Search results for: Partial Knowing Support

Authors: Alae El Alami, Mohamed Bahaj

Abstract:

This paper proposes an approach for translating an existing relational database (RDB) schema into ORDB. The transition is done with methods that can extract various functions from a RDB which is based on aggregations, associations between the various tables, and the reflexive relationships. These methods can extract even the inheritance knowing that no process of reverse engineering can know that it is an Inheritance; therefore, our approach exceeded all of the previous studies made for ​​the transition from RDB to ORDB. In summation, the creation of the New Data Model (NDM) that stocks the RDB in a form of a structured table, and from the NDM we create our navigational model in order to simplify the implementation object from which we develop our different types. Through these types we precede to the last step, the creation of tables.

The step mentioned above does not require any human interference. All this is done automatically, and a prototype has already been created which proves the effectiveness of this approach.

Keywords: Relational databases, Object-relational databases, Semantic enrichment.

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Authors: M.R.Isvandzibaei, E.Bidokh, M.R.Alinaghizadeh, A.Nasirian, A.Moarrefzadeh

Abstract:

In this paper a study on the vibration of thin cylindrical shells with ring supports and made of functionally graded materials (FGMs) composed of stainless steel and nickel is presented. Material properties vary along the thickness direction of the shell according to volume fraction power law. The cylindrical shells have ring supports which are arbitrarily placed along the shell and impose zero lateral deflections. The study is carried out based on third order shear deformation shell theory (T.S.D.T). The analysis is carried out using Hamilton-s principle. The governing equations of motion of FGM cylindrical shells are derived based on shear deformation theory. Results are presented on the frequency characteristics, influence of ring support position and the influence of boundary conditions. The present analysis is validated by comparing results with those available in the literature.

Keywords: Vibration, FGM, Cylindrical shell, Hamilton'sprinciple, Ring support.

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Authors: B. Gangloff, N. Malleh

Abstract:

Well-being at work has many positive aspects. Our general hypothesis is that employees who feel well-being at work will be positively valued by their superiors, and that this positive value, which evokes the concept of social norms, allows us to assign to well-being at work a normative status. Three populations (line managers, students destined to become human resource managers, and employees) responded to a well-being questionnaire. Managers had to indicate, for each item, if they appreciated (or not) an employee feeling the well-being presented in the item; students had to indicate which items an employee should check if s/he wants to be positively (versus negatively) appreciated by his/her superior; and employees had to indicate to what degree each item corresponded to the well-being they used to feel. Three hypotheses are developed and confirmed: Managers positively value employees feeling some sense of well-being; students are aware of this positivity; spontaneously employees show a state of well-being, which means, knowing that spontaneous self-presentation is often produced by social desirability, that employees are aware of the well-being positivity. These data are discussed under a conceptual and applied angle.

Keywords: Normativity, well-being at work, organization, evaluation.

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Authors: Mohammad Taghi Darvishi, Maliheh Najafi, Mohammad Najafi

Abstract:

In this work, we obtain some analytic solutions for the (3+1)-dimensional breaking soliton after obtaining its Hirota-s bilinear form. Our calculations show that, three-wave method is very easy and straightforward to solve nonlinear partial differential equations.

Keywords: (3+1)-dimensional breaking soliton equation, Hirota'sbilinear form.

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Authors: Norziana Aminudin, Titik Khawa Abdul Rahman, Ismail Musirin

Abstract:

One of the factors to maintain system survivability is the adequate reactive power support to the system. Lack of reactive power support may cause undesirable voltage decay leading to total system instability. Thus, appropriate reactive power support scheme should be arranged in order to maintain system stability. The strength of a system capacity is normally denoted as system loadability. This paper presents the enhancement of system loadability through optimal reactive power planning technique using a newly developed optimization technique, termed as Multiagent Immune Evolutionary Programming (MAIEP). The concept of MAIEP is developed based on the combination of Multiagent System (MAS), Artificial Immune System (AIS) and Evolutionary Programming (EP). In realizing the effectiveness of the proposed technique, validation is conducted on the IEEE-26-Bus Reliability Test System. The results obtained from pre-optimization and post-optimization process were compared which eventually revealed the merit of MAIEP.

