Relevant bibliographies by topics / CHARN models

Academic literature on the topic 'CHARN models'

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Published: 8 June 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "CHARN models":

1

Kanai, Hiroomi, Hiroaki Ogata, and Masanobu Taniguchi. "Estimating function approach for CHARN Models." METRON 68, no. 1 (April 2010): 1–21. http://dx.doi.org/10.1007/bf03263521.

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Amano, Tomoyuki. "Asymptotic Optimality of Estimating Function Estimator for CHARN Model." Advances in Decision Sciences 2012 (July 3, 2012): 1–11. http://dx.doi.org/10.1155/2012/515494.

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CHARN model is a famous and important model in the finance, which includes many financial time series models and can be assumed as the return processes of assets. One of the most fundamental estimators for financial time series models is the conditional least squares (CL) estimator. However, recently, it was shown that the optimal estimating function estimator (G estimator) is better than CL estimator for some time series models in the sense of efficiency. In this paper, we examine efficiencies of CL and G estimators for CHARN model and derive the condition that G estimator is asymptotically optimal.
3

Ngatchou-Wandji, Joseph, Marwa Ltaifa, Didier Alain Njamen Njomen, and Jia Shen. "Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models." Mathematics 10, no. 4 (February 17, 2022): 624. http://dx.doi.org/10.3390/math10040624.

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This work is concerned with multivariate conditional heteroscedastic autoregressive nonlinear (CHARN) models with an unknown conditional mean function, conditional variance matrix function and density function of the distribution of noise. We study the kernel estimator of the latter function when the former are either parametric or nonparametric. The consistency, bias and asymptotic normality of the estimator are investigated. Confidence bound curves are given. A simulation experiment is performed to evaluate the performance of the results.
4

Arrouch, Mohamed Salah Eddine, Echarif Elharfaoui, and Joseph Ngatchou-Wandji. "Change-Point Detection in the Volatility of Conditional Heteroscedastic Autoregressive Nonlinear Models." Mathematics 11, no. 18 (September 21, 2023): 4018. http://dx.doi.org/10.3390/math11184018.

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This paper studies single change-point detection in the volatility of a class of parametric conditional heteroscedastic autoregressive nonlinear (CHARN) models. The conditional least-squares (CLS) estimators of the parameters are defined and are proved to be consistent. A Kolmogorov–Smirnov type-test for change-point detection is constructed and its null distribution is provided. An estimator of the change-point location is defined. Its consistency and its limiting distribution are studied in detail. A simulation experiment is carried out to assess the performance of the results, which are compared to recent results and applied to two sets of real data.
5

Chananet, C., S. Sukparungsee, and Y. Areepong. "The ARL of EWMA Chart for Monitoring ZINB Model Using Markov Chain Approach." International Journal of Applied Physics and Mathematics 4, no. 4 (2014): 236–39. http://dx.doi.org/10.7763/ijapm.2014.v4.290.

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Antonowicz, Mirosław. "Innovative Models of Supply Chain Management." Journal of Management and Business Administration. Central Europe 26, no. 2 (June 15, 2018): 2–15. http://dx.doi.org/10.7206/jmba.ce.2450-7814.225.

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Pupo, Amaury, David Baez-Nieto, Agustín Martínez, Ramón Latorre, and Carlos González. "Proton channel models." Channels 8, no. 3 (April 22, 2014): 180–92. http://dx.doi.org/10.4161/chan.28665.

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Milac, Adina, Andriy Anishkin, Sarosh N. Fatakia, Carson C. Chow, Sergei Sukharev, and H. Robert Guy. "Structural models of TREK channels and their gating mechanism." Channels 5, no. 1 (January 2011): 23–33. http://dx.doi.org/10.4161/chan.5.1.13905.

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Korobko, M. M. "Discrete model of chain conveyor movement dynamics." Naukovij žurnal «Tehnìka ta energetika» 11, no. 4 (September 10, 2020): 89–94. http://dx.doi.org/10.31548/machenergy2020.04.089.

