Books: 'Demand prediction'

1

Cohen, Maxime C., Paul-Emile Gras, Arthur Pentecoste, and Renyu Zhang. Demand Prediction in Retail. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85855-1.

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Tomar, Anuradha, Prerna Gaur, and Xiaolong Jin, eds. Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6490-9.

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3

Tennant, Steven Trevor. Short term demand analysis and prediction for control of water supply. Leicester: Leicester Polytechnic, 1987.

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Tennant, S. T. Short term demand analysis and prediction for control of water supply. Leicester: Leicester Polytechnic, 1987.

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Tennant, S. T. A system description of GIDAP(Graphical Interactive Demand Analysis & Prediction program. Leicester: Leicester Polytechnic, 1986.

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Tennant, S. A system description of GIDAP: (A Graphical Interactive Demand Analysis and Prediction Program). Leicester: Leicester Polytechnic, 1986.

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7

Coulbeck, B. Development of a demand prediction program for use in optimal control of water supply. Leicester: Leicester Polytechnic, 1985.

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8

Tennant, S. Test and verification procedures for GIDAP: (A Graphical Interactive Demand Analysis and Prediction Program). Leicester: Leicester Polytechnic, 1986.

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9

Cronin, David. Patterns in money demand: Indicators and predictions. Dublin: Research and Publications Department, Central Bank of Ireland, 1994.

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10

Grigor'ev, Anatoliy, and Evgeniy Isaev. Methods and algorithms of data processing. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1032305.

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The tutorial deals with selected methods and algorithms of data processing, the sequence of solving problems of processing and analysis of data to create models behavior of the object taking into account all the components of its mathematical model. Describes the types of technological methods for the use of software and hardware for solving problems in this area. The algorithms of distributions, regressions vremenny series, transform them with the aim of obtaining mathematical models and prediction of the behavior information and economic systems (objects). The second edition is supplemented by materials that are in demand by researchers in the part of the correct use of clustering algorithms. Are elements of the classification algorithms to identify their capabilities, strengths and weaknesses. Are the procedures of justification and verify the adequacy of the results of the cluster analysis, conducted a comparison and evaluation of different clustering techniques, given information about visualization of multidimensional data and examples of practical application of clustering algorithms. Meets the requirements of Federal state educational standards of higher education of the last generation. For students of economic specialties, specialists, and graduate students.

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11

Hussar, William J. Predicting the need for newly hired teachers in the United States to 2008-09. Washington, DC: National Center for Education Statistics, U.S. Dept. of Education, Office of Educational Research and Improvement, 1999.

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12

Quel Sénégal pour demain?: Une vision chrétienne et citoyenne. Paris: L'Harmattan, 2012.

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13

1923-, Harvey Julien, ed. Repères pour demain: Avenir et environnement au Québec. Montréal: Bellarmin, 1987.

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14

Sidorenko, Oleg. Microbiological bases of natural milk starter culture. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1150302.

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For the first time, the educational and methodological manual summarizes knowledge about the peculiarities of the ecology of lactobacilli of natural starter cultures of different geographical zones of Russia. Geographical races of lactobacilli and yeast of dairy national products can be a source of new, more resistant to extreme factors (including medicinal preparations) enzymes that will be in demand in biotechnology, medicine. Gives fundamentally important predictions that can be experimentally verified. The prospect of treating the microbiome of the digestive organs is shown — eliminating therapy with bacteriophages, lactotherapy instead of chemotherapy. Meets the requirements of the federal state educational standards of higher education of the latest generation. It is intended for the preparation of students of biological specialties, agricultural technologists, as well as bachelors in the profiles "Technology of production, storage and processing of animal products" and "Natural starter cultures" in the directions: 35.03.07 "Technology of production and processing of agricultural products", 19.03.03 and 19.04.03 "Food of animal origin".

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15

Robinson, Grant. The demand for and production of a new technique for predicting expenditure patterns of construction projects for estate services directorate of the D.H.S.S. (Northern Ireland). [s.l: The Author], 1994.

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16

Cohen, Maxime C., Paul-Emile Gras, Arthur Pentecoste, and Renyu Zhang. Demand Prediction in Retail: A Practical Guide to Leverage Data and Predictive Analytics. Springer International Publishing AG, 2022.

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17

Jin, XiaoLong, Anuradha Tomar, and Prerna Gaur. Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting. Springer, 2023.

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18

Manousakis, Alexandros I. The use of neural networks to help facilitate the accurate prediction of electricity demand on Crete. 2000.