Keywords: Load margin, MAIEP, Maximum loading point, ORPP.

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Authors: Ehsan Amid, Sina Rezaei Aghdam, Hamidreza Amindavar

Abstract:

Steel surface defect detection is essentially one of pattern recognition problems. Support Vector Machines (SVMs) are known as one of the most proper classifiers in this application. In this paper, we introduce a more accurate classification method by using SVMs as our final classifier of the inspection system. In this scheme, multiclass classification task is performed based on the "one-againstone" method and different kernels are utilized for each pair of the classes in multiclass classification of the different defects. In the proposed system, a decision tree is employed in the first stage for two-class classification of the steel surfaces to "defect" and "non-defect", in order to decrease the time complexity. Based on the experimental results, generated from over one thousand images, the proposed multiclass classification scheme is more accurate than the conventional methods and the overall system yields a sufficient performance which can meet the requirements in steel manufacturing.

Keywords: Steel Surface Defect Detection, Support Vector Machines, Kernel Methods.

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Authors: Ji-il Park, Min Kyu Yu, Jong-woo Lee, Sam-hyeon Yoo

Abstract:

The purpose of this research is to analyze the gait strategy between the normal and loaded gait. To this end, five male participants satisfied two conditions: the normal and loaded gait (backpack load 25.2 kg). As expected, results showed that additional loads elicited not a proportional increase in vertical and shear ground reaction force (GRF) parameters but also increase of the impulse, momentum and mechanical work. However, in case of the loaded gait, the time duration of the double support phase was increased unexpectedly. It is because the double support phase which is more stable than the single support phase can reduce instability of the loaded gait. Also, the directions of the pre-collision and after-collision were moved upward and downward compared to the normal gait. As a result, regardless of the additional backpack load, the impulse-momentum diagram during the step-to-step transition was maintained such as the normal gait. It means that human walk efficiently to keep stability and minimize total net works in case of the loaded gait.

Keywords: Normal gait, loaded gait, impulse, collision, gait analysis, mechanical work, backpack load.

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Authors: Zineddine Bouyahiaoui, Rabah Haoui

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The aim of this work is to analyze a flow around the axisymmetric blunt body taken into account the chemical and vibrational nonequilibrium flow. This work concerns the entry of spacecraft in the atmosphere of the planet Mars. Since the equations involved are non-linear partial derivatives, the volume method is the only way to solve this problem. The choice of the mesh and the CFL is a condition for the convergence to have the stationary solution.

Keywords: Hypersonic flow, nonequilibrium flow, shock wave, blunt body.

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Authors: Mohd A. Mezher, Maysam F. Abbod

Abstract:

Genetic Folding (GF) a new class of EA named as is introduced for the first time. It is based on chromosomes composed of floating genes structurally organized in a parent form and separated by dots. Although, the genotype/phenotype system of GF generates a kernel expression, which is the objective function of superior classifier. In this work the question of the satisfying mapping-s rules in evolving populations is addressed by analyzing populations undergoing either Mercer-s or none Mercer-s rule. The results presented here show that populations undergoing Mercer-s rules improve practically models selection of Support Vector Machine (SVM). The experiment is trained multi-classification problem and tested on nonlinear Ionosphere dataset. The target of this paper is to answer the question of evolving Mercer-s rule in SVM addressed using either genetic folding satisfied kernel-s rules or not applied to complicated domains and problems.

