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Livres sur le sujet « Multi risk assessment »

Auteur : Grafiati
Publié le 9 mars 2023
Mis à jour le 14 mars 2023

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1

Abella, Enrique Armando Castellanos. Multi-scale landslide risk assessment in Cuba. Enschede : International Institute for Geo-information Science and Earth Observation, 2008.

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2

Abella, Enrique Armando Castellanos. Multi-scale landslide risk assessment in Cuba. Enschede : International Institute for Geo-information Science and Earth Observation, 2008.

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3

Abella, Enrique Armando Castellanos. Multi-scale landslide risk assessment in Cuba. Enschede : International Institute for Geo-information Science and Earth Observation, 2008.

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4

Ren, Jingzheng, dir. Multi-Criteria Decision Analysis for Risk Assessment and Management. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78152-1.

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Gul, Muhammet, Suleyman Mete, Faruk Serin et Erkan Celik. Fine–Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-52148-6.

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6

Andy, Alaszewski, et English National Board for Nursing, Midwifery and Health Visiting., dir. Risk assessment and management in multi-agency, multi-professional health care : Education and practice. London : English National Board for Nursing, Midwifery and Health Visiting, 1998.

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7

R, Parkhurst Benjamin, Cadmus Group et Water Environment Research Foundation, dir. Aquatic ecological risk assessment : A multi-tiered approach : project 91-AER-1. Alexandria, VA : Water Environment Research Foundation, 1996.

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8

Hmara, Ivan, et Viktor Strel'nikov. Environmental epidemiology and risk assessment. ru : INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1019063.

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The material presented in the textbook is based on modern ideas about environmental epidemiology as an interdisciplinary field of knowledge, the purpose of which is a multi — level study of the "environment-human health"system. Special attention is paid to the issues of risk assessment as an integral part of ecoepidemiological research. It corresponds to the program of the discipline "Environmental Epidemiology", approved by the Scientific and Methodological Council for Environmental Education of UMO Universities. For students in the field of training 05.03.06 "Ecology and nature management", as well as related biological, environmental and medical areas and specialists of the relevant work profiles.
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9

Olsen, Odd Einar. Standardization and risk governance : A multi-disciplinary approach. Abingdon, Oxon : Routledge, 2020.

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10

SETAC Workshop on Framework for Ecological Risk Management (1997 Williamsburg, Va.). A multi-stakeholder framework for ecological risk management : Summary of a SETAC technical workshop. Pensacola, FL : SETAC Press, 1998.

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11

United States. Federal Emergency Management Agency., dir. Multi hazard identification and risk assessment : The cornerstone of the national mitigation strategy. [Washington, D.C : Federal Emergency Management Agency, 1997.

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12

Sorvari, Jaana. Application of risk assessment and multi-criteria analysis in contaminated land management in Finland. Helsinki : Edita Prima, 2010.

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13

United States. Nuclear Regulatory Commission., dir. Multi-agency radiation survey and site investigation manual (MARSSIM) : Final. Washington, D.C : United States, Nuclear Regulatory Commission, 1997.

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14

Indonesia) Forum Riset Geomatika (2006 Jakarta. Forum Riset Geomatika (GeoReForm 2006) : Multi-hazards, challenges for risk assessment, mapping, and management : prosiding. Cibinong : Balai Penelitian Geomatika, Pusat Pelayanan Jasa dan Informasi, Badan Koordinasi Survei dan Pemetaan Nasional, 2006.

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15

Tribhuvana Viśvavidyālaya. Central Department of Environmental Science. Multi-hazard and risk assessment of Istul and Manpan watersheds, Budhi Gandaki River basin, Nepal. Kathmandu : Central Department of Environmental Science, Tribhuvan University, 2015.

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16

United States. Environmental Protection Agency., United States. Dept. of Defense., United States. Dept. of Energy., U.S. Nuclear Regulatory Commission., United States. Food and Drug Administration., Geological Survey (U.S.) et National Institute of Standards and Technology (U.S.), dir. Multi-agency radiological laboratory, analytical protocols manual. [Washington, D.C : U.S. Nuclear Regulatory Commission], 2001.

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17

Duo chi du tu fa huan jing wu ran shi gu feng xian qu hua = Multi-scale environmental pollution emergency risk zoning. Beijing : Ke xue chu ban she, 2013.