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19

Fitzpatrick, Timothy William. Toward understanding and predicting the performance of demand release disinfectants. 1986.

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20

Permut, Howard, Illinois Regional Transportation Author, and Inwon Lee. Methods of Predicting Local Demand for New Rapid Transit Services. Creative Media Partners, LLC, 2018.

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21

Jong, Gerard de. Expedite: Expert-System Based Predictions of Demand for Internal Transport in Europe. Rand Corporation, 2003.

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22

de, Jong Gerard, EXPEDITE Consortium, RAND Europe, Rand Corporation, and European Commission. Directorate-General for Energy and Transport., eds. EXPEDITE: EXpert-system based PrEdictions of demand for internal transport in Europe. Santa Monica, CA: RAND, 2003.

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23

Buchman, Tim, and Michael Sterling. Staffing models in the ICU. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0002.

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Three decades ago a critical care provider surplus was forecast. Projections changed at the turn of the century when the Committee on Manpower of Pulmonary and Critical Care Societies (COMPACCS) report was issued. Demographers, statisticians, and clinicians used population, patient, hospital, and provider data to forecast that the supply for critical care physicians would not keep pace with demand, and that the shortfall would be around 22% by 2020, climbing to 35% by 2030. In 2006, the Health Resources and Services Administration (HRSA) similarly forecast a significant shortage of intensivists by 2020. All signs suggest that the COMPACCS prediction is correct. This chapter describes and discusses three novel strategies by which intensivist expertise can be leveraged to provide care for a larger group of critically-ill patients. The three strategies include the use of hospitalists, engagement of affiliate providers (nurse practitioners and physician assistants with advanced critical care competencies), and investment in tele- ICU services. These strategies are complementary and can be combined to provide models tailored to local needs and resources.

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24

Green, Jason, Dimitar Antov, and Mark Henneman. Optimizing Growth: Predictive and Profitable Strategies to Understand Demand and Outsmart Your Competitors. Wiley & Sons, Incorporated, John, 2018.

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25

author, Henneman Mark 1961, and Antov Dimitar 1978 author, eds. Optimizing growth: Predictive and profitable strategies to understand demand and outsmart your competitors. 2018.

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26

Green, Jason, Dimitar Antov, and Mark Henneman. Optimizing Growth: Predictive and Profitable Strategies to Understand Demand and Outsmart Your Competitors. Wiley & Sons, Incorporated, John, 2018.

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27

Le monde au XXIIe siècle : Utopies pour après-demain. Presses Universitaires de France - PUF, 2014.

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28

Chase, Charles W. Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. Wiley & Sons, Incorporated, John, 2021.

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29

Chase, Charles W. Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. Wiley & Sons, Limited, John, 2021.

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30

Chase, Charles W. Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. Wiley & Sons, Incorporated, John, 2021.

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31

Chase, Charles W. Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. Wiley & Sons, Incorporated, John, 2021.

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32

Stone, Emily. Do Women Compete for Mates When Men Are Scarce? Edited by Maryanne L. Fisher. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199376377.013.16.

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This review explores whether and how imbalances in the number of men and women—the sex ratio—affects mating competition. I evaluate the available evidence against two hypotheses: a mating supply and demand hypothesis, which predicts mate competition to increase when mates are scarce, and predictions from a ‘faithful as your options’ hypothesis, which suggests mate competition should increase with a surplus of mates because the returns to mating effort are greatest. Men’s mating effort consistently increased with a surplus of mates, supporting the ‘faithful as your options’ hypothesis, but results for women’s mating effort were mixed. Some measures supported the mating supply and demand hypothesis, some supported the ‘faithful as your options’ hypothesis, and some found no relationship with the sex ratio. Socioeconomic development may explain variation in sex ratio effects for women if men are better able to constrain women’s mating effort in traditional societies, or other variables, like variation in mate quality, may better explain women’s mate competition.

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33

Stegenga, Jacob. Drug Regulation and the Inductive Risk Calculus. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190467715.003.0002.

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The drug approval process is fraught with inductive risk. Regulators must make a prediction about whether or not an experimental drug will be effective and safe. Such inductive risk has important practical consequences, and so non-epistemic values about the importance of these consequences impact the regulatory decisions. To balance the demands of the non-epistemic values, regulators must perform an “inductive risk calculus.” In the American context, this inductive risk calculus is not well-managed. For a variety of fine-grained methodological reasons, the epistemic standard with which the FDA assesses experimental pharmaceuticals is low. This chapter discusses these problems and argues that the inductive risk calculus for pharmaceutical regulation should be retuned in a variety of ways.

