A fuzzy-clustering based approach for MADM handover in 5G ultra-dense networks

As the global data traffic has significantly increased in the recent year, the ultra-dense deployment of cellular networks (UDN) is being proposed as one of the key technologies in the fifth-generation mobile communications system (5G) to provide a much higher density of radio resource. The densification of small base stations could introduce much higher inter-cell interference and lead user to meet the edge of coverage more frequently. As the current handover scheme was originally proposed for macro BS, it could cause serious handover issues in UDN i.e. ping-pong handover, handover failures and frequent handover. In order to address these handover challenges and provide a high quality of service (QoS) to the user in UDN. This paper proposed a novel handover scheme, which integrates both advantages of fuzzy logic and multiple attributes decision algorithms (MADM) to ensure handover process be triggered at the right time and connection be switched to the optimal neighbouring BS. To further enhance the performance of the proposed scheme, this paper also adopts the subtractive clustering technique by using historical data to define the optimal membership functions within the fuzzy system. Performance results show that the proposed handover scheme outperforms traditional approaches and can significantly minimise the number of handovers and the ping-pong handover while maintaining QoS at a relatively high level. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

Systematic review of decision making algorithms in extended neutrosophic sets

The Neutrosophic set (NS) has grasped concentration by its ability for handling indeterminate, uncertain, incomplete, and inconsistent information encountered in daily life. Recently, there have been various extensions of the NS, such as single valued neutrosophic sets (SVNSs), Interval neutrosophic sets (INSs), bipolar neutrosophic sets (BNSs), Refined Neutrosophic Sets (RNSs), and triangular fuzzy number neutrosophic set (TFNNs). This paper contains an extended overview of the concept of NS as well as several instances and extensions of this model that have been introduced in the last decade, and have had a significant impact in literature. Theoretical and mathematical properties of NS and their counterparts are discussed in this paper as well. Neutrosophic-set-driven decision making algorithms are also overviewed in detail

Fuzzy Interval-Valued Multi Criteria Based Decision Making for Ranking Features in Multi-Modal 3D Face Recognition

Soodamani Ramalingam, 'Fuzzy interval-valued multi criteria based decision making for ranking features in multi-modal 3D face recognition', Fuzzy Sets and Systems, In Press version available online 13 June 2017. This is an Open Access paper, made available under the Creative Commons license CC BY 4.0 https://creativecommons.org/licenses/by/4.0/This paper describes an application of multi-criteria decision making (MCDM) for multi-modal fusion of features in a 3D face recognition system. A decision making process is outlined that is based on the performance of multi-modal features in a face recognition task involving a set of 3D face databases. In particular, the fuzzy interval valued MCDM technique called TOPSIS is applied for ranking and deciding on the best choice of multi-modal features at the decision stage. It provides a formal mechanism of benchmarking their performances against a set of criteria. The technique demonstrates its ability in scaling up the multi-modal features.Peer reviewedProo

RE-EVALUATING SUSTAINABILITY OF MICROFINANCE INSTITUTIONS BY USING TOPSIS

Purpose: The measurement of sustainability for microfinance institutions (MFIs) has been a serious problem for both practitioners and researchers over the last few decades. A multicriteria decision-making approach is used to develop an index that measures the sustainability of microfinance institutions based on the double bottom line. Methodology: The sustainability score of MFIs operating in Pakistan for the year 2006-2015 is measured using the technique for order preference by similarity to ideal solution (TOPSIS). During the assessment, equal weights are assigned to all indicators of sustainability. Additionally, a hypothetical organization was assigned the industry threshold to generate composite scores using TOPSIS. Later, sustainability levels of individual MFIs were compared with this industry threshold. Findings: Microfinance institutions that attain higher financial sustainability and positive outreach are ranked high. The result shows that the threshold sustainability level of the microfinance sector in Pakistan from 2006-2015 was 23.52, 26.31, 23.80, 45.83, 45.83, 66.67, 77.77, 91.60, and 88.88 percent respectively. Although the sustainability level in 2015 decreases with respect to 2014, still the overall growth of the sector is remarkable. Practical implications: The results obtained from TOPSIS for evaluating the sustainability of MFIs under the double bottom line highlight its practical applicability. MFIs are under immense pressure by regulatory bodies, investors, donors, and financial experts to achieve sustainability. This index would help MFIs to track progress and improve their sustainability. Novelty/Originality: This study is the first of its kind to determine the sustainability of MFI by using all the four indicators of sustainability, including financial self-sufficiency, operational self-sufficiency, depth of outreach and breadth of outreach. Existing sustainability indicators does not provide the threshold level of sustainability. Instead, they provide a ranking of MFIs from top to bottom only. This study is novel to identify whether MFIs have met or failed to achieve sustainability by providing the threshold level

Application of time-cost-quality-risk trade-off model in magnetic resonance imaging machine installation project

Effective project planning in Magnetic Resonance Imaging (MRI) machine installation takes into consideration several factors including Time, Cost, Quality and Risk which are essential but conflicting factors that affect projects. These critical factors should be optimized in all projects especially those in Low and Medium Income Countries (LMIC) with limited resources and inadequate investment in medical facilities and equipment. The main objective of this study was to develop an optimization model for fuzzy Time-Cost-Quality-Risk Trade-off (TCQRT) problem for MRI machine installation project. The model was solved by Multiobjective Genetic Algorithm (MOGA) and the solutions ranked using the Technique for the Order of Preferences by Similarity to Ideal Solution (TOPSIS). The results indicate a trade-off relationship exists among time, cost, quality and risks.Keywords: Time-Cost-Quality Trade-off Model, Magnetic Resonance Imaging, Multiobjective Genetic Algorith