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Improving the reliability of structures of transport mechanisms and other elements, reducing metal content, improving performance, expanding functionality and technical capabilities is a priority area of work to improve existing and develop new machines for beet growing. The dynamic model of the chain conveyor which considers the basic movement and fluctuations of elements of the drive and a working cloth is developed in work. The model is represented by a system of discrete masses with eight degrees of freedom. The operation of chain conveyors is characterized by the presence of dynamic forces arising from the pulsating movement of the chain at a steady rotation of the drive sprocket. At the start-up site, dynamic forces from increasing the speed from zero to a certain constant value are added to these forces. Under such conditions, significant alternating dynamic loads can occur in the chain, which as a result of the accumulation of fatigue phenomena can lead to its premature destruction.
10

Irfan Sabir, Raja, and Muhammad Irfan. "Levels and Barriers to Supply Chain Integration: A conceptual model of Supply Chain Performance." International Journal of Management Science and Business Administration 1, no. 1 (2014): 52–59. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.11.1005.

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In modern business scenario Supply chain has become the back bone for every business organization. All supply chain partners are joined together in value delivery network of company that no one can perform better without support of other. The ultimate objective of this cohesive relationship is to deliver value to customers and gets desired state of customer satisfaction & loyalty for the organization. For this purpose it is necessary to integrate the internal and external partners of Supply chain at different levels. The Purpose of the paper is to investigate the impact of supply chain integration on supply chain performance. The construct of Supply chain integration has been divided into three derivers that are information integration, coordination resource sharing and organizational relationship linkage. There are certain barriers to integration found in each industry that have moderating effects on the relationship b/w integration and organization performance.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "CHARN models":

1

Salman, Youssef. "Testing a class of time-varying coefficients CHARN models with application to change-point study." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0170.

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Dans cette thèse, nous étudions un test du rapport de vraisemblance pour détecter les ruptures faibles dans la moyenne conditionnelle d'une classe de modèles CHARN à coefficients dépendants du temps. Nous établissons la structure de normalité asymptotique locale (LAN) de la famille de vraisemblances étudiées. Nous montrons l'optimalité asymptotique du test et donnons une expression explicite de sa puissance locale en fonction des potentiels points de rupture et des amplitudes des ruptures. Nous décrivons des stratégies de détection des ruptures et d'estimation de leurs localisations. Les estimateurs sont obtenus comme indices de temps rendant maximal un estimateur de la puissance locale. Les simulations numériques que nous faisons montrent de bonnes performances de notre méthode sur les exemples considérés
In this thesis, we study a likelihood ratio test for detecting multiple weak changes in the conditional mean of a class of time-dependent coefficients CHARN models.We establish the locally asymptotically normality (LAN) structure of the family of likelihoods under study. We prove that the test is asymptotically optimal, and we give an explicit form of its asymptotic local power as a function of candidates change locations and changes magnitudes. We describe some strategies for weak change-points detection and their location estimates. The estimates are obtained as the time indices maximizing an estimate of the local power. The simulation study we conduct shows the good performance of our methods on the examples considered
2

Modarres-Mousavi, Shabnam. "Monitoring Markov Dependent Binary Observations with a Log-Likelihood Ratio Based CUSUM Control Chart." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/26235.

