultural terraces: Case study of Horný Tisovník, Slovakia

2017 ◽  
Vol 25 (1) ◽  
pp. 34-45 ◽  
Author(s):  
Martina Slámová ◽  
Jana Krčmářová ◽  
Pavel Hronček ◽  
Mariana Kaštierová
Keyword(s):  
Land Use ◽  
Environmental Factors ◽  
Environmental History ◽  
Agricultural Landscape ◽  
Agricultural Land ◽  
Linear Models ◽  
Principal Component ◽  
Agricultural Terraces ◽  
Factors Influencing

Abstract The cadastral district of Horný Tisovník represents a traditionally managed Carpathian mountain agricultural landscape with extensive terraces. It was historically governed by two counties with different feudal economic systems - agricultural and industrial. This paper aims to enrich traditional methods in environmental history. We applied geospatial statistics and multivariate data analysis for the assessment of environmental factors influencing the distribution of agricultural terraces. Using linear models, the hypothesis was tested that the terrace distribution is functionally related to selected factors (affiliation to the historic counties; average altitude and slope; distance from water, buildings and settlements; units of natural potential vegetation; and current land use). Significantly greater amounts of terraces were located in the agricultural county compared to the industrial county. A principal component analysis showed the coincidence between the current agricultural land use and higher concentrations of terraces occurring in lower altitudes, closer to settlements and buildings, and within the unit of Carpathian oak-hornbeam forests. These findings regarding the most significant factors influencing the distribution of terraces are used in proposals for incentives to improve the management of the traditional agricultural landscape.

scholarly journals A comparative analysis of quantification and validation methods for prospecting the anthropogenic mine as material reserve for circular construction

2021 ◽  
Vol 2042 (1) ◽  
pp. 012169
Author(s):  
Damun Jawanrudi ◽  
Joseph McGranahan ◽  
Felix Heisel
Keyword(s):  
Comparative Analysis ◽  
Linear Models ◽  
Survey Methods ◽  
Material Resource ◽  
Data Format ◽  
Waste Production ◽  
Time Accuracy ◽  
New Generation ◽  
Continuous Material

Abstract Globally, buildings account for at least 39% of CO2 emissions and more than 50% of resource extraction and solid waste production. Therefore, any transition to carbon neutral buildings must be paired with new resource sensibilities and a shift from linear models of material consumption to continuous material use within a circular economy. Prospecting the (urban) anthropogenic mine represents an essential step towards circular construction and requires a robust methodology for data collection and interpretation. This paper presents a comparative analysis of survey methods, evaluated by parameters of time, accuracy, equipment, and labor to determine the ability of each tool in providing the necessary data to activate the existing built environment as a material resource. Chosen methods span from on-site manual and analog surveys to off-site digital technologies on a variety of case study scales. In all cases, the output’s data format (sketch book, images, mesh or point cloud outputs) can be cumbersome to process with CAD and BIM software, increasing time to results and limiting the technology’s potential, introducing the call for a new generation of survey tools specifically addressing the needs of deconstruction and salvage in circular construction.

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