Готові списки джерел за темами / Hierarchical Demand Model

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Добірка наукової літератури з теми "Hierarchical Demand Model"

Автор: Grafiati

Опубліковано: 10 січня 2023

Оновлено: 28 січня 2023

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Статті в журналах з теми "Hierarchical Demand Model"

Chattopadhyay, Nachiketa, Amita Majumder, and Dipankor Coondoo. "DEMAND THRESHOLD, ZERO EXPENDITURE AND HIERARCHICAL MODEL OF CONSUMER DEMAND." Metroeconomica 60, no. 1 (February 2009): 91–118. http://dx.doi.org/10.1111/j.1467-999x.2008.00323.x.

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Wang, Hui Li, and Zhong Ke Shi. "Hierarchical Regression Model for Analyzing Truck Freight Demand." Applied Mechanics and Materials 178-181 (May 2012): 2752–56. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.2752.

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Trucks play a significant role in transporting freight through the ground transportation systems, and it is important to be able to estimate and predict the amount of freight in a highway network. In this study, truck weight and volume data, obtained from Weigh-in-Motion stations in California, are analyzed to examine temporal and seasonal patterns. Then coupled with socio- economic variables, a hierarchical regression model is established for estimating freight demand. The model reveals that truck freight demand can be estimated by the truck annual average daily traffic along with the population, number of firms and median income at that county level. What is more, it has a predicting capability of freight weight where no truck weight data is measured. Therefore it can be served for practitioners to predict the growth of freight demand in a freeway network, and is useful to achieve the optimal flows design of cargo at all segments, regardless of whether or not weight data is available.

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Ho, Yen-Yi, Tien Nhu Vo, Haitao Chu, Xianghua Luo, and Chap T. Le. "A Bayesian hierarchical model for demand curve analysis." Statistical Methods in Medical Research 27, no. 7 (October 20, 2016): 2038–49. http://dx.doi.org/10.1177/0962280216673675.

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Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration’s policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine. The conventional approach popularly used to analyze the demand curve data is individual-specific non-linear least square regression. The non-linear least square approach sets out to minimize the residual sum of squares for each subject in the dataset; however, this one-subject-at-a-time approach does not allow for the estimation of between- and within-subject variability in a unified model framework. In this paper, we review the existing approaches to analyze the demand curve data, non-linear least square regression, and the mixed effects regression and propose a new Bayesian hierarchical model. We conduct simulation analyses to compare the performance of these three approaches and illustrate the proposed approaches in a case study of nicotine self-administration in rats. We present simulation results and discuss the benefits of using the proposed approaches.

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Ho, Yen-Yi, Tien Nhu Vo, Haitao Chu, Mark G. LeSage, Xianghua Luo, and Chap T. Le. "WITHDRAWN A Bayesian hierarchical model for demand curve analysis." Statistical Methods in Medical Research 27, no. 8 (July 9, 2018): 2401–12. http://dx.doi.org/10.1177/0962280216680651.

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Arora, Neeraj, Greg M. Allenby, and James L. Ginter. "A Hierarchical Bayes Model of Primary and Secondary Demand." Marketing Science 17, no. 1 (February 1998): 29–44. http://dx.doi.org/10.1287/mksc.17.1.29.

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Yan, Huang, Xiaoning Zhang, and Xiaolei Wang. "Hierarchical Passenger Hub Location Problem in a Megaregion Area Considering Service Availability." Promet - Traffic&Transportation 33, no. 2 (March 31, 2021): 247–58. http://dx.doi.org/10.7307/ptt.v33i2.3563.

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The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.

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Xu, Songyuan, Yuqi Liang, and Jing Zuo. "A Travel Demand Response Model in MaaS Based on Spatiotemporal Preference Clustering." Journal of Advanced Transportation 2022 (December 19, 2022): 1–15. http://dx.doi.org/10.1155/2022/2000835.