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Our objective is to monitor the changes in a proportion with correlated binary observations. All of the published work on this subject used the first-order Markov chain model for the data. Increasing the order of dependence above one by extending a standard Markov chain model entails an exponential increase of both the number of parameters and the dimension of the transition probability matrix. In this dissertation, we develop a particular Markov chain structure, the Multilevel Model (MLM), to model the correlation between binary data. The basic idea is to assign a lower probability to observing a 1 when all previous correlated observations are 0â s, and a higher probability to observing a 1 as the last observed 1 gets closer to the current observation. We refer to each of the distinct situations of observing a 1 as a â levelâ . For a given order of dependence, , at most different values of conditional probabilities of observing a 1 can be assigned. So the number of levels is always less than or equal to . Compared to a direct extension of the first-order Markov model to higher orders, our model is considerably parsimonious. The number of parameters for the MLM is only one plus the number of levels, and the transition probability matrix is . We construct a CUSUM control chart for monitoring a proportion with correlated binary observations. First, we use the probability structure of a first-order Markov chain to derive a log-likelihood ratio based CUSUM control statistic. Then, we model this CUSUM statistic itself as a Markov chain, which in turn allows for designing a control chart with specified statistical properties: the Markov Binary CUSUM (MBCUSUM) chart. We generalize the MBCUSUM to account for any order of dependence between binary observations through implying MLM to the data and to our CUSUM control statistic. We verify that the MBCUSUM has a better performance than a curtailed Shewhart chart. Also, we show that except for extremely large changes in the proportion (of interest) the MBCUSUM control chart detects the changes faster than the Bernoulli CUSUM control chart, which is designed for independent observations.
Ph. D.
3

Frühwirth-Schnatter, Sylvia. "Bayesian Model Discrimination and Bayes Factors for Normal Linear State Space Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1993. http://epub.wu.ac.at/108/1/document.pdf.

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It is suggested to discriminate between different state space models for a given time series by means of a Bayesian approach which chooses the model that minimizes the expected loss. Practical implementation of this procedures requires a fully Bayesian analysis for both the state vector and the unknown hyperparameters which is carried out by Markov chain Monte Carlo methods. Application to some non-standard situations such as testing hypotheses on the boundary of the parameter space, discriminating non-nested models and discrimination of more than two models is discussed in detail. (author's abstract)
Series: Forschungsberichte / Institut für Statistik
4

Fayez, Mohamed. "AN AUTOMATED METHODOLOGY FOR A COMPREHENSIVE DEFINITION OF THE SUPPLY CHAIN USING GENERIC ONTOLOGICAL COMPONENTS." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2509.

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Today, worldwide business communities are in the era of the Supply Chains. A Supply Chain is a collection of several independent enterprises that partner together to achieve specific goals. These enterprises may plan, source, produce, deliver, or transport materials to satisfy an immediate or projected market demand, and may provide the after sales support, warranty services, and returns. Each enterprise in the Supply Chain has roles and elements. The roles include supplier, customer, or carrier and the elements include functional units, processes, information, information resources, materials, objects, decisions, practices, and performance measures. Each enterprise, individually, manages these elements in addition to their flows, their interdependencies, and their complex interactions. Since a Supply Chain brings several enterprises together to complement each other to achieve a unified goal, the elements in each enterprise have to complement each other and have to be managed together as one unit to achieve the unified goal efficiently. Moreover, since there are a large number of elements to be defined and managed in a single enterprise, then the number of elements to be defined and managed when considering the whole Supply Chain is massive. The supply chain community is using the Supply Chain Operations Reference model (SCOR model) to define their supply chains. However, the SCOR model methodology is limited in defining the supply chain. The SCOR model defines the supply chain in terms of processes, performance metrics, and best practices. In fact, the supply chain community, SCOR users in particular, exerts massive effort to render an adequate supply chain definition that includes the other elements besides the elements covered in the SCOR model. Also, the SCOR model is delivered to the user in a document, which puts a tremendous burden on the user to use the model and makes it difficult to share the definition within the enterprise or across the supply chain. This research is directed towards overcoming the limitations and shortcomings of the current supply chain definition methodology. This research proposes a methodology and a tool that will enable an automated and comprehensive definition of the Supply Chain at any level of details. The proposed comprehensive definition methodology captures all the constituent parts of the Supply Chain at four different levels which are, the supply chain level, the enterprise level, the elements level, and the interaction level. At the Supply Chain level, the various enterprises that constitute the supply chain are defined. At the enterprise level, the enterprise elements are identified. At the enterprises' elements level, each element in the enterprise is explicitly defined. At the interaction level, the flows, interdependence, and interactions that exist between and within the other three levels are identified and defined. The methodology utilized several modeling techniques to generate generic explicit views and models that represents the four levels. The developed views and models were transformed to a series of questions and answers, where the questions correspond to what a view provides and the answers are the knowledge captured and generated from the view. The questions and answers were integrated to render a generic multi-view of the supply chain. The methodology and the multi-view were implemented in an ontology-based tool. The ontology includes sets of generic supply chain ontological components that represent the supply chain elements and a set of automated procedures that can be utilized to define a specific supply chain. A specific supply chain can be defined by re-using the generic components and customizing them to the supply chain specifics. The ontology-based tool was developed to function in the supply chain dynamic, information intensive, geographically dispersed, and heterogeneous environment. To that end, the tool was developed to be generic, sharable, automated, customizable, extensible, and scalable.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering and Management Systems
5