Keywords: Genetic Folding, GF, Evolutionary Algorithms, Support Vector Machine, Genetic Algorithm, Genetic Programming, Multi-Classification, Mercer's Rules

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Authors: Nnamdi I. Nwulu, Shola G. Oroja

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It has become crucial over the years for nations to improve their credit scoring methods and techniques in light of the increasing volatility of the global economy. Statistical methods or tools have been the favoured means for this; however artificial intelligence or soft computing based techniques are becoming increasingly preferred due to their proficient and precise nature and relative simplicity. This work presents a comparison between Support Vector Machines and Artificial Neural Networks two popular soft computing models when applied to credit scoring. Amidst the different criteria-s that can be used for comparisons; accuracy, computational complexity and processing times are the selected criteria used to evaluate both models. Furthermore the German credit scoring dataset which is a real world dataset is used to train and test both developed models. Experimental results obtained from our study suggest that although both soft computing models could be used with a high degree of accuracy, Artificial Neural Networks deliver better results than Support Vector Machines.

Keywords: Artificial Neural Networks, Credit Scoring, SoftComputing Models, Support Vector Machines.

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Authors: R. Tur, A. Yardımcı

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Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.

Keywords: Fuzzy logic, decision support systems, construction industry.

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Authors: Fouzia Alsabah Shaikh, Anjali Ghosh

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The present study was done primarily to address two major research gaps: firstly, development of an empirical measure of life meaningfulness for substance users and secondly, to determine the psychosocial determinants of life meaningfulness among the substance users. The study is classified into two phases: the first phase which dealt with development of Life Meaningfulness Scale and the second phase which examined the relationship between life meaningfulness and social support, abstinence self efficacy and depression. Both qualitative and quantitative approaches were used for framing items. A Principal Component Analysis yielded three components: Overall Goal Directedness, Striving for healthy lifestyle and Concern for loved ones which collectively accounted for 42.06% of the total variance. The scale and its subscales were also found to be highly reliable. Multiple regression analyses in the second phase of the study revealed that social support and abstinence self efficacy significantly predicted life meaningfulness among 48 recovering inmates of a de-addiction center while level of depression failed to predict life meaningfulness.

Keywords: Perceived Life meaningfulness, Social Support, Abstinence Self Efficacy, Depression, Substance Use.

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: Corporate credit rating prediction, feature selection, genetic algorithms, instance selection, multiclass support vector machines.

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Authors: M. Saleh, H. Bevrani

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This paper quantifies the impact of providing a shortterm excess active power support of a variable speed wind turbine (VSWT) and effect of super magnetic energy storage (SMES) unit on frequency control, particularly temporary minimum frequency (TMF) term. To demonstrate the effect of these factors on the power system frequency, a three-area power system is considered as a test system.

Keywords: Frequency regulation, inertia, primary frequencycontrol, rotational energy, variable speed wind turbine.

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Authors: Arne Koschel

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This article discusses event monitoring options for heterogeneous event sources as they are given in nowadays heterogeneous distributed information systems. It follows the central assumption, that a fully generic event monitoring solution cannot provide complete support for event monitoring; instead, event source specific semantics such as certain event types or support for certain event monitoring techniques have to be taken into account. Following from this, the core result of the work presented here is the extension of a configurable event monitoring (Web) service for a variety of event sources. A service approach allows us to trade genericity for the exploitation of source specific characteristics. It thus delivers results for the areas of SOA, Web services, CEP and EDA.

Keywords: Event monitoring, ECA, CEP, SOA, Web services.

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

Abstract:

In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: Anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines.

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Authors: Seifedine Kadry

Abstract:

In this article, our objective is the analysis of the resolution of non-linear differential systems by combining Newton and Continuation (N-C) method. The iterative numerical methods converge where the initial condition is chosen close to the exact solution. The question of choosing the initial condition is answered by N-C method.

Keywords: Continuation Method, Newton Method, Finite Difference Method, Numerical Analysis and Non-Linear partial Differential Equation.