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To respond to travel demand in the MaaS system, improve transport efficiency, and optimize the framework of MaaS, we propose a travel demand response model based on a spatiotemporal preference clustering algorithm that considers the impact of travel preferences and features of the MaaS system to improve travel demand response and achieve full coverage of travel demands. Specifically, in the MaaS system, the time preference hierarchical clustering algorithm is optimized with travel preference as the perception factor and preference priority order as the iteration index. Then, we cluster the departure and arrival times of reservation demand points and iteratively analyze the discrete points to obtain the set of reservation demand points with convergent time dimensions under similar preferences. Then, the spatial preference DBSCAN clustering algorithm is improved with travel preference and preference priority order as the iteration indices, and spatial clustering of the time-dense points are updated by the silhouette coefficient to obtain reservation demand points with similar spatiotemporal preference and respond to the demands. Meanwhile, traffic resources are coordinated by the MaaS system and the flexible means of transport are deployed to spatiotemporal discrete points to achieve full coverage of travel demand. Simulation shows that when the neighborhood range is 0.5 km and the least number of reservation demand sites is 3, our spatiotemporal model achieves a response rate of reservation demand points at 95%, and a demand coverage rate of 100%, which is 15% and 6.7% higher than the hierarchical clustering model and the DBSCAN clustering model, respectively. The demand response rate is also improved compared to the spatiotemporal clustering model in the customized bus model. The model and algorithm have some applicability and can be applied to areas with fixed, semifixed and flexible route transport, thereby considerably improving the travel demand response efficiency and transport service quality.

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Suresh, P., and P. Balasubramanie. "User Demand Aware Grid Scheduling Model with Hierarchical Load Balancing." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/439362.

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Grid computing is a collection of computational and data resources, providing the means to support both computational intensive applications and data intensive applications. In order to improve the overall performance and efficient utilization of the resources, an efficient load balanced scheduling algorithm has to be implemented. The scheduling approach also needs to consider user demand to improve user satisfaction. This paper proposes a dynamic hierarchical load balancing approach which considers load of each resource and performs load balancing. It minimizes the response time of the jobs and improves the utilization of the resources in grid environment. By considering the user demand of the jobs, the scheduling algorithm also improves the user satisfaction. The experimental results show the improvement of the proposed load balancing method.

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Li, Ting-ting, Rui Song, Shi-wei He, Ming-kai Bi, Wei-chuan Yin, and Ying-qun Zhang. "Multiperiod Hierarchical Location Problem of Transit Hub in Urban Agglomeration Area." Mathematical Problems in Engineering 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/7189060.

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With the rapid urbanization in developing countries, urban agglomeration area (UAA) forms. Also, transportation demand in UAA grows rapidly and presents hierarchical feature. Therefore, it is imperative to develop models for transit hubs to guide the development of UAA and better meet the time-varying and hierarchical transportation demand. In this paper, the multiperiod hierarchical location problem of transit hub in urban agglomeration area (THUAA) is studied. A hierarchical service network of THUAA with a multiflow, nested, and noncoherent structure is described. Then a multiperiod hierarchical mathematical programming model is proposed, aiming at minimizing the total demand weighted travel time. Moreover, an improved adaptive clonal selection algorithm is presented to solve the model. Both the model and algorithm are verified by the application to a real-life problem of Beijing-Tianjin-Hebei Region in China. The results of different scenarios in the case show that urban population migration has a great impact on the THUAA location scheme. Sustained and appropriate urban population migration helps to reduce travel time for urban residents.

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Xi, Jianfeng, Kai Mu, Tongqiang Ding, Chengyuan Zhang, and Hongyu Guo. "A macroscopic and hierarchical location model of regional road traffic disaster relief material repository." Advances in Mechanical Engineering 11, no. 1 (January 2019): 168781401882176. http://dx.doi.org/10.1177/1687814018821764.

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Since the disaster point of road traffic emergency and the emergency demand were uncertain, the demand weighting model and the hierarchical location model are suitable for the characteristics of road traffic emergency. According to the requirements for coverage area of the macroscopic-location of the large area of disaster relief material repository, the demand weighting model and the hierarchical location model were established in this article. Among them, the demand weight model was solved by modeling, and the demand weight of each disaster point was obtained; the location model was combined with immune algorithm and ant colony algorithm to get the hierarchical location scheme. Finally, Jing-jin-ji that represented China’s “capital circle” was taken as an example, the model was solved using MATLAB, the mathematical software, and provided scientific and reasonable decision-making support for location selection. Moreover, it also provided a basis for the classification of the road traffic disaster relief material repository.