Hao, Yan. "Automated Reductions of Markov Chain Models of Calcium Release Site Models." W&M ScholarWorks, 2012. https://scholarworks.wm.edu/etd/1539623353.

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Markov chain models have played an important role in understanding the relationship between single channel gating of intracellular calcium (Ca2+) channels, specifically 1,4,5-trisphosphate receptors (IP3Rs) and ryanodine receptors (RyRs), and the stochastic dynamics of Ca2+ release events, known as Ca2+ puffs and sparks. Mechanistic Ca2+ release site models are defined by the composition of single channel models whose transition probabilities depend on the local calcium concentration and thus the state of the other channels. Unfortunately, the large state space of such compositional models impedes simulation and computational analysis of the whole cell Ca2+ signaling in which the stochastic dynamics of localized Ca2+ release events play an important role. This dissertation introduces, implements and validates the application of several automated model reduction techniques that significantly reduce the computational cost of mechanistic compositionally defined Ca2+ release site models.;A common feature of Ca2+ channel models is the separation of time scales. For example, the well-known bell-shaped equilibrium open probability of IP3Rs can be reproduced by Markov Chain models that include transitions mediated by fast Ca2+ activation and slower Ca2+ inactivation. Chapter 2 introduces an automated model reduction technique that is based on fast/slow analysis that leverages these time scale differences. Rate constants in the single channel model are categorized as either fast or slow, groups of release site states that are connected by fast transitions are identified and lumped, and transition rates between reduced states are chosen consistent with the conditional probability distributions among states within each group. The fast/slow reduction approach is validated by the fact that puff/spark statistics can be efficiently computed from reduced Ca2+ release site models with small and transient error.;For Markov chain Ca2+ release site models without time-scale separation, the manner in which the full model states should be aggregated for optimal reduction is difficult to determine a priori. In Chapter 3, a genetic algorithm based approach that mimics the inheritance, mutation and selection processes of natural evolution is implemented to reduce these models. Given a full model of interest and target reduced model size, this genetic algorithm searches for set partitions, each corresponding to a potential scheme for state aggregation, that lead to reduced models that well-approximate the full model. A whole cell model with coupled local and global Ca2+ signaling is simplified by replacing a compositionally defined full Ca2+ release site model with a reduced model obtained through the genetic algorithm.;In Chapter 4, a Langevin formulation of Ca2+ release sites is introduced as an alternative model reduction technique that is applicable when the number of channels per Ca2+ release site is too large for the previously discussed reduction methods, but not so large that the stochasticity of Ca2+ release is negligible. The Langevin formulation for coupled intracellular Ca2+ channels results in stochastic differntial equations that well-approximate the corresponding Markov chain models when release sites possess as few as 20 channels, and the agreement improves as the number of channels per release site increases. Importantly, the computational time required by the Langevin approach does not increase with the size of Ca2+ release site.
6

Miazhynskaia, Tatiana, Sylvia Frühwirth-Schnatter, and Georg Dorffner. "A comparison of Bayesian model selection based on MCMC with an application to GARCH-type models." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2003. http://epub.wu.ac.at/586/1/document.pdf.