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34

Conti-Brown, Peter. Politics, Independence, and Retirees. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198827443.003.0002.

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Until recently, it was widely believed that central banks must protect people from their own worst instincts: the populace demands easy money and low interest rates, and a politically sensitive representative class will give it to them. Central banks have the responsibility of resolving this time inconsistency problem by protecting the long-term value of the currency even against the short term demands of politics. Yet the financial crisis of 2008 and the 2016 election have changed this narrative. This chapter explores how this new political economy of central banking, in the face of long-term low interest rates, changes the posture of central banks against the rest of the polity. It discusses some history of political pressures against central banks in other climates and makes predictions about how the ‘new normal’ of lower interest rates will challenge the Fed’s ability to stay above the political fray, despite its best intentions.

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35

Mills, Gary H. Pulmonary disease and anaesthesia. Edited by Philip M. Hopkins. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0082.

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Respiratory adverse events are the commonest complications after anaesthesia and have profound implications for the recovery of the patient and their subsequent health. Outcome prediction related to respiratory disease and complications is vital when determining the risk:benefit balance of surgery and providing informed consent. Surgery produces an inflammatory response and pain, which affects the respiratory system. Anaesthesia produces atelectasis, decreases the drive to breathe, and causes muscle weakness. As the respiratory system ages, closing capacity increases and airway closure becomes an increasing issue, resulting in atelectasis. Increasing comorbidity and polypharmacy reduces the patient’s ability to eliminate drugs. The proportion of major operations on older frailer patients is rising and postoperative recovery becomes more complicated and the demand for critical care rises. At the same time, the population is becoming more obese, producing rapid decreases in end-expiratory lung volume on induction, together with a high incidence of sleep-disordered breathing. Despite this, many high-risk patients are not accurately identified preoperatively, and of those that are admitted to critical care, some are discharged and then readmitted to the intensive care unit with complications. Respiratory diseases may lead to increases in pulmonary vascular resistance and increased load on the right heart. Some lung diseases are primarily fibrotic or obstructive. Some are inflammatory, autoimmune, or vasculitic. Other diseases relate to the drive to breathe, the nerve supply to, or the respiratory muscles themselves. The range of types of respiratory disease is wide and the physiological consequences of respiratory support are complex. Research continues into the best modes of respiratory support in theatre and in the postoperative period and how best to protect the normal lung. It is therefore essential to understand the effects of surgery and anaesthesia and how this impacts existing respiratory disease, and the way this affects the balance between load on the respiratory system and its capacity to cope.

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36

Determining Design Energy Targets - Predicting Energy Demand at Design Stage - Sub-metering - Monitoring Feedback from Designers and Occupiers (Design & Maintenance Guide: 17). The Stationery Office Books (Agencies), 1999.

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37

International Conference on Gears 2017. VDI Verlag, 2017. http://dx.doi.org/10.51202/9783181022948.

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Talking about the design of modern high-performance power train applications, one of the essential components to focus on are the gears. Gears convert torque and speed in a very wide power range, at low cost and with minimal losses and noise emission. However, the demands regarding cost, power density, NVH-behavior and efficiency are steadily increasing. Demands, which can only be met using modern gearing technologies that allow combining individual materials, heat treatment and manufacturing processes. Particularly in the industrial sector, the requirements for the reliability and service life of the gear units have increased. Therefore, more and more accurate calculation methods are required for the load bearing capacity, life expectancy and failure probability as well as better test methods. This aspect is also becoming more important with regard to Industry 4.0 and Predictive Maintenance. In addition, the potentials of innovative production methods like powder metal sintering, plas...

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38

Martich, Daniel, and Jody Cervenak. Integration of information technology in the ICU. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0007.

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As we look to the evolving health care industry with improved care quality, health outcomes, and cost parameters, the demands of the critical care environment require a transformation. Technology, process, and people are at the centre of this transformation. The power is in the knowledge that can be achieved and the process improvements that can be made through automation. Five major areas of technology evolution include workflow automation, information exchange, clinical decision support, and predictive modelling, remote monitoring, and data analytics. If designed properly, technology can result in doing things differently (better) and doing different things. Information exchange is required for quality and efficient critical care information delivery. Data analytics will use information for comparative effectiveness, registry reporting, population management, and research study recruiting.

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39

Jackson, Natalie. The Rise of Poll Aggregation and Election Forecasting. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.28.