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Більше джерел

Дисертації з теми "Hierarchical Demand Model"

Arora, Neeraj. "A hierarchical model to study primary demand." The Ohio State University, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=osu1277406634.

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Morckel, Victoria Chaney. "Predicting the Probability of Housing Abandonment Using Hierarchical and Spatial Models." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345167783.

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Smith, Adam Nicholas. "Bayesian Analysis of Partitioned Demand Models." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1497895561381294.

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Хазім, Ямен. "Моделі и методи управління багатонгоменклатурним складським запасом в умовах невизначеності попиту". Thesis, НТУ "ХПІ", 2016. http://repository.kpi.kharkov.ua/handle/KhPI-Press/22708.

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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.13.03 – системи та процеси керування. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2016. Дисертаційна робота присвячена розробці моделей і методів управління багатономенклатурним запасом в багаторівневій складській системі в умовах невизначеності попиту. На основі аналізу відомих публікацій виявлені недоліки традиційно використовуваних методів вирішення задач управління запасами і сформульовані задачі дослідження. Запропоновано загальну технологію рішення багатономенклатурної задачі управління запасами. Задачу вирішено з урахуванням середніх витрат на зберігання нереалізованої частини товару і втрат від можливого дефіциту Розроблено методику розв'язання задачі управління запасами за ймовірнісним критерієм. Розглянуто методи оцінки ефективності функціонування системи масового обслуговування з немарківським вхідним потоком і немарківським обслуговуванням. Запропоновано марківську модель функціонування складської системи "оптова база - магазини" і обґрунтовано метод розрахунку розподілу ймовірностей станів. Запропоновано метод раціонального розподілу ресурсу в ієрархічній складській системі. Для випадку, коли процес функціонування системи не може бути адекватно описаний марківськими методами, задача управління вирішується з використанням імітаційної моделі. Проведено аналіз ефективності функціонування в залежності від характеристик процесу попиту і самої системи.
Thesis for scientific degree of candidate of technical sciences, specialty 05.13.03 – systems and management processes. – National Technical University "Kharkiv Polytechnic Institute", Kharkov, 2016. The thesis is devoted to the development of models and multinomenclature stock management in a tiered storage system under demand uncertainty. On the basis of the known publications identified deficiencies commonly used methods for solving the inventory management problems and formulate research problems. Total technology solutions diversified inventory management tasks. The problem is solved taking into account the average cost of storing unsold part of the goods and losses due to a possible deficit procedure was developed for solving the problem of inventory management on probabilistic criteria. The methods of evaluating the performance of a queuing system with non-Markov and non-Markov input flow service. A Markov model of operation storage system "wholesale warehouse - shops" and justified method of calculating the probability distribution of states. A method for rational resource allocation in a hierarchical storage system. For the case where the system of functioning of the process can not be adequately described by the Markov method, control is achieved by using a simulation model. The analysis of the efficiency of the process, depending on the characteristics of demand and the system itself.

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Хазим, Ямен. "Модели и методы управления многономенклатурным складским запасом в условиях неопределенности спроса". Thesis, НТУ "ХПИ", 2016. http://repository.kpi.kharkov.ua/handle/KhPI-Press/22709.

