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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.

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Hesitant Fuzzy Linguistic Term Sets for Decision Making

This paper describes how the Evidential Reasoning approach for multi-criteria decision analysis, with the support of its software implementation, Intelligent Decision System (IDS), can be used to analyse whether low level radioactive waste should be stored at the surface or buried deep underground in the territory of the community of Mol in Belgium. Following an outline of the problem and the assessment criteria, the process of using IDS for data collection, information aggregation and outcome presentation is described in detail. The outcomes of the analysis are examined using the various sensitivity analysis functions of IDS. It is demonstrated that the analysis using IDS can generate informative outcomes to support the decision process.

Application of intelligent decision system to nuclear waste depository option analysis

This paper illustrates how efficiency, effectiveness, consistency and reliability of nuclear safety culture assessment can be improved by the Intelligent Decision System (IDS) tool. It describes how IDS can be used as both a knowledge management and assessment supporting tool for nuclear safety culture assessment using the IAEA Safety Culture Assessment Review Team (SCART) guidelines. Once the assessment knowledge is built into IDS, the tool provides support at the data gathering stage by retrieving the right guidance at when and where it is needed so that the assessment can be made more efficiently, consistently and objectively. At the Discussion and closing stage of the assessment, the tool generates aggregated assessment results for both a team of and individual reviewers in text and graphical formats. The text report highlights the strengths and the areas for improvement, including advice on how to improve and examples of best practices in the areas. The various graphical interfaces and charts provide side by side comparisons, panoramic view of the strengths and weaknesses, trends and profiles of assessment outcomes made by different reviewers, for different organisations or for the same organisation at different time. Those outcomes give a speedy and accurate account of the review so that discussions and feedback can be made more productively and constructively.

Supporting nuclear safety culture assessment using Intelligent Decision System software

This study aims to explore a novel method for determining attribute weights, which is a key issue in constructing and analyzing multiple-attribute decision-making (MADM) problems. To this end, a hybrid approach combining the data envelopment analysis (DEA) model without explicit inputs (DEA-WEI) and a two-layer minimax optimization scheme is developed. It is demonstrated that in this approach, the most favorable set of weights is first considered for each alternative or decision-making unit (DMU) and these weight sets are then aggregated to determine the best compromise weights for attributes, with the interests of all DMUs simultaneously considered in a fair manner. This approach is particularly suitable for situations where the preferences of decision-makers (DMs) are either unclear or difficult to acquire. Two case studies are conducted to illustrate the proposed approach and its use for determining weights for attributes in practice. The first case concerns the assessment of research strengths of 24 selected countries using certain measures, and the second concerns the analysis of the performance of 64 selected Chinese universities, where the preferences of DMs are either unknown or ambiguous, but the weights of the attributes should be assigned in a fair and unbiased manner.

Using Two-layer Minimax Optimization and DEA to Determine Attribute Weights

The attainment of high-protein-retention and low-protein-fouling membranes is crucial for industries that necessitate protein production or separation process. The present study aimed to develop a novel method for preparing polyacrylonitrile (PAN) membranes possessing a highly hydrophilic and negatively charged surface as well as interior structure. The method involved a pre-hydrolysis treatment during the preparation of the PAN dope solution, followed by phase inversion in an alkaline solution. Chemical and material characterization of the dopes and membranes uncovered that the cyclized PAN structure served as a reaction intermediate that facilitated strong hydrolysis effect during phase inversion and homogeneously formed carboxyl groups in the membrane’s interior structure. The resulting membrane showed a highly hydrophilic surface with a contact angle of 12.4° and demonstrated less than 21% flux decay and more than 95% flux recovery during multi-cycle filtration of bovine serum albumin (BSA) solution, with a high protein rejection rate of 96%. This study offers a facile and effective alternative for preparing PAN membranes with enhanced antifouling and protein-retention properties.

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Preparation of a Low-Protein-Fouling and High-Protein-Retention Membrane via Novel Pre-Hydrolysis Treatment of Polyacrylonitrile (PAN)

Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method considers the different importance weights of multiple DMs by extending the Fuzzy Preferences Programming Method (FPP). The elements of the group pairwise comparison matrices are presented as fuzzy numbers rather than exact numerical values in order to model the uncertainty and imprecision in the DMs’ judgments. Unlike the known fuzzy prioritization techniques, the proposed method is able to derive crisp weights from incomplete and fuzzy set of comparison judgments and doesn’t require additional aggregation procedures. A prototype of a decision tool is developed to assist DMs to use the proposed method for solving fuzzy group prioritization problems. A detailed numerical example is used to illustrate the proposed approach.

Dong-Ling Xu

Papers

Application of intelligent decision system to nuclear waste depository option analysis

Supporting nuclear safety culture assessment using Intelligent Decision System software

Using Two-layer Minimax Optimization and DEA to Determine Attribute Weights

Preparation of a Low-Protein-Fouling and High-Protein-Retention Membrane via Novel Pre-Hydrolysis Treatment of Polyacrylonitrile (PAN)

Deriving Weights from Group Fuzzy Pairwise Comparison Judgement Matrices