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This paper presents a comprehensive review and comparison of five computational methods for Bayesian model selection, based on MCMC simulations from posterior model parameter distributions. We apply these methods to a well-known and important class of models in financial time series analysis, namely GARCH and GARCH-t models for conditional return distributions (assuming normal and t-distributions). We compare their performance vis--vis the more common maximum likelihood-based model selection on both simulated and real market data. All five MCMC methods proved feasible in both cases, although differing in their computational demands. Results on simulated data show that for large degrees of freedom (where the t-distribution becomes more similar to a normal one), Bayesian model selection results in better decisions in favour of the true model than maximum likelihood. Results on market data show the feasibility of all model selection methods, mainly because the distributions appear to be decisively non-Gaussian.
Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
7

Ahlin, Mikael, and Felix Ranby. "Predicting Marketing Churn Using Machine Learning Models." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-161408.

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For any organisation that engages in marketing actions there is a need to understand how people react to communication messages that are sent. Since the introduction of General Data Protection Regulation, the requirements for personal data usage have increased and people are able to effect the way their personal information is used by companies. For instance people have the possibility to unsubscribe from communication that is sent, this is called Opt-Out and can be viewed as churning from communication channels. When a customer Opt-Out the organisation loses the opportunity to send personalised marketing to that individual which in turn result in lost revenue.  The aim with this thesis is to investigate the Opt-Out phenomena and build a model that is able to predict the risk of losing a customer from the communication channels. The risk of losing a customer is measured as the estimated probability that a specic individual will Opt-Out in the near future. To predict future Opt-Outs the project uses machine learning algorithms on aggregated communication and customer data. Of the algorithms that were tested the best and most stable performance was achieved by an Extreme Gradient Boosting algorithm that used simulated variables. The performance of the model is best described by an AUC score of 0.71 and a lift score of 2.21, with an adjusted threshold on data two months into the future from when the model was trained. With a model that uses simulated variables the computational cost goes up. However, the increase in performance is signicant and it can be concluded that the choice to include information about specic communications is considered relevant for the outcome of the predictions. A boosted method such as the Extreme Gradient Boosting algorithm generates stable results which lead to a longer time between model retraining sessions.
8

Yang, GuoLu. "Modèle de transport complet en rivière avec granulométrie étendue." Grenoble 1, 1989. http://www.theses.fr/1989GRE10011.

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Les variations des lignes d'eau et du lit des rivieres alluvionnaires dans le cas du transport complet (charriage+suspension) des sediments en granulometrie etendue sont etudiees par un modele mathematique uni-dimensionnel. Dans ce modele le charriage et la suspension sont consideres comme deux phenomenes du transport en tenant compte d'un terme source-puits qui represente l'echange entre eux. Le terme source-puits est formule par un modele d'echanges stochastiques considerant trois etats: suspension, charriage et immobilite, les probabilites des etats sont obtenues par le processus de chaine de markov. Le modele conceptuel d'une "couche melangee" est introduit pour reproduire les phenomenes de pavage et de triage. Le systeme d'equations a resoudre est analyse par la methode des caracteristiques. Une solution numerique decouplee du systeme est presentee. Un nouvel algorithme, assurant le calcul couple du transport par convection-diffusion-reaction, est developpe. Des tests du modele mathematique sont systematiquement effectues afin d'examiner la sensibilite et montrer la precision du modele
9

Trávníček, Jan. "Tvorba spolehlivostních modelů pro pokročilé číslicové systémy." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236226.

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This thesis deals with the systems reliability. At First, there is discussed the concept of reliability itself and its indicators, which can specifically express reliability. The second chapter describes the different kinds of reliability models for simple and complex systems. It further describes the basic methods for construction of reliability models. The fourth chapter is devoted to a very important Markov models. Markov models are very powerful and complex model for calculating the reliability of advanced systems. Their suitability is explained here for recovered systems, which may contain absorption states. The next chapter describes the standby redundancy. Discusses the advantages and disadvantages of static, dynamic and hybrid standby. There is described the influence of different load levels on the service life. The sixth chapter is devoted to the implementation, description of the application and description of the input file in XML format. There are discussed the results obtaining in experimental calculations.
10

Wu, Claudia. "Total supply chain cost model." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34869.