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Диссертация на соискание ученой степени кандидата технических наук по специальности 05.13.03 – системы и процессы управления. – Национальный технический университет "Харьковский политехнический институт", Харьков, 2016. Диссертационная работа посвящена разработке моделей и методов управления многономенклатурным запасом в многоуровневой складской системе в условиях неопределенности спроса. На основе анализа известных публикаций выявлены недостатки традиционно используемых методов решения задач управления запасами и сформулированы задачи исследования. Предложена общая технология решения многономенклатурной задачи управления запасами. Задача решена с учетом средних затрат на хранение непроданной части товара и потерь от возможного дефицита. Задача с учетом ограничений решена методом неопределенных множителей Лагранжа. Разработана методика решения задачи управления запасами по вероятностному критерию. Для случая рэлеевского распределения спроса решение сведено к системе уравнений, решаемых численно. Предложена марковская модель функционирования складской системы "оптовая база – магазины". Введены графовая модель системы и система дифференциальных уравнений для описания поведения распределения вероятностей состояний системы. Предложен метод расчета распределения вероятностей состояний. Предложен метод рационального распределения ресурса в иерархической складской системе. Для случая рэлеевского спроса получено аналитическое решение. Рассмотрен метод решения задачи управления запасами в иерархической системе в ситуации, когда процесс функционирования системы не может быть адекватно описан марковскими методами. В этом случае задача управления решается с использованием имитационной модели. Проведен анализ эффективности функционирования в зависимости от характеристик процесса спроса и самой системы.
Thesis for scientific degree of candidate of technical sciences, specialty 05.13.03 – systems and management processes. – National Technical University "Kharkiv Polytechnic Institute", Kharkov, 2016. The thesis is devoted to the development of models and multinomenclature stock management in a tiered storage system under demand uncertainty. On the basis of the known publications identified deficiencies commonly used methods for solving the inventory management problems and formulate research problems. Total technology solutions diversified inventory management tasks. The problem is solved taking into account the average cost of storing unsold part of the goods and losses due to a possible deficit procedure was developed for solving the problem of inventory management on probabilistic criteria. The methods of evaluating the performance of a queuing system with non-Markov and non-Markov input flow service. A Markov model of operation storage system "wholesale warehouse - shops" and justified method of calculating the probability distribution of states. A method for rational resource allocation in a hierarchical storage system. For the case where the system of functioning of the process can not be adequately described by the Markov method, control is achieved by using a simulation model. The analysis of the efficiency of the process, depending on the characteristics of demand and the system itself.

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Smyth, Kevin Barry. "An Exploration of and Case Studies in Demand Forecast Accuracy: Replenishment, Point of Sale, and Bounding Conditions." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1506682418566979.

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Bromage, Adam Carl. "Reconceptualising the Nature of Executive Functioning: Introducing the Hierarchical Demand Model (HDM)." Thesis, 2020. https://vuir.vu.edu.au/42032/.

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Over the past 20 years, many investigations have sought to define the construct of Executive Functioning (EF) via the fragmentation of Executive Function skillsets. This approach has served useful for the demarcation and detailed account of complex cognitive functions that can manifest during various clinical pathologies. Yet, theoretical accounts remain heterogeneous in these representations, and neuropsychological measures of their purported constituents are critiqued for measurement impurity and poor ecological validity. This study aimed to reconceptualise traditional scoring approaches of a variety of EF tests through the lens of cognitive control theory, via a 3-study design. Performance on 13 different EF tests were assessed in 105 participants (Mage= 30.00, SD = 7.11). Study 1 sought to develop, apply, and preliminary test a Demand Classification System (DCS). The DCS comprised of 16 classifications of demand across a criterion of complexity (Abstraction, Contextual Stability, Action Rules, Instruction and Rules, Dual-Task Requirements) and novelty (Automaticity, Schematic, and Episodic). Confirmatory Factor Analysis (CFA) demonstrated that within these tests, performance variance could be attributed to the nature of its internal demands for complexity and novelty. Using congeneric modelling, Study 2 revealed that complexity- novelty classifications accounted for a significant amount of unique shared variance between tests. Factor weighted performance scores were created for each level of demand identified by Studies 1 and 2. Finally, Study 3 aimed to assess the relationships between performance at varying levels of demand using Structural Equation Modelling. The results supported the existence of hierarchically contingent relationships that align with existing neurological mechanisms proposed for cognitive control. The collective outcome of these analyses is the offering of The Hierarchical Demand Model (HDM) which proposes that in order to successfully engage in a goal-directed task the individual must recognise what is known, appraise what is required, and reconcile the difference to formulate an effective response. The HDM and its agent the DCS, collectively serves to operationalise known influencers of demand to the neuropsychological testing environment. This has significant implications not only for the future use of neuropsychological tools as singular measures of EF, but also how these measures can be better utilised for the assessment of overall higher-order cognitive ability. This approach urges the recognition of synergy between cognitive control and EF, and the duality of their influence over the execution of controlled behaviour in response to demand. This project offers not only a methodical system whereby this synergistic approach can be successfully applied, but also a framework that is able to account for the nature of human engagement at various levels of complexity and novelty across a hierarchical continuum of demand.