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Authors: Ashiquer Rahman

Abstract:

The cutting edge knowledge mediation system called ‘ePLANETe’ provides a framework for building knowledge, tools, and methods for education, research, and sustainable practices, as well as the deliberative assessment support for Higher Education, Research Institutions, and elsewhere e.g., the collaborative learning and research on sustainability and biodiversity issues of territorial development sectors. The paper is to present the analytical perspective of the ‘ePLANETe’ concept and functionalities as an experimental platform for contributing to sustainability assessment. Now the ‘ePLANETe’ can be seen as experimentation of the challenges of “ICT for Green”. The digital technologies of ‘ePLANETe’ are exploited (i) to facilitate collaborative research, learning tools, and knowledge for sustainability challenges, and (ii) as deliberation support tools in pursuing of sustainability performance and practices in territorial governance, public policy, and business strategy, as well as in the higher education sectors itself. The paper investigates the dealing capacity of qualitative and quantitative assessment of agriculture sustainability through the stakeholder-based integrated assessment. Specifically, this paper focuses on integrating system methodologies with Deliberation Support Tools (DST) and INTEGRAAL method for collective assessment and decision-making in implementing regional plans. The report aims to identify the effective knowledge and tools to enable deliberations methodologies regarding practices on the sustainability of agriculture and biodiversity issues, societal responsibilities, and regional planning, concentrating on the question: “How to effectively mobilize resources (knowledge, tools, and methods) from different sources and at different scales regarding on agriculture and biodiversity issues to address sustainability challenges” that will create the scope for qualitative and quantitative assessments of sustainability as a new landmark of the agriculture sector.

Keywords: Biodiversity, Deliberation Support Tools, INTEGRAAL, stakeholder.

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Authors: Rajneesh Rani, Renu Dhir, G. S. Lehal

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Script identification is one of the challenging steps in the development of optical character recognition system for bilingual or multilingual documents. In this paper an attempt is made for identification of English numerals at word level from Punjabi documents by using Gabor features. The support vector machine (SVM) classifier with five fold cross validation is used to classify the word images. The results obtained are quite encouraging. Average accuracy with RBF kernel, Polynomial and Linear Kernel functions comes out to be greater than 99%.

Keywords: Script identification, gabor features, support vector machines.

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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Authors: Matthew Dickinson

Abstract:

A core/trunk exoskeleton design has been produced that is aimed to assist the raise to stand motion. A 3D model was produced to examine the use of additive manufacturing as a core method for producing structural components for the exoskeleton presented. The two materials that were modelled for this simulation work were Polylatic acid (PLA) and polyethylene terephthalate with carbon (PET-C), and the central spinal cord of the design being Nitrile rubber. The aim of this study was to examine the use of 3D printed materials as the main skeletal structure to support the core of a human when moving raising from a resting position. The objective in this work was to identify if the 3D printable materials could be offered as an equivalent alternative to conventional more expensive materials, thus allow for greater access for production for home maintenance. A maximum load of lift force was calculated, and this was incrementally reduced to study the effects on the material. The results showed a total number of 8 simulations were run to study the core in conditions with no muscular support through to 90% of operational support. The study presents work in the form of a core/trunk exoskeleton that presents 3D printing as a possible alternative to conventional manufacturing.

Keywords: 3D printing, Exo-Skeleton, PLA, PETC.

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.

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Authors: A. Bahar Ganiyeva, M. Sabuhi Tanriverdiyev

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The article analyzes state support and policy mechanisms aimed at driving tourism as one of the vibrant and rapidly developing economies. State programs and long-range strategic roadmaps and previous programs execution, results and their impact on the particular countries economy have been raised during the research. This theme provides a useful framework for discussions with a wider range of stakeholders as the implications arising are of importance both for academics and practitioners engaged in hospitality and tourism development and research. The impact that tourism has on sustainable regional development in emerging markets is highly substantial. For Azerbaijan, Turkey, Georgia, and Russia, with their rich natural resources and cultural heritage, tourism can be an important basis for economic expansion, and a way to form an acceptable image of the countries as safe, open, hospitable, and complex.

Keywords: Sustainable tourism, hospitality, destination, strategic roadmap, tourism, economy, growth, state support, mechanism, policy formation, state program.