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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.
Includes bibliographical references (leaves 72-73).
Sourcing and outsourcing decisions have taken on increased importance within Teradyne to improve efficiency and competitiveness. This project delivered a conceptual framework and a software tool to analyze supply chain costs associated with a specified supply chain design. Determining total supply chain cost is a complex challenge. This work developed the concept of a hierarchical, inter-related, multi-level supply chain cost architecture. Within this architecture, supply chain costs can be expressed as a sum of only 5 supply chain cost factors (material, labor, logistics, inventory holding, and overhead costs). The reduction of a large number of potential cost factors eases communication about total supply chain costs within an organization. An interactive Excel VBA software was developed which allows the user to experimentally model changes to a specific supply chain design. The VBA program automatically recalculates the supply chain costs based on the changes made. The output of the program is a comparison of costs associated with different supply chain designs. In a case study, the total supply chain cost model was applied to evaluate different supply chain node locations in Southeast Asia for one of Teradyne's testers.
by Claudia Wu.
S.M.
M.B.A.
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Books on the topic "CHARN models":

1

Tayur, Sridhar, Ram Ganeshan, and Michael Magazine, eds. Quantitative Models for Supply Chain Management. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4949-9.

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Estampe, Dominique. Supply Chain Performance and Evaluation Models. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119005421.

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Ramanathan, Usha, and Ramakrishnan Ramanathan, eds. Supply Chain Strategies, Issues and Models. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5352-8.

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Poswal, Muhammad S. Evaluation of supply chain improvement models. Manchester: UMIST, 1997.

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Sridhar, Tayur, Ganeshan Ram, and Magazine Michael, eds. Quantitative models for supply chain management. Boston: Kluwer Academic Publishers, 1999.

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Tayur, Sridhar, Ram Ganeshan, and Michael Magazine. Quantitative models for supply chain management. New York: Springer Science, 1999.

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Banisch, Sven. Markov Chain Aggregation for Agent-Based Models. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24877-6.

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Poirier, Charles C. Using models to improve the supply chain. Boca Raton, Fla: St. Lucie Press, 2004.

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Geunes, Joseph, Panos M. Pardalos, and H. Edwin Romeijn, eds. Supply Chain Management: Models, Applications, and Research Directions. Boston: Kluwer Academic Publishers, 2005. http://dx.doi.org/10.1007/b106640.

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Brandenburg, Marcus. Quantitative Models for Value-Based Supply Chain Management. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31304-2.

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Book chapters on the topic "CHARN models":

1

Goetschalckx, Marc. "Supply Chain Models." In Supply Chain Engineering, 521–613. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-6512-7_12.

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Barga, Roger, Valentine Fontama, and Wee Hyong Tok. "Building Churn Models." In Predictive Analytics with Microsoft Azure Machine Learning, 189–206. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1200-4_9.

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Fadell, Edward R., and Sufian Y. Husseini. "Cellular Chain Models." In Springer Monographs in Mathematics, 153–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56446-8_9.

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Barga, Roger, Valentine Fontama, and Wee Hyong Tok. "Building Churn Models." In Predictive Analytics with Microsoft Azure Machine Learning, 107–27. Berkeley, CA: Apress, 2014. http://dx.doi.org/10.1007/978-1-4842-0445-0_6.

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Rodrigues, Eliane Regina, and Jorge Alberto Achcar. "Markov Chain Models." In Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies, 11–23. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4645-3_2.

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Møller, Jan Kloppenborg, Marcel Schweiker, Rune Korsholm Andersen, Burak Gunay, Selin Yilmaz, Verena Marie Barthelmes, and Henrik Madsen. "Markov chain models." In Statistical Modelling of Occupant Behaviour, 253–88. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003340812-9.

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Goetschalckx, Marc. "Advanced Supply Chain Models." In Supply Chain Engineering, 615–70. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-6512-7_13.

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Framinan, Jose M. "Enriching SC Models." In Modelling Supply Chain Dynamics, 123–49. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79189-6_6.