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Книги з теми "Hierarchical Demand Model"

Hendricks, Wallace E. Hierarchical spline models for conditional quantiles and the demand for electricity. Urbana-Champaign, Ill: Bureau of Economic and Business Research, 1990.

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Jacobsson, Bengt, and Göran Sundström. Governing the State. Edited by Jon Pierre. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199665679.013.20.

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In modern democracies, demands put on governments to govern are high. However, the governing of states has proven difficult. The difficulties can be explained by the fact that modern states possess a complexity unparalleled in any other organization. Ambiguity, conflicting interests, compromises, and the risk of overload reveal governments as everything but those rational, coordinated and problem-solving entities that they routinely are presented as. However, this does not mean that states are ungovernable. Governments are often able to govern state activities, but they do it in other ways than those implied by contemporary management models with their hierarchical, top-down-oriented, command-and-control methods. Based on a multitude of empirical studies in Sweden, this chapter discusses six strategies that the Swedish government uses when governing state agencies: creating formal organizations, positioning, fostering competition, distancing, forming communication channels, and storytelling.

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Dallmayr, Fred. The Prospect of Confucian Democracy. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190670979.003.0006.

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Recent times have seen resolute efforts seeking to reconcile Asian traditions with democracy, specifically by bending some hierarchical features of the past in the direction of the qualitative equality and relationality demanded in our age. The chapter concentrates on debates in several Asian countries, including China, about the compatibility of Confucian teachings with the democratic requirement of equal citizenship. The chapter distinguishes between a minimalist, a maximalist, and a balanced approach. In the first case, Confucian teachings are restricted to the purely private sphere removed from public life. This model robs Confucianism of the crucial element of social relationality. In the second type, Confucianism is elevated to a dominant creed, in violation of the constitutive openness (or emptiness) of the democratic public space. The last version rejects this totalizing ambition, but without abandoning Confucianism’s educational and socializing qualities, thus arriving at a social-democratic vision.

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Частини книг з теми "Hierarchical Demand Model"

Florian, Michael, Jia Hao Wu, and Shuguang He. "A Multi-Class Multi-Mode Variable Demand Network Equilibrium Model with Hierarchical Logit Structures." In Applied Optimization, 119–33. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-6871-8_8.

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Yelland, Phillip M., and Xiaojing Dong. "Forecasting Demand for Fashion Goods:A Hierarchical Bayesian Approach." In Intelligent Fashion Forecasting Systems: Models and Applications, 71–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39869-8_5.

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Wang, Cuizhen, Camelia M. Kantor, Jerry T. Mitchell, and Todd S. Bacastow. "Digital Earth Education." In Manual of Digital Earth, 755–83. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9915-3_24.

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Abstract Digital Earth (DE) education provides students with geospatial knowledge and skills to locate, measure, and solve geographic problems on Earth’s surface. The rapid development of geospatial technology has promoted a new vision of DE to embrace data infrastructure, social networks, citizen science, and human processes on Earth. The high demand for a geospatial workforce also calls for an ever-changing, diverse form of learning experiences. Limited efforts, however, have been made regarding DE education to adapt to this changing landscape, with most interventions falling short of expectations. This chapter gives an overview of current teaching and learning structures with DE technologies. Successes and obstacles for K-12 education are explored first, followed by classroom technologies and experiential learning and outreach exercises such as academic certificates and internships in higher education. Taking the geospatial intelligence model from the U.S. Geospatial Intelligence Foundation (USGIF) as an example, recent advancements in DE education for professional careers are described via its geospatial competencies, hierarchical frameworks, and credentials. In alignment with the principles of DE development, future DE education calls for an integrated learning framework of open data, real-world context, and virtual reality for better preparedness of our students in the geospatial world.

