다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Data Mining Practical Machine Learning Tools and Techniques

Statistical Analysis with Missing Data

A freely available dataset produced from three million Landsat satellite images reveals substantial changes in the distribution of global surface water over the past 32 years and their causes, from climate change to human actions. The distribution of surface water has been mapped globally, and local-to-regional studies have tracked changes over time. But to date, there has been no global and methodologically consistent quantification of changes in surface water over time. Jean-Francois Pekel and colleagues have analysed more than three million Landsat images to quantify month-to-month changes in surface water at a resolution of 30 metres and over a 32-year period. They find that surface waters have declined by almost 90,000 square kilometres—largely in the Middle East and Central Asia—but that surface waters equivalent to about twice that area have been created elsewhere. Drought, reservoir creation and water extraction appear to have driven most of the changes in surface water over the past decades. The location and persistence of surface water (inland and coastal) is both affected by climate and human activity1 and affects climate2,3, biological diversity4 and human wellbeing5,6. Global data sets documenting surface water location and seasonality have been produced from inventories and national descriptions7, statistical extrapolation of regional data8 and satellite imagery9,10,11,12, but measuring long-term changes at high resolution remains a challenge. Here, using three million Landsat satellite images13, we quantify changes in global surface water over the past 32 years at 30-metre resolution. We record the months and years when water was present, where occurrence changed and what form changes took in terms of seasonality and persistence. Between 1984 and 2015 permanent surface water has disappeared from an area of almost 90,000 square kilometres, roughly equivalent to that of Lake Superior, though new permanent bodies of surface water covering 184,000 square kilometres have formed elsewhere. All continental regions show a net increase in permanent water, except Oceania, which has a fractional (one per cent) net loss. Much of the increase is from reservoir filling, although climate change14 is also implicated. Loss is more geographically concentrated than gain. Over 70 per cent of global net permanent water loss occurred in the Middle East and Central Asia, linked to drought and human actions including river diversion or damming and unregulated withdrawal15,16. Losses in Australia17 and the USA18 linked to long-term droughts are also evident. This globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities. We anticipate that this freely available data will improve the modelling of surface forcing, provide evidence of state and change in wetland ecotones (the transition areas between biomes), and inform water-management decision-making.

High-resolution mapping of global surface water and its long-term changes

Dealing with uncertainty is always a challenging problem, and different tools have been proposed to deal with it. Recently, a new model that is based on hesitant fuzzy sets has been presented to manage situations in which experts hesitate between several values to assess an indicator, alternative, variable, etc. Hesitant fuzzy sets suit the modeling of quantitative settings; however, similar situations may occur in qualitative settings so that experts think of several possible linguistic values or richer expressions than a single term for an indicator, alternative, variable, etc. In this paper, the concept of a hesitant fuzzy linguistic term set is introduced to provide a linguistic and computational basis to increase the richness of linguistic elicitation based on the fuzzy linguistic approach and the use of context-free grammars by using comparative terms. Then, a multicriteria linguistic decision-making model is presented in which experts provide their assessments by eliciting linguistic expressions. This decision model manages such linguistic expressions by means of its representation using hesitant fuzzy linguistic term sets.

/pdf/hesitant-fuzzy-linguistic-term-sets-for-decision-making-4y2hc7e6bo.pdf

Hesitant Fuzzy Linguistic Term Sets for Decision Making

Clinical decision support systems

https://www.research.manchester.ac.uk/portal/files/82888032/Triangular_bounded_consistency_of_fuzzy_preference_relations.pdf

Triangular bounded consistency of fuzzy preference relations

The Evidential Reasoning (ER) approach has been developed to support multiple criteria decision making (MCDM) under uncertainty. It is built upon Dempster's rule for evidence combination and uses belief functions for dealing with probabilistic uncertainty and ignorance. In this introductory paper, following a brief introduction to Dempster's rule and the ER approach, we report the discovery of a new generic ER rule for evidence combination [16]. We first introduce the concepts and equations of a new extended belief function and then examine the detailed combination equations of the new ER rule. A numerical example is provided to illustrate the new ER rule.

/pdf/introduction-to-the-er-rule-for-evidence-combination-5ej4v7cd7n.pdf

Introduction to the ER rule for evidence combination

Group article recommendation based on ER rule in Scientific Social Networks

Energy development concerns not only the development of renewable energies but also the shift from centralised to clean, decentralised power generation. The development of decentralised energy (DE) is a core part of the energy and economic strategies being adopted around the world that drives the progress toward a highly sustainable future. This paper reviews the concepts, development status, trends, benefits and challenges of DE systems and analyses the existing models and methods for assessing the performance of these systems. A hierarchical decision model for evaluating the performance of DE systems is also constructed based on the framework of multiple criteria decision analysis, which considers the identification, definition and assessment grade of decision criteria. The evidential reasoning approach is applied to aggregate assessment information in a case study of the implementation of an intelligent decision system. Sensitivity and trade-off analyses are also conducted to show how the proposed model can be used to support decision making in DE systems.

/pdf/decentralised-energy-and-its-performance-assessment-models-4oqvbb0ohf.pdf

Dong-Ling Xu

Papers

Clinical decision support systems

Triangular bounded consistency of fuzzy preference relations

Introduction to the ER rule for evidence combination

Group article recommendation based on ER rule in Scientific Social Networks

Decentralised energy and its performance assessment models