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Ravindran, A. Ravi, Donald P. Warsing, and Paul M. Griffin. "Inventory Management Methods and Models." In Supply Chain Engineering, 91–162. 2nd ed. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003283393-3.

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Cordell, Andrea, and Ian Thompson. "Porter’s Value Chain." In The Procurement Models Handbook, 165–67. Third edition. | Abingdon, Oxon ; New York, NY : Routledge, 2019. | Earlier editions published as: Purchasing models handbook: a guide to the most popular business models used in purchasing / Andrea Reynolds and Ian Thompson.: Routledge, 2019. http://dx.doi.org/10.4324/9781351239509-50.

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Conference papers on the topic "CHARN models":

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Barriga, Angela, Davide Di Ruscio, Ludovico Iovino, Phuong T. Nguyen, and Alfonso Pierantonio. "An extensible tool-chain for analyzing datasets of metamodels." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3419626.

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M, Janjevic, Nsamzinshuti A, Rigo N, and Ndiaye AB. "APPLYING THE SUPPLY CHAIN OPERATIONS REFERENCE (SCOR) MODEL FOR THE EVALUATION OF SEVERAL URBAN CONSOLIDATION CENTRE OPERATING MODELS." In World Conference on Supply Chain Management. TIIKM, 2017. http://dx.doi.org/10.17501/wcosm.2017.2107.

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Bilic, Damir, Etienne Brosse, Andrey Sadovykh, Dragos Truscan, Hugo Bruneliere, and Uwe Ryssel. "An Integrated Model-Based Tool Chain for Managing Variability in Complex System Design." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2019. http://dx.doi.org/10.1109/models-c.2019.00045.

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Naranjo-Guevara, Natalia, Jean Louis Steevenz, and Sonja Floto-Stammen. "A sustainable business model for Black Soldier Fly production in the feed supply chain: Exploring business models for a farming transition with Black Soldier Fly." In New Business Models 2023. Maastricht University Press, 2023. http://dx.doi.org/10.26481/mup.2302.44.

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Abstract:
To propose sustainable opportunities to traditional farmers in the Netherlands to face challenges such as increasing CO2 emissions, nitrogen deposition, and rising prices in production, this study investigated a sustainable business model for Black Soldier Fly production in the feed supply chain. First, the value chain and stakeholders in the emerging BSF farming industry were identified. Information collected through secondary research was then analyzed through the Triple Layered Business Model Canvas tool. The proposed model could be applied by traditional farmers in order to innovate in the transition to more sustainable protein production. To reach such sustainability engagement with all stakeholders can help strengthen the value propositions, in a multi-stakeholder value model. Finally, the risks and opportunities of the proposed BSF-production business model are discussed.
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Nyffenegger, Roger, Stefan Grösser, and Nancy Bocken. "Diffusion of Circular Photovoltaic Product-Service Systems among Large Solar Applications: A Supply and Demand Analysis." In New Business Models 2023. Maastricht University Press, 2023. http://dx.doi.org/10.26481/mup.2302.24.

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This research paper analyzes the value proposition, creation, and capture of circular solar photovoltaic (PV) business models in Switzerland, with a focus on product-service system (PSS)-related PV business models. The paper identifies three areas of circular solar PV business models within the midstream value chain: application-related, position-related, and interaction-related. The paper also discusses the benefits and drawbacks of PSS business models in demand-side focus groups and presents possible solutions on which the supply side can focus. The research aims to contribute to the adoption of PSS-related solar PV business models by business-to-business (B2B) and business-to-government (B2G) customers.
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Magalhaes, Patricia, Rafael Tourinho Aoude, Alberto Corrêa dos Reis, and Manoel Roberto Robilotta. "Multi-Meson Model applied to $D^+ \to K^+ K^- K^+$." In VIII International Workshop On Charm Physics. Trieste, Italy: Sissa Medialab, 2017. http://dx.doi.org/10.22323/1.289.0086.