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18

United States. Environmental Protection Agency., United States. Dept. of Defense., United States. Dept. of Energy. et U.S. Nuclear Regulatory Commission., dir. Multi-agency radiation survey and site investigation manual (MARSSIM) : Draft for public comment. [Washington, DC : U.S. Nuclear Regulatory Commission?], 1996.

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19

Multi-Criteria Decision Analysis for Risk Assessment and Management. Springer International Publishing AG, 2022.

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20

Ren, Jingzheng. Multi-Criteria Decision Analysis for Risk Assessment and Management. Springer International Publishing AG, 2021.

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21

Taylor, Craig E. Robust Simulation for Mega-Risks : The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management. Springer, 2015.

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22

Taylor, Craig. Robust Simulation for Mega-Risks : The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management. Springer, 2015.

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23

Toxicological Risk Assessment and Multi-System Health Impacts from Exposure. Elsevier, 2021. http://dx.doi.org/10.1016/c2020-0-02454-0.

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Tsatsakis, Aristidis M. Toxicological Risk Assessment and Multi-System Health Impacts from Exposure. Elsevier Science & Technology Books, 2021.

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25

Tsatsakis, Aristidis M. Toxicological Risk Assessment and Multi-System Health Impacts from Exposure. Academic Press, 2021.

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26

Olsen, Odd Einar. Standardization and Risk Governance : A Multi-Disciplinary Approach. Taylor & Francis, 2019.

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27

Kumar, Vijay, Prasenjit Chatterjee, Rajeev Kumar et Jyoti Chawla. Multi-Criteria Decision Making for Risk Assessment of Emerging Environmental Contaminants. Wiley & Sons, Limited, John, 2022.

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28

Kumar, Vijay, Prasenjit Chatterjee, Rajeev Kumar et Jyoti Chawla. Multi-Criteria Decision Making for Risk Assessment of Emerging Environmental Contaminants. Wiley & Sons, Incorporated, John, 2022.

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29

Kumar, Vijay, Prasenjit Chatterjee, Rajeev Kumar et Jyoti Chawla. Multi-Criteria Decision Making for Risk Assessment of Emerging Environmental Contaminants. Wiley & Sons, Incorporated, John, 2022.

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30

Kumar, Vijay, Prasenjit Chatterjee, Rajeev Kumar et Jyoti Chawla. Multi-Criteria Decision Making for Risk Assessment of Emerging Environmental Contaminants. Wiley & Sons, Incorporated, John, 2022.

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31

Hill, Maxine L. Multi Hazard Identification & Risk Assessment : A Cornerstone of the National Mitigation Strategy. DIANE Publishing Company, 1999.

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32

Federation, Water Environment, Benjamin R. Parkhurst et Cadmus Group. Aquatic Ecological Risk Assessment : A Multi-Tiered Approach : Project 91-Aer-1. Water Environment Federation, 1996.

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33

Pena, Neiler Medina. Adaptive Disaster Risk Assessment : Combining Multi-Hazards with Socioeconomic Vulnerability and Dynamic Exposure. Taylor & Francis Group, 2021.

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34

Pena, Neiler Medina. Adaptive Disaster Risk Assessment : Combining Multi-Hazards with Socioeconomic Vulnerability and Dynamic Exposure. Taylor & Francis Group, 2021.

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35

Pena, Neiler Medina. Adaptive Disaster Risk Assessment : Combining Multi-Hazards with Socioeconomic Vulnerability and Dynamic Exposure. Taylor & Francis Group, 2021.

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36

Risk Analysis As Polity-Making in Multi-level Administrations. Taylor & Francis Group, 2021.

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37

Multi-Asset Risk Modeling : Techniques for a Global Economy in an Electronic and Algorithmic Trading Era. Elsevier Science & Technology Books, 2013.

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38

Multi-agency radiation survey and site investigation manual (MARSSIM) : Final. [Washington, D.C : U.S. Nuclear Regulatory Commission, 1997.

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39

Multi-agency radiation survey and site investigation manual (MARSSIM) : Final. [Washington, D.C : U.S. Nuclear Regulatory Commission, 1997.

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40

Gul, Muhammet, Erkan Celik, Suleyman Mete et Faruk Serin. Fine-Kinney-Based Fuzzy Multi-Criteria Occupational Risk Assessment : Approaches, Case Studies and Python Applications. Springer International Publishing AG, 2021.