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This chapter discusses (1) the development of election poll aggregation and its use in popular election forecasts, (2) the technical and statistical demands of using polls this way, and (3) the controversies surrounding aggregation and forecasting. The first section covers how increases in publicly released polls resulted in poll averaging and aggregation websites becoming popular in the early 2000s, then how election forecasting using polls as the biggest predictors became popular in the media. The second section discusses how polls are aggregated and how aggregations vary. The focus then turns to how polls are used in election forecasts. Finally, common questions that arise from poll aggregation and forecasting are addressed: Are averages always better than single polls? Are there too many forecasts; do we need to aggregate the forecasts? Are we expecting too much from polls, which are meant to be snapshots, not predictions, by using them in forecasts?

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40

Frid, Christopher L. J., and Bryony A. Caswell. The future ocean. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198726289.003.0008.

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This chapter considers the future ocean: how it will be used by humanity, the threats from marine pollution and other synergistic human pressures. By 2050, the global population will have doubled in less than 100 years. Thus, more food, energy, transportation and waste disposal will be required. Increasing demands will be placed on ecosystems and their natural resilience will be tested to the limit. The oceans are complex dynamic systems and predicting their future state is difficult. Adaptation to these changes will require a robust scientific understanding of human impacts, their nature and scale and the options for remediation. As new materials are developed the challenges to marine pollution science continue to arise. However, as demonstrated in this book cost-effective technological solutions are not always possible. It is therefore critical that natural scientists, engineers, economists and social scientists work together to make marine pollution ‘a solvable problem’.

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41

Cartwright, Nancy. Causal Powers. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198796572.003.0002.

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Hume urged that there is no difference between the obtaining of a power and its exercise; others, that there is no difference between its exercise and the result that occurs. This chapter reinforces the reasons, based in the success of the analytic method in a variety of sciences and often in daily life, for taking exercisings to be real and separate from both the obtaining (along per-haps with triggering if needed) of a power and the overall result. If exercisings are real, the chapter urges, then the Mill-Ramsey-Lewis view of laws is in trouble, at least if laws are going to account for much of what happens, since ex-ercisings of powers surely should not be admissible into any ontology the view allows. One might hope to rescue the Mill-Ramsey-Lewis account by retaining the demand that laws and theories cover as much as possible as simply as possible but give up the requirement that they be true. In that case laws could involve exercisings but not as true features of the world, rather as part of an instrument for predicting facts that the view lets in to its ontology. This chapter adumbrates this proposal and argues that it will not work. If laws are to cover much of what we think they do, we will have to have exercisings in our ontology, and, the chapter argues (contrary to a proposal floated by Richard Corry), we can’t have exercisings without powers. So we had best accept that powers have full citizenship in the world that science presents to us.

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42

Cruickshank, Steven. Mathematical models and anaesthesia. Edited by Jonathan G. Hardman. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0027.

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The use of mathematics in medicine is not as widespread as it might be. While professional engineers are instructed in a wide variety of mathematical techniques during their training in preparation for their daily practice, tradition and the demands of other subjects mean that doctors give little attention to numerical matters in their education. A smattering of statistical concepts is typically the main mathematical field that we apply to medicine. The concept of the mathematical model is important and indeed familiar; personal finance, route planning, home decorating, and domestic projects all require the application of the basic mathematical tools we acquire at school. This utility is why we learn them. The insight that can be gained by applying mathematics to physiological and other problems within medical practice is, however, underexploited. The undoubted complexity of human biology and pathology perhaps leads us to give up too soon. There are useful and practical lessons that can be learned from the use of elementary mathematics in medicine. Anaesthetic training in particular lends itself to such learning with its emphasis on physics and clinical measurement. Much can be achieved with simple linear functions and hyperbolas. Further exploration into exponential and sinusoidal functions, although a little more challenging, is well within our scope and enables us to cope with many time-dependent and oscillatory phenomena that are important in clinical anaesthetic practice. Some fundamental physiological relationships are explained in this chapter using elementary mathematical functions. Building further on the foundation of simple models to cope with more complexity enables us to see the process, examine the predictions, and, most importantly, assess the plausibility of these models in practice. Understanding the structure of the model enables intelligent interpretation of its output. Some may be inspired to investigate some of the mathematical concepts and their applications further. The rewards can be intellectually, aesthetically, and practically fruitful. The subtle, revelatory, and quite beautiful connection between exponential and trigonometric functions through the concept of complex numbers is one example. That this connection has widespread practical importance too is most pleasing.

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Books on the topic 'Demand prediction'

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