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Authors: Gehad S. Kaseb, Mona F. Ahmed

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Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets, Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-ATSD), which are publicly available for academic use. The results show that the classification accuracy approaches 86%.

Keywords: Arabic, hybrid classification, sentiment analysis, tweets.

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Authors: Hamdi Melih Saraoğlu, Muhlis Yıldırım, Abdurrahman Özbeyaz, Feyzullah Temurtas

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In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.

Keywords: Palm perspiration, Diabetes, Support Vector Machine, Classification.

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Authors: Mohamad K. Hasan, Hameed Al-Qaheri

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Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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Authors: Tsung-Hsien Yu, Ya-Hsuan Chou, Ming-Wei Chen, Chi-Ming Chen, Yi-Hsuan Li

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Observations and long-term trends indicate that climate change impacts would be significant and affects Taiwan directly and severely. Taiwan engages not only in mitigation, but also in adaptation. However, there are cognitive gaps on adaptation between government and populace. Besides, a vision of zero-carbon and renewable energy 100% will be adopted in future. Therefore, the objectives of this article are to 1) hold a National Forum for knowing differences between the strategies of zero-carbon and renewable energy 100% and cognitions of general populace, and 2) plan a clear roadmap for the vision, strategy, and measures. In this forum, we set 5 group topics, 5 presumed themes, and issues mentioned review for concluding the critical issues. Finally, there are 4 strategies and 14 critical issues which correlate with the vision and strategy of government and the cognition of the general populace.

Keywords: Cognitive gap, world café, renewable energy, zero-carbon.

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Authors: Khaled Abduesslam. M, Mohammed Ali, Basher H Alsdai, Muhammad Nizam, Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New- England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, Least Squares Support Vector Machine, Learning Vector Quantization, Voltage Collapse.

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Authors: L. Achou, A. Doghmane

Abstract:

Elastic performances, as an essential property of nanowires (NWs), play a significant role in the design and fabrication of modern nanodevices. In this paper, our interest is focused on ZnO NWs to investigate wire diameter (D_wire ≤ 400 nm) effects on elastic properties. The plotted data reveal that a strong size dependence of the elastic constants exists when the wire diameter is smaller than ~ 100 nm. For larger diameters (D_wire > 100 nm), these ones approach their corresponding bulk values. To enrich this study, we make use of the scanning acoustic microscopy simulation technique. The calculation methodology consists of several steps: determination of longitudinal and transverse wave velocities, calculation of refection coefficients, calculation of acoustic signatures and Rayleigh velocity determination. Quantitatively, it was found that changes in ZnO diameters over the ranges 1 nm ≤ D_wire ≤ 100 nm lead to similar exponential variations, for all elastic parameters, of the from: A = a + b exp(-D_wire/c) where a, b, and c are characteristic constants of a given parameter. The developed relation can be used to predict elastic properties of such NW by just knowing its diameter and vice versa.

Keywords: Elastic properties, nanowires, semiconductors, ZnO.

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Authors: Jin-Bao Zhao, Wei Deng

Abstract:

This paper aims at developing a multilevel fuzzy decision support model for urban rail transit planning schemes in China under the background that China is presently experiencing an unprecedented construction of urban rail transit. In this study, an appropriate model using multilevel fuzzy comprehensive evaluation method is developed. In the decision process, the followings are considered as the influential objectives: traveler attraction, environment protection, project feasibility and operation. In addition, consistent matrix analysis method is used to determine the weights between objectives and the weights between the objectives- sub-indictors, which reduces the work caused by repeated establishment of the decision matrix on the basis of ensuring the consistency of decision matrix. The application results show that multilevel fuzzy decision model can perfectly deal with the multivariable and multilevel decision process, which is particularly useful in the resolution of multilevel decision-making problem of urban rail transit planning schemes.

Keywords: Urban rail transit, planning schemes, multilevel fuzzy decision support model, consistent matrix analysis

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