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Patni, Jagdish Chandra. "Hierarchical Load Balancing Model by Optimal Resource Utilization." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, 150–64. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5339-8.ch007.

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Powerful computational capabilities and resource availability at a low cost is the utmost demand for high performance computing. The resources for computing can viewed as the edges of an interconnected grid. It can attain the capabilities of grid computing by balancing the load at various levels. Since the nature of resources are heterogeneous and distributed geographically, the grid computing paradigm in its original form cannot be used to meet the requirements, so it can use the capabilities of the cloud and other technologies to achieve the goal. Resource heterogeneity makes grid computing more dynamic and challenging. Therefore, in this article the problem of scalability, heterogeneity and adaptability of grid computing is discussed with a perspective of providing high computing, load balancing and availability of resources.

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Teng, Yu, and Nan Kong. "Assessing Multi-Site Distributed Coordination in Dynamic Assignment of Time-Critical Entity via Agent-Based Simulation." In Advances in Civil and Industrial Engineering, 58–72. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2098-8.ch004.

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This chapter investigates distributed coordination in dynamic assignment of time-critical entities among multiple sites. The authors develop an agent-based simulation model in which each agent applies some adaptive assignment rule to match supplies and demands that are generated at its own site. They assume each agent has autonomy to design its hierarchical assignment rule and update it based on periodical review of its assignment performance. The authors model the benefit of each assignment based on the life spans of the resource and the need, and a distance measure between them. They consider two distinct centralized initial assignment rules and assess how agents update their rules. The authors also evaluate the impact of different agent environments, numbers of supply/demand agents, and ratios of supply/demand rates.

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Aghezzaf, El-Houssaine, and Carles Sitompul. "Design of Robust Supply Chains." In Advances in Civil and Industrial Engineering, 200–229. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2098-8.ch011.

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In a supply chain operating under uncertainty, a possible approach to reduce the complexity and scope of the planning process is to organize all involved critical planning decisions in a hierarchical structure. This chapter attempts to explore new ways of integrating production and scheduling plans in a complex supply chain taking into account effects of some specific uncertainty types. In particular, uncertainty types inherent to the demand and to the process or equipment are considered. To deal with demand uncertainty at the strategic level, the safety stock placement problem in supply chains with limited production capacities is investigated. Results of this analysis and its consequences at the design level are reported and discussed. At the tactical level, each stage in the supply chain generates its own aggregate plans in order to balance supply and demand. To deal with uncertainty at this level, some robust deterministic planning models are discussed. These models make use only of the readily available data, such as averages and standard deviations, related to the uncertain planning parameters. At the operational level, the issue of disaggregating the generated robust tactical plans into detailed plans is investigated. A model taking into account the progressive deterioration of the production equipment is discussed. The results of some simulations are also reported and discussed.

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Gavrilova, Marina L. "Adaptive Computation Paradigm in Knowledge Representation." In Software Applications, 3258–71. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-060-8.ch188.

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The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.

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Gavrilova, Marina L. "Adaptive Computation Paradigm in Knowledge Representation." In Utilizing Information Technology Systems Across Disciplines, 301–14. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-616-7.ch019.

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Zaitsev, Dmitry A., and Tatiana R. Shmeleva. "Modeling With Colored Petri Nets." In Research Anthology on Reliability and Safety in Aviation Systems, Spacecraft, and Air Transport, 397–424. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5357-2.ch015.

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Aviation and aerospace systems are complex and concurrent and require special tools for their specification, verification, and performance evaluation. The tool in demand should be easily integrated into the standard loop of model-driven development. Colored Petri nets represent a combination of a Petri net graph and a functional programming language ML that makes it powerful and convenient tool for specification of real-life system and solving both tasks: correctness proof i.e. verification and performance evaluation. This chapter studies basic and advanced features of CPN Tools – a powerful modeling system which uses graphical language of colored Petri nets. Starting with a concept of colored hierarhical timed Petri net, it goes through declaration of color sets and functions to peculiarities of hierarchical design of complex models and specification of timed characteristics. The authors accomplish the chapter with a real-life case study of performance evaluation for switched Ethernet network.