STUDY TOWARDS THE TIME-BASED MCDA RANKING ANALYSIS – A SUPPLIER SELECTION CASE STUDY

Decision-making processes increasingly use models based on various methods to ensure professional analysis and evaluation of the considered alternatives. However, the abundance of these methods makes it difficult to choose the proper method to solve a given problem. Also, it is worth noting whether different results can be obtained using different methods within a single decision problem. In this paper, we used three selected Multi-Criteria Decision Analysis (MCDA) methods called COMET, TOPSIS, and SPOTIS in order to examine how the obtained rankings vary. The selection of material suppliers was taken into consideration. The equal weights, entropy and standard deviation methods were used to determine the weights for criteria. Final preferences values were then compared with the WS similarity coefficient and weighted Spearman correlation coefficient to check the similarity of the received rankings. It was noticed that in the given problem, all of the methods provide highly correlated results, and the obtained positional rankings are not significantly different. However, practical conclusions indicate the need to look for improved solutions in the correct and accurate assessment of suppliers in a given period

Primena modifikovanog rasplinutog TOPSIS metoda za višekriterijumske odluke u građevinarstvu

In this paper is presented and applied one fuzzy TOPSIS method for the multicriteria ranking of objects for reconstruction and maintenance. At the beginning is given short review on the genesis and development of this method and described a TOPSIS procedure with crisp input data that constitute a decision matrix and weights of criteria. This procedure is illustrated by one simple numerical example. The necessity of presentation of these parameters as triangular fuzzy numbers due to impossibility of their precise determination or assessment in the practice. The exact expressions for the determination of these products of the decision matrix and weights coefficients as triangular fuzzy numbers, that authors of this paper are derived earlier, are given in the paper. For every alternative (the object) these parameters are assumed as random fuzzy numbers for which are determined generalised expected values, variances and standard deviations. From the normalised matrix of the expected values are determined expected ideal positive and ideal negative values. For every alternative are determined generalized expected distances and relative closenesses to the ideal positive and ideal negative solution. The ranking of alternatives is performed according to these values. Mathematical expressions for coefficients of investments distribution on the alternatives (objects) are proposed in the work. One example of ranking of the bridge structures according to the risk is given at the end of the work and formulated corresponding conclusions.U ovom radu predlaže se i primenjuje jedan modifikovani rasplinuti TOPSIS metod za višekriterijumsko rangiranje objekata za rekonstrukciju i održavanje. Na početku se daje kratak osvrt na nastanak i razvoj ovog metoda i opisuje se TOPSIS procedura s fiksnim (nerasplinutim) ulaznim podacima koji sačinjavaju matricu odlučivanja i težinske koeficijente kriterijuma. Ova procedura se ilustruje jednim jednostavnim brojčanim primerom. Objašnjava se neophodnost prikazivanja ovih parametara - kao trougaonih rasplinutih brojeva - zbog nemogućnosti njihovog preciznog određivanja ili procenjivanja u praksi. U radu se daju tačni izrazi, koje su autori ranije izveli, za određivanje proizvoda elemenata matrice odlučivanja i težinskih koeficijenata kao trougaonih rasplinutih brojeva. Ovi parametri za svaku alternativu (objekat) tretiraju se kao slučajne rasplinute veličine, za koje se određuju tačne generalisane očekivane vrednosti, varijanse i standardne devijacije. Iz normalizovane matrice očekivanih vrednosti određuju se očekivana idealna pozitivna i očekivana idealna negativna rešenja. Za svaku alternativu određuju se generalisane očekivane distance i relativne bliskosti ovim rešenjima, kao i odgovarajuće varijanse i koeficijenti varijacije. Alternative se rangiraju prema ovim vrednostima. U radu se predlažu izrazi za sračunavanje koeficijenta raspodele investicionih sredstava na (alternative) objekte. Na kraju, dat je jedan primer rangiranja mostovskih konstrukcija u odnosu na rizik i formulisani su odgovarajući zaključci

Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: A multicriteria framework

The number of people with dementia (PwD) is increasing dramatically. PwD exhibit impairments of reasoning, memory, and thought that require some form of self‐management intervention to support the completion of everyday activities while maintaining a level of independence. To address this need, efforts have been directed to the development of assistive technology solutions, which may provide an opportunity to alleviate the burden faced by the PwD and their carers. Nevertheless, uptake of such solutions has been limited. It is therefore necessary to use classifiers to discriminate between adopters and nonadopters of these technologies in order to avoid cost overruns and potential negative effects on quality of life. As multiple classification algorithms have been developed, choosing the most suitable classifier has become a critical step in technology adoption. To select the most appropriate classifier, a set of criteria from various domains need to be taken into account by decision makers. In addition, it is crucial to define the most appropriate multicriteria decision‐making approach for the modelling of technology adoption. Considering the above‐mentioned aspects, this paper presents the integration of a five‐phase methodology based on the Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution to determine the most suitable classifier for supporting assistive technology adoption studies. Fuzzy Analytic Hierarchy Process is used to determine the relative weights of criteria and subcriteria under uncertainty and Technique for Order of Preference by Similarity to Ideal Solution is applied to rank the classifier alternatives. A case study considering a mobile‐based self‐management and reminding solution for PwD is described to validate the proposed approach. The results revealed that the best classifier was k‐nearest‐neighbour with a closeness coefficient of 0.804, and the most important criterion when selecting classifiers is scalability. The paper also discusses the strengths and weaknesses of each algorithm that should be addressed in future research