scholarly journals Integrating Sustainability in the Quality Assessment of EHEA Institutions: A Hybrid FDEMATEL-ANP-FIS Model

2020 ◽  
Vol 12 (5) ◽  
pp. 1707 ◽  
Author(s):  
Javier Puente ◽  
Isabel Fernandez ◽  
Alberto Gomez ◽  
Paolo Priore
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Quality Assessment ◽  
Conceptual Model ◽  
Fuzzy Inference ◽  
Multicriteria Decision Making ◽  
Analytic Network Process ◽  
Fuzzy Decision Making ◽  
Inference System ◽  
European Higher Education

This paper proposes the design of a conceptual model of quality assessment in European higher education institutions (HEIs) that takes into account some of the critical reflections made by certain authors in the literature regarding standards and guidelines suggested for this purpose by the European Higher Education Area (EHEA). In addition, the evaluation of the conceptual model was carried out by means of the reliable hybrid methodology MCDM-FIS (multicriteria decision making approach–fuzzy inference system) using FDEMATEL and FDANP methods (fuzzy decision-making trial and evaluation laboratory and FDEMATEL-based analytic network process). The choice of these methodologies was justified by the existing interrelationships among the criteria and dimensions of the model and the degree of subjectivity inherent in its evaluation processes. Finally, it is suggested to include sustainability as a determining factor in the university context due to its great relevance in the training of future professionals.

scholarly journals An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Ali Safa Sadiq ◽  
Norsheila Binti Fisal ◽  
Kayhan Zrar Ghafoor ◽  
Jaime Lloret
Keyword(s):  
Decision Making ◽  
Wireless Networks ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Weight Vector ◽  
Point Load ◽  
Fuzzy Decision Making ◽  
Inference System ◽  
Handover Decision ◽  
Seamless Mobility

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.

Multicriteria decision-making in flight route selection

2020 ◽  
Vol 92 (9) ◽  
pp. 1377-1384
Author(s):  
Leszek Rolka ◽  
Alicja Mieszkowicz-Rolka ◽  
Grzegorz Drupka
Keyword(s):  
Decision Making ◽  
Traffic Management ◽  
Fuzzy Inference ◽  
Multicriteria Decision Making ◽  
Optimization Procedure ◽  
Decision Matrix ◽  
Inference System ◽  
Content Type ◽  
Multicriteria Decision ◽  
Flight Route

Purpose This paper aims to present a hybrid logical-arithmetic approach for selecting optimal flight routes. It can be used in the framework of free route airspace (FRA), which is aimed at achieving higher efficiency of air traffic management. Design/methodology/approach At the first stage, an initial subset of flight routes is selected that are promising alternatives with respect to single numerical criteria. At the second stage, a hybrid multicriteria decision model is constructed, consisting of numerical criteria and additional linguistic criteria. At the third stage, the numerical and linguistic criteria are integrated into a crisp decision matrix for determining the final ranking using the technique for order preferences by similarity to an ideal solution (TOPSIS) method. Findings The considered decision-making problem involves different kinds of criteria. Numerical (objective) criteria are given as real numbers. Linguistic (subjective) criteria are expressed with the help of fuzzy linguistic values. In consequence, a (logical) reasoning process prior to performing an (arithmetic) optimization procedure is necessary. Furthermore, a uniform optimization procedure requires a way of combining numerical and linguistic attributes. Practical implications The proposed approach can be applied to solving various multicriteria decision-making problems, where both objective and subjective criteria are taken into account. Originality/value First, a fuzzy information system that includes linguistic condition attributes is constructed. Second, a fuzzy inference system that is necessary for determining the resulting fuzzy criterion “turbulence conditions” for all flight routes is introduced. Finally, a way of combining numerical and linguistic criteria is proposed. This is done by converting values of fuzzy attributes into crisp ones, basing on the preferences of a decision-maker.

scholarly journals IMPORTANCE-PERFORMANCE ANALYSIS BASED BALANCED SCORECARD FOR PERFORMANCE EVALUATION IN HIGHER EDUCATION INSTITUTIONS: AN INTEGRATED FUZZY APPROACH

2020 ◽  
Vol 21 (3) ◽  
pp. 647-678
Author(s):  
Salman Nazari-Shirkouhi ◽  
Saeed Mousakhani ◽  
Mahdokht Tavakoli ◽  
Mohammad Reza Dalvand ◽  
Jonas Šaparauskas ◽  
...  
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Performance Evaluation ◽  
Performance Analysis ◽  
Balanced Scorecard ◽  
Higher Education Institutions ◽  
Analytic Network Process ◽  
Fuzzy Decision Making ◽  
The Balanced Scorecard ◽  
Network Process

