Search results for: Markov decision processes (MDPs)

Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

Abstract:

This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: Flexible job shop scheduling, Decision tree, Priority rules, Case study.

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Authors: Turgay Temel, John Hallam

Abstract:

A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.

Keywords: Classification, neuro-spike coding, parametricmodel, Gaussian mixture with EM algorithm, sequential decision.

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Authors: Randa Ibrahim Elanwar, Mohsen Rashwan, Samia Mashali

Abstract:

In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.

Keywords: Arabic, Hidden Markov Models, online handwriting, word segmentation

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Authors: Yasmin Mohd Yacob, Harsa A. Mat Sakim, Nor Ashidi Mat Isa

Abstract:

Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.

Keywords: Feature ranking, decision tree, hierarchical cluster, Manhattan distance.

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Authors: Reza Ebrahimpour, Samaneh Hamedi

Abstract:

Classifier fusion may generate more accurate classification than each of the basic classifiers. Fusion is often based on fixed combination rules like the product, average etc. This paper presents decision templates as classifier fusion method for the recognition of the handwritten English and Farsi numerals (1-9). The process involves extracting a feature vector on well-known image databases. The extracted feature vector is fed to multiple classifier fusion. A set of experiments were conducted to compare decision templates (DTs) with some combination rules. Results from decision templates conclude 97.99% and 97.28% for Farsi and English handwritten digits.

Keywords: Decision templates, multi-layer perceptron, characteristics Loci, principle component analysis (PCA).

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Authors: Yang Bao, LuJing Zhang

Abstract:

Typical Intelligent Decision Support System is 4-based, its design composes of Data Warehouse, Online Analytical Processing, Data Mining and Decision Supporting based on models, which is called Decision Support System Based on Data Warehouse (DSSBDW). This way takes ETL,OLAP and DM as its implementing means, and integrates traditional model-driving DSS and data-driving DSS into a whole. For this kind of problem, this paper analyzes the DSSBDW architecture and DW model, and discusses the following key issues: ETL designing and Realization; metadata managing technology using XML; SQL implementing, optimizing performance, data mapping in OLAP; lastly, it illustrates the designing principle and method of DW in DSSBDW.

Keywords: Decision Support System, Data Warehouse, Data Mining.

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Authors: Jorge Cardoso

Abstract:

Workflow Management Systems (WfMS) alloworganizations to streamline and automate business processes and reengineer their structure. One important requirement for this type of system is the management and computation of the Quality of Service(QoS) of processes and workflows. Currently, a range of Web processes and workflow languages exist. Each language can be characterized by the set of patterns they support. Developing andimplementing a suitable and generic algorithm to compute the QoSof processes that have been designed using different languages is a difficult task. This is because some patterns are specific to particular process languages and new patterns may be introduced in future versions of a language. In this paper, we describe an adaptive algorithm implemented to cope with these two problems. The algorithm is called adaptive since it can be dynamically changed as the patterns of a process language also change.

Keywords: quality of service, web processes, workflows, web services

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Authors: M. Satya Sai Ram, P. Siddaiah, M. Madhavi Latha

Abstract:

This paper investigates the performance of a speech recognizer in an interactive voice response system for various coded speech signals, coded by using a vector quantization technique namely Multi Switched Split Vector Quantization Technique. The process of recognizing the coded output can be used in Voice banking application. The recognition technique used for the recognition of the coded speech signals is the Hidden Markov Model technique. The spectral distortion performance, computational complexity, and memory requirements of Multi Switched Split Vector Quantization Technique and the performance of the speech recognizer at various bit rates have been computed. From results it is found that the speech recognizer is showing better performance at 24 bits/frame and it is found that the percentage of recognition is being varied from 100% to 93.33% for various bit rates.

Keywords: Linear predictive coding, Speech Recognition, Voice banking, Multi Switched Split Vector Quantization, Hidden Markov Model, Linear Predictive Coefficients.

