Improving early OSV design robustness by applying ‘Multivariate Big Data Analytics’ on a ship's life cycle

Abbasian, Niki Sadat; Salajegheh, Afshin; Gaspar, Henrique M.; Brett, Per Olaf

doi:10.1016/j.jii.2018.02.002

Cited by 16 publications

(13 citation statements)

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“…Data parser is a vital BDA technique that screens out outliers and thus eliminates the generation of misleading results. For the quality of input and output data, the Data Parser is provided with data fusion and data cleaning functions [51].…”

Section: A Data Parsermentioning

confidence: 99%

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An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

et al. 2020

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This paper analyses the operator's risk-based decision (RBD) company for slow steaming, and creates a sailing speed optimization model for slow steaming (SSOM-SS), aiming to balance the expected utility-based objectives (EUO) of fuel consumption, SOx emissions and delivery delay. Considering the limitations of existing theoretical fuel consumption functions under uncertainties in voyages, the authors applies big data analytics (BDA) techniques like data fusion and feature selection to provide the SSOM-SS with accurate and suitable data on fuel consumption. In addition, a solver is built based on the genetic algorithm (GA) to solve the SSOM-SS. The effectiveness of the SSOM-SS is verified through a case study on the RBD for slow steaming of an Orient Overseas Container Line (OOCL) containership sailing across the sulphur emission control areas (SECAs) in Chinese coastal regions. The results show that the SSOM-SS can facilitate the RBD for slow steaming, and provide a novel tool for sailing speed optimization. INDEX TERMS Big data analytics (BDA), slow steaming, sailing speed optimization, fuel consumption, genetic algorithm (GA), risk aversion.

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Section: A Data Parsermentioning

confidence: 99%

“…For instance, the AIS data and log data may differ in recording frequency, which could be an obstacle for further analysis. This calls for data fusion in the coherent data warehouse [51], [52]. The necessity of data fusion also arises from the inevitable missing entries in the raw data.…”

Section: ) Data Fusionmentioning

confidence: 99%

An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

et al. 2020

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“…. , l) is C e k = T k , I k , F k by applying weighted averaging or geometric averaging operators which is given in Equations (5) and (8). Ranking order of the alternatives is determine based on the score function of the aggregated values of SVNSNsC e k (k = 1, 2, .…”

Section: An Approach Based On Proposed Operatorsmentioning

confidence: 99%

“…The method is addressed to select the best alternative among the finite set of alternatives as claimed by decision makers under the preference values of the alternatives. MCDM problems extensively applied with quantitative or qualitative attribute values and have a board application in medical diagnosis [1,2], ecology [3], sensor network [4] management science and engineering [5,6], economic [7], market prediction and engineering technology [8], transport service problem [9] etc. As our modern society move forward with the decision-making process, so it always faces imprecise, vague and uncertain facts to take a decision in solving decision-making problems.…”

Section: Introductionmentioning

confidence: 99%

A Robust Single-Valued Neutrosophic Soft Aggregation Operators in Multi-Criteria Decision Making

Jana

Pal

2019

Symmetry

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Molodtsov originated soft set theory that was provided a general mathematical framework for handling with uncertainties in which we meet the data by affix parameterized factor during the information analysis as differentiated to fuzzy as well as neutrosophic set theory. The main object of this paper is to lay a foundation for providing a new approach of single-valued neutrosophic soft tool which is considering many problems that contain uncertainties. In present study, a new aggregation operators of single-valued neutrosophic soft numbers have so far not yet been applied for ranking of the alternatives in decision-making problems. To this propose work, single-valued neutrosophic soft weighted arithmetic averaging (SVNSWA) operator, single-valued neutrosophic soft weighted geometric averaging (SVNSWGA) operator have been used to compare two single-valued neutrosophic soft numbers (SVNSNs) for aggregating different single-valued neutrosophic soft input arguments in neutrosophic soft environment. Then, its related properties have been investigated. Finally, a practical example for Medical diagnosis problems provided to test the feasibility and applicability of the proposed work.

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“…MADM approaches identify how attribute information is to be processed to compute a suitable alternative or to rank the alternatives for supporting decision-making. It has been broadly applied in different domains, including engineering technology [1], operation research [2], and management science [3]. To solve decision-making problems having uncertainty, Atanassov [4] introduced the idea of intuitionistic fuzzy sets (IFSs) which involve both membership and non-membership functions, an efficient generalization of fuzzy sets [5] which characterize only membership function.…”

Section: Introductionmentioning

confidence: 99%

Multi-Attribute Decision-Making Based on m-Polar Fuzzy Hamacher Aggregation Operators

2019

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In this paper, we introduce certain aggregation operators, namely, the m-polar fuzzy (mF) Hamacher weighted average operator, mF Hamacher ordered weighted average (mFHOWA) operator, mF Hamacher hybrid average (mFHHA) operator, mF Hamacher weighted geometric (mFHWG) operator, mF Hamacher weighted ordered geometric operator, and mF Hamacher hybrid geometric (mFHHG) operator. We discuss some properties of these operators, inclusive of their ability to implement both symmetric and asymmetric treatments of the items. We develop an algorithmic model to solve multi-attribute decision-making (MADM) problems in mF environment using mF Hamacher weighted average operator (mFHWA) and mFHWG operators. They can compensate for the possible asymmetric roles of the attributes that describe the problem. In the end, to prove the validity and feasibility of the proposed work, we give applications for selecting the most affected country regarding human trafficking, selecting health care waste treatment methods and selecting the best company for investment. We also solve practical MADM problems by using ELECTRE-I method, and give a comparative analysis.

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Improving early OSV design robustness by applying ‘Multivariate Big Data Analytics’ on a ship's life cycle

Cited by 16 publications

References 1 publication

An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

A Robust Single-Valued Neutrosophic Soft Aggregation Operators in Multi-Criteria Decision Making

Multi-Attribute Decision-Making Based on m-Polar Fuzzy Hamacher Aggregation Operators

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