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Zaitsev, Dmitry A., and Tatiana R. Shmeleva. "Modeling With Colored Petri Nets." In Automated Systems in the Aviation and Aerospace Industries, 378–404. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7709-6.ch014.

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Тези доповідей конференцій з теми "Hierarchical Demand Model"

Bai, Lei, Lina Yao, Salil S. Kanhere, Xianzhi Wang, and Quan Z. Sheng. "STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/274.

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Multi-step passenger demand forecasting is a crucial task in on-demand vehicle sharing services. However, predicting passenger demand is generally challenging due to the nonlinear and dynamic spatial-temporal dependencies. In this work, we propose to model multi-step citywide passenger demand prediction based on a graph and use a hierarchical graph convolutional structure to capture both spatial and temporal correlations simultaneously. Our model consists of three parts: 1) a long-term encoder to encode historical passenger demands; 2) a short-term encoder to derive the next-step prediction for generating multi-step prediction; 3) an attention-based output module to model the dynamic temporal and channel-wise information. Experiments on three real-world datasets show that our model consistently outperforms many baseline methods and state-of-the-art models.

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Peng, Xufu, and Hongli Wang. "The Design of Demand Teaching Mode based on the Pattern of Hierarchical Teaching Model." In 2015 International Conference on Management, Education, Information and Control. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/meici-15.2015.3.

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Chen, Qianwen, Zude Zhou, Xiaomei Zhang, and Xuemei Jiang. "Multi-Tenant Access Control Model for Cloud Manufacturing." In ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/msec2017-2719.

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Cloud manufacturing is a new service-oriented networked manufacturing mode based on the concept of “Manufacture as a Service” and achieves the sharing of manufacturing resources and manufacturing capacity. Multi-tenancy technology can improve utilization efficiency of manufacturing resources and ensure information security among tenants, enabling users to share the cloud manufacturing resources better. To execute this new mode, isolation access and on-demand services are indispensable. However, the traditional access control model cannot satisfy the demands of multi-tenant environment on cloud manufacturing platform. To solve the demands in such an environment, a model named Multi-Tenant Access Control Model for Cloud Manufacturing (CM-MTAC) is proposed. Based on cloud manufacturing architecture, we build a hierarchical cloud manufacturing access control architecture combining multi-tenancy. Considering the demands under this condition, the elements of cloud manufacturing access control model and the relationships between them are redefined by extending the ABAC model. Then multi-tenancy authorization framework is proposed and XACML language is used to describe the policy to provide our model with on-demand service, isolation access and inter-tenant collaboration. Finally, we develop this model into the cloud manufacturing monitoring platform. Results show that our model, compared with traditional models, has a better performance of on-demand service, isolation access and inter-tenant cooperation under the environment of cloud manufacturing.

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Mukherjee, Sumanta, Krishnasuri Narayanam, Nupur Aggarwal, Digbalay Bose, and Amith Singhee. "Robust resource demand estimation using hierarchical Bayesian model in a distributed service system." In CODS COMAD 2021: 8th ACM IKDD CODS and 26th COMAD. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3430984.3431003.

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Liu Jun, Zhao Jun-Tian, and Rui Zhi-Yuan. "A hierarchical production control and scheduling model of hybrid manufacutring system with random demand." In 2008 IEEE International Conference on Automation and Logistics (ICAL). IEEE, 2008. http://dx.doi.org/10.1109/ical.2008.4636212.

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Kim, Donghun, and James E. Braun. "Hierarchical Model Predictive Control Approach for Optimal Demand Response for Small/Medium-sized Commercial Buildings." In 2018 Annual American Control Conference (ACC). IEEE, 2018. http://dx.doi.org/10.23919/acc.2018.8431566.

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Kim, Harrison M., and I. Jessica Hidalgo. "Pseudo-Hierarchical Multistage Model for System of Systems Design and Operations." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35825.

