Selection of oil spill response method in Arctic offshore waters: A fuzzy decision tree based framework

Hu, Guangji; Mohammadiun, Saeed; Gharahbagh, Abdorreza Alavi; Li, Jianbing; Hewage, Kasun; Sadiq, Rehan

doi:10.1016/j.marpolbul.2020.111705

Cited by 33 publications

(12 citation statements)

References 28 publications

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“…Fuzzy decision tree algorithm [1] is an improved algorithm of decision tree algorithm [2]. As fuzzy classifification systems based on fuzzy decision tree are generally robust, FDT have been widely and successfully applied to many fields, such as decision-making [3,4], classification and prediction [5,6], medical treatment [7,8,9], etc.…”

Section: Introductionmentioning

confidence: 99%

Z-number Decision Tree and Its Appliction

Fang¹,

Wu²,

Liu³

et al. 2023

Preprint

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Fuzzy decision tree(FDT) is an expansion and improvement of decision tree, which expands the application scope of decision tree to deal with the uncertainty and extracts classification rules efficiently. However, there are some problems in the process of sample attributes fuzzifying, such as information loss and the influence of strong personal subjectivity on the results. To solve these problems, a fuzzy decision tree algorithm based on Z-number(Z-FDT) is put forward. we propose a method to construct Z-number, first, membership functions is defined to fuzzify the data set and describe the size of the probability measure of the fuzzy set, then the cluster centers of multi-dimensional data are extracted ,using the fuzzy clustering algorithm., the membership function and cluster centers of different categories fuzzy partition the sample data set based on the features of the sample, and obtain the fuzzy sets. Finally, based on the definition of Z-number, fuzzy sets are constructed into Z-numbers. After the multidimensional data set is transformed into Z-numbers, the uncertainty measure of Z-number is used to select appropriate features to partition the data set, until the stop condition is met. Z-FDT can directly classify and predict samples with continuous attribute values, and has good generalization ability and relatively stable results, at the last, this will be confirmed through the comparative experiment with ID3, Cart and Fuzzy ID3.

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Section: Introductionmentioning

confidence: 99%

Z-number Decision Tree and Its Appliction

Fang¹,

Wu²,

Liu³

et al. 2023

Preprint

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“…This method can also apply to physical methods as marine oil spill remediation. [105][106][107] Thermal remediation methods, such as in situ burning, [108][109][110] are a simple and rapid means of remediation that requires minimal specialized equipment to remove a great deal of spilled oil efficiently. The effectiveness of this method depends on the condition of the wind and quality of the oil; it is effective when there is no wind, and the spills consists of fresh oils or light refined products, which quickly burn without endangering marine life.…”

Section: Remediation Technologies For Oil Spillsmentioning

confidence: 99%

A Role for Newly Developed Sorbents in Remediating Large‐Scale Oil Spills: Reviewing Recent Advances and Beyond

Kim

Zhang

Chung

et al. 2021

Advanced Sustainable Systems

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The conservation of ocean and freshwater have been crucial issues over the past decades, and oil/water separation is a well‐known technology to restore polluted water systems. In the meantime, oil sorbents serve as a promising means of achieving water conservation to recover from oil spills, which require a multi‐factorial approach to review high selectivity, capacity, and rate of oil recovery. However, reusability is a critical component to consider in incidents with large‐scale spills. With the development of sorbent technology, some studies have progressed to explore surface engineering and material design for high oil sorption capacity and durability. Thus, this systemic review, a summary of sorbent developments, serves as a guide to understanding practical applications that can apply to large‐scale oil spills and recognize remaining issues. In this review, the oil weathering process and oil sorption mechanisms in relation to the characteristics of target pollutants are introduced. Then, this comprehensive review focuses on materials in advanced sorbents. These materials have properties including, aligned channels for fast sorption, self‐heating capabilities for viscous oil cleanup, and magnetic‐responsiveness to enhance a collection of final products. The perspective and challenges for the next generation of oil spills remediation technology‐based oil sorbents materials are finally presented in the last section.

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“…The richness of video content and video quality determine the retention and experience of members (Farnaz et al) [ 3 ]. However, live video education evolved from the traditional video industry, but it is quite different from the traditional new media business in terms of video content, video architecture, user needs, member audience, and so on (Hu et al) [ 4 ]. Therefore, we cannot apply the traditional video model evaluation methods to the modern video education model, so we lack some evaluation and deep understanding of the current video education model.…”

Section: Introductionmentioning

confidence: 99%

MOOC Teaching Model of Basic Education Based on Fuzzy Decision Tree Algorithm

Yuanyuan

2022

Computational Intelligence and Neuroscience

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In recent years, the development of science and technology in China has greatly affected people’s ways of entertainment. In the traditional industrial model, new industries and Internet industries represented by the Internet have emerged, and the Internet video business is an emerging business that has been gradually emerging in the Internet industry in recent years. Moreover, this new teaching method has been gradually noticed in simple education, such as MOOC, I want to self-study network, and Smart Tree, and other online learning websites have sprung up. At present, the epidemic environment makes people pay more attention to this convenient and wide range of online video education. Therefore, we need to evaluate this kind of online video teaching model from the effectiveness of this kind of method and the quality of user experience. This paper takes this as the starting point and chooses the earliest online video platform, MOOC, as the model to establish a set of perfect user experience quality evaluation methods suitable for domestic online video education mode. Considering the data source, the accuracy of the results, and other factors, we chose the industry-leading platform MOOC network as an example. Through the exploration of the MOOC teaching mode in basic education, a member experience evaluation model is established based on fuzzy decision tree algorithm. The experimental results show that the model has high accuracy and high reliability.

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Selection of oil spill response method in Arctic offshore waters: A fuzzy decision tree based framework

Cited by 33 publications

References 28 publications

Z-number Decision Tree and Its Appliction

Z-number Decision Tree and Its Appliction

A Role for Newly Developed Sorbents in Remediating Large‐Scale Oil Spills: Reviewing Recent Advances and Beyond

MOOC Teaching Model of Basic Education Based on Fuzzy Decision Tree Algorithm

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