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Authors: C. Ardil

Abstract:

This paper presents architectural acoustic modeling to estimate reverberation time in room acoustic design using multiple criteria decision making analysis. First, fundamental decision criteria were determined to evaluate the reverberation time in the room acoustic design problem. Then, the proposed model was applied to a practical decision problem to evaluate and select the optimal room acoustic design model. Finally, the optimal acoustic design of the rooms was analyzed and ranked using a multiple criteria decision making analysis method.

Keywords: Architectural acoustics, room acoustics, architectural acoustic modeling, reverberation time, room acoustic design, multiple criteria decision making analysis, decision analysis, MCDMA

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Authors: C. Ardil

Abstract:

This paper introduces a new method for multiplecriteria decision making (MCDM) that avoids order reversal and ensures consistency in decision-making. The proposed method involves range targeting of benefit and cost criteria vectors for range normalization of the initial decision matrix. The Reference Linear Combination (RLC) is used to avoid the rank reversal problem. The preference order generated from the target score matrix does not require relative comparisons between alternatives but relies on a chosen reference solution point after transforming the original decision matrix into an MCDM problem by specifying the minimum and maximum bounds of each criterion. The efficiency and applicability of the proposed RLC method were demonstrated in the selection of commercial passenger aircraft. 

Keywords: Aircraft selection, reference linear combination (RLC), multiple criteria decision-making, MCDM

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Authors: Wided Guezguez, Nahla Ben Amor

Abstract:

This paper proposes a new decision making approch based on quantitative possibilistic influence diagrams which are extension of standard influence diagrams in the possibilistic framework. We will in particular treat the case where several expert opinions relative to value nodes are available. An initial expert assigns confidence degrees to other experts and fixes a similarity threshold that provided possibility distributions should respect. To illustrate our approach an evaluation algorithm for these multi-source possibilistic influence diagrams will also be proposed.

Keywords: influnece diagram, decision making, graphical decision models, influence diagrams, possibility theory.

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Authors: C. Ardil

Abstract:

The decision to select an unmanned combat aircraft is complicated since several options and conflicting criteria must be considered at simultaneously. When making multiple criteria decision, it is important to consider the selected evaluation criteria, including priceability, payloadability, stealthability, speedability , and survivability. The fundamental goal of the study is to select the best unmanned combat aircraft by taking these evaluation criteria into account. The optimal aircraft was chosen using the fuzzy proximity measure method, which enables decision-makers to designate preferences as standard fuzzy set numbers during the multiple criteria decision-making process. To assess the applicability of the proposed approach, a numerical example is provided. Finally, by comparing determined unmanned combat aircraft, the proposed method produced a successful application, and the best aircraft was selected.

Keywords: standard fuzzy sets (SFS), unmanned combat aircraft selection, multiple criteria decision making (MCDM), multiple criteria group decision making (MCGDM), proximity measure method (PMM)

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Authors: Mehdi Kheradmand, Mehdi Azhdary Moghaddam, Abdolreza Zahiri, Khalil Ghorbani

Abstract:

This research compares results of major methods of determining the flow discharge using experimental relationships with results from the M5 decision tree model in meandering compound sections in several laboratory channels. It was found that the M5 decision tree model enjoyed greater accuracy of statistical parameters compared to methods to the said methods. This suggested that the M5 decision tree model has highly improved the calculated accuracy of the flow discharge in meandering compound channels.

Keywords: Stage-discharge relationship, M5 decision tree model, compound section, meandering compound channel.

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Authors: D. Pérez, M. M. E. Alemany

Abstract:

In this work, a framework to model the Supply Chain (SC) Collaborative Planning (CP) process is proposed. The main contributions of this framework concern 1) the presentation of the decision view, the most important one due to the characteristics of the process, jointly within the physical, organisation and information views, and 2) the simultaneous consideration of the spatial and temporal integration among the different supply chain decision centres. This framework provides the basis for a realistic and integrated perspective of the supply chain collaborative planning process and also the analytical modeling of each of its decisional activities.

Keywords: Collaborative Planning, Decision View, Distributed Decision-Making, Framework.