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De Yta Hernández, Alejandro, Eduard De La Cruz Burelo, and Michel Hernández Villanueva. "Beyond the Standard Model invisible particle searches in tau lepton decays." In 10th International Workshop on Charm Physics. Trieste, Italy: Sissa Medialab, 2021. http://dx.doi.org/10.22323/1.385.0036.

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Robson, Michael P., Ronak Buch, and Laxmikant V. Kale. "Runtime Coordinated Heterogeneous Tasks in Charm++." In 2016 Second International Workshop on Extreme Scale Programming Models and Middleware (ESPM2). IEEE, 2016. http://dx.doi.org/10.1109/espm2.2016.011.

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Sommer, Stefan, Aditya Tatu, Chen Chen, Dan R. Jurgensen, Marleen de Bruijne, Marco Loog, Mads Nielsen, and Francois Lauze. "Bicycle chain shape models." In 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2009. http://dx.doi.org/10.1109/cvprw.2009.5204053.

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Sommer, S., A. Tatu, Chen Chen, D. R. Jurgensen, M. de Bruijne, M. Loog, M. Nielsen, and F. Lauze. "Bicycle chain shape models." In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR Workshops). IEEE, 2009. http://dx.doi.org/10.1109/cvpr.2009.5204053.

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Reports on the topic "CHARN models":

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Lohn, Andrew. Poison in the Well: Securing the Shared Resources of Machine Learning. Center for Security and Emerging Technology, June 2021. http://dx.doi.org/10.51593/2020ca013.

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Modern machine learning often relies on open-source datasets, pretrained models, and machine learning libraries from across the internet, but are those resources safe to use? Previously successful digital supply chain attacks against cyber infrastructure suggest the answer may be no. This report introduces policymakers to these emerging threats and provides recommendations for how to secure the machine learning supply chain.
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Wereley, Norman M., and Bruce K. Walker. Approximate Evaluation of Semi-Markov Chain Reliability Models,. Fort Belvoir, VA: Defense Technical Information Center, February 1988. http://dx.doi.org/10.21236/ada194669.

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Farris, Stephen, and Manuel D. Rossetti. Hybrid Simulation/Analytic Models for Military Supply Chain Performance Analysis. Fort Belvoir, VA: Defense Technical Information Center, October 2004. http://dx.doi.org/10.21236/ada445893.

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Gregorio, J., J. Hughes, and C. Lorch. Model Based Definition – Recommendations for Supply Chain Integration. National Physical Laboratory, February 2023. http://dx.doi.org/10.47120/npl.ms46.

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Robert H. Hurt and Eric M. Suuberg. STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION. Office of Scientific and Technical Information (OSTI), May 2000. http://dx.doi.org/10.2172/781790.

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Hurt, Robert, Joseph Calo, Robert Essenhigh, and Christopher Hadad. STRUCTURE BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION. Office of Scientific and Technical Information (OSTI), June 2001. http://dx.doi.org/10.2172/786860.

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Hurt, R., J. Calo, R. Essenhigh, C. Hadad, and E. Stanley. Structure-Based Predictive model for Coal Char Combustion. Office of Scientific and Technical Information (OSTI), March 1997. http://dx.doi.org/10.2172/646004.

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Hurt, R., J. Calo, R. Essenhigh, C. Hadad, and E. Stanley. Structure-Based Predictive model for Coal Char Combustion. Office of Scientific and Technical Information (OSTI), June 1997. http://dx.doi.org/10.2172/646324.

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Hurt, R., J. Colo, R. Essenhigh, C. Hadad, and E. Stanley. Structure-Based Predictive model for Coal Char Combustion. Office of Scientific and Technical Information (OSTI), September 1997. http://dx.doi.org/10.2172/646325.

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Christopher Hadad, Joseph Calo, Robert Essenhigh, and Robert Hurt. Structure-Based Predictive Model for Coal Char Combustion. Office of Scientific and Technical Information (OSTI), April 1998. http://dx.doi.org/10.2172/2301.

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To the bibliography