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41

Best, Katharina, Igor Mikolic-Torreira, Rebecca Balebako, Michael Johnson, Trung Tran et Krista Romita Grocholski. Assessing Force Sufficiency and Risk Using RAND's Multi-Period Assessment of Force Flow (MPAFF) Tool. RAND Corporation, 2019. http://dx.doi.org/10.7249/rr1954.

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42

Tran, Trung, Katharina Ley Best, Michael Johnson, Igor Mikolic-Torreira et Rebecca Balebako. Assessing Force Sufficiency and Risk Using RAND's Multi-Period Assessment of Force Flow (MPAFF) Tool. RAND Corporation, The, 2019.

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43

Gul, Muhammet, Erkan Celik, Suleyman Mete et Faruk Serin. Fine–Kinney-Based Fuzzy Multi-Criteria Occupational Risk Assessment : Approaches, Case Studies and Python Applications. Springer, 2020.

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44

Linkov, Igor, Gregory A. Kiker et Richard J. Wenning. Environmental Security in Harbors and Coastal Areas : Management Using Comparative Risk Assessment and Multi-Criteria Decision Analysis. Springer, 2007.

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45

Glantz, Morton, et Robert L. Kissell. Multi-Asset Risk Modeling : Techniques for a Global Economy in an Electronic and Algorithmic Trading Era. Elsevier Science & Technology Books, 2013.

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46

Ştefan, Catrinel Alice. Social-Emotional Prevention Programs for Preschool Children's Behavior Problems : A Multi-level Efficacy Assessment of Classroom, Risk Group, and Individual Level. Palgrave Macmillan, 2018.

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47

Ştefan, Catrinel Alice. Social-Emotional Prevention Programs for Preschool Children's Behavior Problems : A Multi-level Efficacy Assessment of Classroom, Risk Group, and Individual Level. Palgrave Macmillan, 2018.

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48

(Editor), Igor Linkov, Gregory A. Kiker (Editor) et Richard J. Wenning (Editor), dir. Environmental Security in Harbors and Coastal Areas : Management Using Comparative Risk Assessment and Multi-Criteria Decision Analysis (NATO Science for ... Security Series C : Environmental Security). Springer, 2007.

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49

(Editor), Igor Linkov, Gregory A. Kiker (Editor) et Richard J. Wenning (Editor), dir. Environmental Security in Harbors and Coastal Areas : Management Using Comparative Risk Assessment and Multi-Criteria Decision Analysis (NATO Science for ... Security Series C : Environmental Security). Springer, 2007.

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50

Sanderson, Benjamin Mark. Uncertainty Quantification in Multi-Model Ensembles. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.707.

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Long-term planning for many sectors of society—including infrastructure, human health, agriculture, food security, water supply, insurance, conflict, and migration—requires an assessment of the range of possible futures which the planet might experience. Unlike short-term forecasts for which validation data exists for comparing forecast to observation, long-term forecasts have almost no validation data. As a result, researchers must rely on supporting evidence to make their projections. A review of methods for quantifying the uncertainty of climate predictions is given. The primary tool for quantifying these uncertainties are climate models, which attempt to model all the relevant processes that are important in climate change. However, neither the construction nor calibration of climate models is perfect, and therefore the uncertainties due to model errors must also be taken into account in the uncertainty quantification.Typically, prediction uncertainty is quantified by generating ensembles of solutions from climate models to span possible futures. For instance, initial condition uncertainty is quantified by generating an ensemble of initial states that are consistent with available observations and then integrating the climate model starting from each initial condition. A climate model is itself subject to uncertain choices in modeling certain physical processes. Some of these choices can be sampled using so-called perturbed physics ensembles, whereby uncertain parameters or structural switches are perturbed within a single climate model framework. For a variety of reasons, there is a strong reliance on so-called ensembles of opportunity, which are multi-model ensembles (MMEs) formed by collecting predictions from different climate modeling centers, each using a potentially different framework to represent relevant processes for climate change. The most extensive collection of these MMEs is associated with the Coupled Model Intercomparison Project (CMIP). However, the component models have biases, simplifications, and interdependencies that must be taken into account when making formal risk assessments. Techniques and concepts for integrating model projections in MMEs are reviewed, including differing paradigms of ensembles and how they relate to observations and reality. Aspects of these conceptual issues then inform the more practical matters of how to combine and weight model projections to best represent the uncertainties associated with projected climate change.
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