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Authors: Abderrahmane Amrouche, Jean Michel Rouvaen

Abstract:

In this paper we present an efficient system for independent speaker speech recognition based on neural network approach. The proposed architecture comprises two phases: a preprocessing phase which consists in segmental normalization and features extraction and a classification phase which uses neural networks based on nonparametric density estimation namely the general regression neural network (GRNN). The relative performances of the proposed model are compared to the similar recognition systems based on the Multilayer Perceptron (MLP), the Recurrent Neural Network (RNN) and the well known Discrete Hidden Markov Model (HMM-VQ) that we have achieved also. Experimental results obtained with Arabic digits have shown that the use of nonparametric density estimation with an appropriate smoothing factor (spread) improves the generalization power of the neural network. The word error rate (WER) is reduced significantly over the baseline HMM method. GRNN computation is a successful alternative to the other neural network and DHMM.

Keywords: Speech Recognition, General Regression NeuralNetwork, Hidden Markov Model, Recurrent Neural Network, ArabicDigits.

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Authors: Jeffrey L. Duffany

Abstract:

The equivalence class subset algorithm is a powerful tool for solving a wide variety of constraint satisfaction problems and is based on the use of a decision function which has a very high but not perfect accuracy. Perfect accuracy is not required in the decision function as even a suboptimal solution contains valuable information that can be used to help find an optimal solution. In the hardest problems, the decision function can break down leading to a suboptimal solution where there are more equivalence classes than are necessary and which can be viewed as a mixture of good decision and bad decisions. By choosing a subset of the decisions made in reaching a suboptimal solution an iterative technique can lead to an optimal solution, using series of steadily improved suboptimal solutions. The goal is to reach an optimal solution as quickly as possible. Various techniques for choosing the decision subset are evaluated.

Keywords: np-complete, complexity, algorithm.

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Authors: Katejarinporn Chaiya, Thawit Janbanklong

Abstract:

The purposes of this study were to design and find users’ satisfaction after using the decision support system for tourism northern part of Thailand, which can provide tourists touristic information and plan their personal voyage. Such information can be retrieved systematically based on personal budget and provinces. The samples of this study were five experts and users 30 persons white collars in Bangkok. This decision support system was designed via ASP.NET. Its database was developed by using MySQL, for administrators are able to effectively manage the database. The application outcome revealed that the innovation works properly as sought in objectives. Specialists and white collars in Bangkok have evaluated the decision support system; the result was satisfactorily positive.

Keywords: Decision Support System, ASP.NET, MySQL.

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Authors: A.M. Al-Fahed Nuseirat, R. Abu-Zitar

Abstract:

In this paper the design of maximally flat linear phase finite impulse response (FIR) filters is considered. The problem is handled with totally two different approaches. The first one is completely deterministic numerical approach where the problem is formulated as a Linear Complementarity Problem (LCP). The other one is based on a combination of Markov Random Fields (MRF's) approach with messy genetic algorithm (MGA). Markov Random Fields (MRFs) are a class of probabilistic models that have been applied for many years to the analysis of visual patterns or textures. Our objective is to establish MRFs as an interesting approach to modeling messy genetic algorithms. We establish a theoretical result that every genetic algorithm problem can be characterized in terms of a MRF model. This allows us to construct an explicit probabilistic model of the MGA fitness function and introduce the Ising MGA. Experimentations done with Ising MGA are less costly than those done with standard MGA since much less computations are involved. The least computations of all is for the LCP. Results of the LCP, random search, random seeded search, MGA, and Ising MGA are discussed.

Keywords: Filter design, FIR digital filters, LCP, Ising model, MGA, Ising MGA.

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Authors: C. Ardil

Abstract:

This article presents a multiple criteria evaluation approach to uncertainty, vagueness, and imprecision analysis for ranking alternatives with fuzzy data for decision making using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The fighter aircraft evaluation and selection decision making problem is modeled in a fuzzy environment with triangular fuzzy numbers. The fuzzy decision information related to the fighter aircraft selection problem is taken into account in ordering the alternatives and selecting the best candidate. The basic fuzzy TOPSIS procedure steps transform fuzzy decision matrices into matrices of alternatives evaluated according to all decision criteria. A practical numerical example illustrates the proposed approach to the fighter aircraft selection problem.