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This paper describes a multilevel, multistage approach to system of systems design optimization where a system design is linked with system allocation along the multistage decision making horizon. The approach is composed of two parts: pseudo-hierarchical formulation (i.e., how to model the stages of multiple, separate decision making processes), and multistage coordination (i.e., how efficiently the proposed model would perform). The pseudo-hierarchical formulation integrates multilevel optimization and multistage programming to capture level-by-level and stage-by-stage system design optimization. The multistage coordination is based on the alternating directions method that is incorporated as an efficient means to solve this inherently largescale optimization problem. An example on collaborative system operation and design between an airline and an aircraft manufacturer validates the methodology where an airline plans to introduce multiple new aircraft to capture dynamically changing demand of the customers. The proposed methodology is validated against the all-in-one approach and the sequential approach.

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Xu, Tao, Catalin Baicu, Brian Manley, Michael Zile, and Thomas Boland. "A Finite Element Model for Drop-on-Demand Printing of Designer Hybrid Cardiovascular Constructs." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79082.

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A Finite element model (FEM) was constructed and used to predict the mechanical properties of hybrid cardiovascular tissue engineering constructs. The model allows implementing 3D structures with desired porosities, mechanical and chemical properties. CAD models where designed using the FEM, with mechanical properties matching those of cardiac tissue. Contractile cardiac hybrids have been fabricated by arranging alternate layers of hydrogels and mammalian cardiovascular cells according to these CAD models using inkjet printers. Alginate hydrogels with controlled microshell structures were built by spraying cross-linkers onto ungelled alginic acid using inkjet printers. Cells were seen to attach to the inside of these microshells. The cells remained viable in constructs as thick as 1 cm due to the programmed porosity. Microscopic and macroscopic contractile function of cardiomyocytes sheets was observed in vitro. These results suggest that the printing method could be used for hierarchical design of functional cardiac patches, balanced with porosity for mass transport and structural support.

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Zhong, Xu, Xia Xu, Xianglin Liao, Yichun Tu, Yeshu Song, Jiajin Liu, Qian Zhao, and Xuefang Chen. "Evaluation System of Human-Factor Training Effect Based on Hierarchical Model." In 2022 29th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/icone29-91986.

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Abstract Nuclear power enterprises attach great importance to staff training and have invested a lot of resources to establish training and authorization systems based on Systematic Approach Training (SAT), including demand analysis, outline design, material preparation, training implementation and evaluation feedback five parts. However, the lack of effective training effect evaluation means in practice makes it difficult to continuously improve the training system. This paper takes human-factor training in nuclear power plants as an example, analyzes the characteristics of human factors training, such as complex training object, rich content and diverse methods, compares the Kirkpatrick model, Context, Input, Process, Product (CIPP) model and Context, Input, Reaction, Output (CIRO) model. The kirkpatrick four-layer model is selected as the theoretical basis to establish the evaluation system for the effect of nuclear power human factor training, including a closed-loop training evaluation process, five evaluation methods and corresponding tools. After a period of practice in a nuclear power operation team, this system has been proved to be able to achieve effective evaluation and continuous improvement of the human-factor training effect in nuclear power plants, and effectively improved the long-term performance of the operation team, the non human-factor mistake record has been more than 900 consecutive days. In view of the problems found in the system practice, the paper also puts forward suggestions for further improvement.

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Ying, Haochao, Fuzhen Zhuang, Fuzheng Zhang, Yanchi Liu, Guandong Xu, Xing Xie, Hui Xiong, and Jian Wu. "Sequential Recommender System based on Hierarchical Attention Networks." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/546.

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With a large amount of user activity data accumulated, it is crucial to exploit user sequential behavior for sequential recommendations. Conventionally, user general taste and recent demand are combined to promote recommendation performances. However, existing methods often neglect that user long-term preference keep evolving over time, and building a static representation for user general taste may not adequately reflect the dynamic characters. Moreover, they integrate user-item or item-item interactions through a linear way which limits the capability of model. To this end, in this paper, we propose a novel two-layer hierarchical attention network, which takes the above properties into account, to recommend the next item user might be interested. Specifically, the first attention layer learns user long-term preferences based on the historical purchased item representation, while the second one outputs final user representation through coupling user long-term and short-term preferences. The experimental study demonstrates the superiority of our method compared with other state-of-the-art ones.

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