Recognizing the state of the universities and disrupting their functions by performance evaluation helps them adopt more appropriate educational, research and institutional policies to conduct a university system. In this paper, the importance of the services provided and the activities of the university are determined by means of the balanced scorecard (BSC) approach, and the performance assessment structure is implemented based on an integrated fuzzy multi-criteria decision making (MCDM) approach. For this purpose, interdependencies between BSC aspects and effective indicators weight are determined by Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) and Fuzzy Analytic Network Process (FANP) methods, respectively. Accordingly, the final weight of the effective indexes on the performance evaluation of university is presented and the educational income is recognized as one of the most important indicators. Finally, the priorities of universities are specified in order to improve the performance and policy making by the importance-performance analysis (IPA). Therefore, the growth of the number of students should be considered as one of the most important stages in improving university performance in the future in order to achieve educational income. Moreover, the guidelines for universities and higher education institutions are presented to identify key factors in implementing and improving performance.

scholarly journals A fuzzy decision making system for building damage map creation using high resolution satellite imagery

2013 ◽  
Vol 13 (2) ◽  
pp. 455-472 ◽  
Author(s):  
H. Rastiveis ◽  
F. Samadzadegan ◽  
P. Reinartz
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Damage Assessment ◽  
Fuzzy Inference ◽  
Earthquake Damage ◽  
Fuzzy Decision Making ◽  
Inference System ◽  
High Resolution Satellite Imagery ◽  
Roof Part ◽  
Earthquake Damage Assessment

Abstract. Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings.

STEREOVISION-BASED FUZZY OBSTACLE AVOIDANCE METHOD

2011 ◽  
Vol 08 (01) ◽  
pp. 169-183 ◽  
Author(s):  
LAZAROS NALPANTIDIS ◽  
ANTONIOS GASTERATOS
Keyword(s):  
Obstacle Avoidance ◽  
Efficient Solution ◽  
Fuzzy Inference ◽  
Autonomous Mobile Robots ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Inference System ◽  
Depth Maps ◽  
Complex Processes ◽  
Stereo Algorithm

This work presents a stereovision-based obstacle avoidance method for autonomous mobile robots. The decision about the direction on each movement step is based on a fuzzy inference system. The proposed method provides an efficient solution that uses a minimum of sensors and avoids computationally complex processes. The only sensor required is a stereo camera. First, a custom stereo algorithm provides reliable depth maps of the environment in frame rates suitable for a robot to move autonomously. Then, a fuzzy decision making algorithm analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on a variety of self-captured outdoor images and the results are presented and discussed.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

Fuzzy-Rule Based Adaptive Data Warehouse

2012 ◽  
Vol 3 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Rajdev Tiwari ◽  
Anubhav Tiwari ◽  
Manu Pratap Singh
Keyword(s):  
Decision Making ◽  
Fuzzy Inference ◽  
Knowledge Workers ◽  
Fuzzy Rule ◽  
Data Warehouses ◽  
Large Reservoir ◽  
Inference System ◽  
Rule Based ◽  
Neuro Fuzzy ◽  
New Generation

Data Warehouses (DWs) are aimed to empower the knowledge workers with information and knowledge which helps them in decision making. Technically, the DW is a large reservoir of integrated data that does not provide the intelligence or the knowledge demanded by users. The burden of data analysis and extraction of information and knowledge from integrated data still lies upon the analyst’s shoulder. The overhead of analysts can be taken off by architecting a new generation data warehouses systems those shall be capable of capturing, organizing and representing knowledge along with the data and information in it. This new generation DW may be called as Knowledge Warehouse (KW) shall exhibit decision making capabilities themselves and can also supplement the Decision Support Systems (DSS) in making decisions quickly and effortlessly. This paper proposes and simulates a fuzzy-rule based adaptive knowledge warehouse with capabilities to learn and represent implicit knowledge by means of adaptive neuro fuzzy inference system (ANFIS).

Lean in higher education

2019 ◽  
Vol 27 (1) ◽  
pp. 82-102 ◽  
Author(s):  
Yigit Kazancoglu ◽  
Yesim Deniz Ozkan-Ozen
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Business School ◽  
Stage Structure ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making ◽  
Stage Model ◽  
Content Type ◽  
Road Map ◽  
Multi Stage

PurposeThis research aims to investigate and define the eight wastes of lean philosophy in higher education institutions (HEIs) by proposing a multi-stage model.Design/methodology/approachThe authors have used a specific multi-criteria decision-making method, fuzzy decision-making trial and evaluation laboratory, to investigate the cause–effect relationships and importance order between criteria for wastes in HEIs. In total, 22 criteria were categorized under eight wastes of lean. The study was implemented in a business school with the participation of faculty members from different departments.FindingsThe results showed that the most important wastes in the business school selected were repeated tasks, unnecessary bureaucracy, errors because of misunderstanding/communication problems, excessive number of academic units and creation of an excessive amount of information. Another important result was that all the sub-wastes of talent were in the causes group, while motion and transportation wastes were in the effect group.Practical implicationsA road map to guide lean transformation for HEIs is proposed with a multi-stage model and potential areas for improvement in HEIs were presented.Originality/valueThis study proposes a multi-stage structure by applying multi-criteria decision-making to HEIs, focussing on wastes from a lean perspective.

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