Keywords: triangular fuzzy number (TFN), multiple criteria decision making analysis, decision making, aircraft selection, MCDMA, fuzzy TOPSIS

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Authors: K. Bommanna Raja, M.Madheswaran, K.Thyagarajah

Abstract:

A higher order spline interpolated contour obtained with up-sampling of homogenously distributed coordinates for segmentation of kidney region in different classes of ultrasound kidney images has been developed and presented in this paper. The performance of the proposed method is measured and compared with modified snake model contour, Markov random field contour and expert outlined contour. The validation of the method is made in correspondence with expert outlined contour using maximum coordinate distance, Hausdorff distance and mean radial distance metrics. The results obtained reveal that proposed scheme provides optimum contour that agrees well with expert outlined contour. Moreover this technique helps to preserve the pixels-of-interest which in specific defines the functional characteristic of kidney. This explores various possibilities in implementing computer-aided diagnosis system exclusively for US kidney images.

Keywords: Ultrasound Kidney Image – Kidney Segmentation –Active Contour – Markov Random Field – Higher Order SplineInterpolation

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Authors: Gee-Sern Jison Hsu

Abstract:

A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.

Keywords: Face recognition, open-set identification, hidden Markov model, support vector machines.

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Authors: Josip Visković, Josip Arnerić, Ante Rozga

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Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modeling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behavior of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.

Keywords: Central and east European countries, financial crisis, Markov switching GARCH model, transition probabilities.

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Authors: S. Panda, S. K. Tomar, R. Prasad, C. Ardil

Abstract:

Order reduction of linear-time invariant systems employing two methods; one using the advantages of Routh approximation and other by an evolutionary technique is presented in this paper. In Routh approximation method the denominator of the reduced order model is obtained using Routh approximation while the numerator of the reduced order model is determined using the indirect approach of retaining the time moments and/or Markov parameters of original system. By this method the reduced order model guarantees stability if the original high order model is stable. In the second method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical examples.

Keywords: Model Order Reduction, Markov Parameters, Routh Approximation, Particle Swarm Optimization, Integral Squared Error, Steady State Stability.

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Authors: Jadwiga R. Ziolkowska

Abstract:

In this paper, a fuzzy algorithm and a fuzzy multicriteria decision framework are developed and used for a practical question of optimizing biofuels policy making. The methodological framework shows how to incorporate fuzzy set theory in a decision process of finding a sustainable biofuels policy among several policy options. Fuzzy set theory is used here as a tool to deal with uncertainties of decision environment, vagueness and ambiguities of policy objectives, subjectivities of human assessments and imprecise and incomplete information about the evaluated policy instruments.

Keywords: Fuzzy set theory, multi-criteria decision-makingsupport, uncertainties, policy making, biofuels

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Authors: Katarzyna Mleczko

Abstract:

Processes of production of innovative medical tools have interdisciplinary character. They consist of direct and indirect close cooperation of specialists of different scientific branches. The Knowledge they have seems to be important for undertaken design, construction and manufacturing processes. The Knowledge exchange between participants of these processes is therefore crucial for the final result, which are innovative medical products. The paper draws attention to the necessity of feedback from the end user to the designer / manufacturer of medical tools which will allow for more accurate understanding of user needs. The study describes prerequisites of production processes of innovative medical (surgical) tools including participants and category of knowledge resources occurring in these processes. They are the result of research in selected Polish organizations involved in the production of medical instruments and are the basis for further work on the development of knowledge sharing model in interdisciplinary teams geographically dispersed.

Keywords: Interdisciplinary production processes, knowledge exchange, knowledge sharing, medical tools, user-centered design.

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Authors: Samsiah Abdul Razak, Daud Mohamad

Abstract:

Molodstov-s soft sets theory was originally proposed as general mathematical tool for dealing with uncertainty problems. The matrix form has been introduced in soft set and some of its properties have been discussed. However, the formulation of soft matrix in group decision making problem only with equal importance weights of criteria, which does not show the true opinion of decision maker on each criteria. The aim of this paper is to propose a method for solving group decision making problem incorporating the importance of criteria by using soft matrices in a more objective manner. The weight of each criterion is calculated by using the Analytic Hierarchy Process (AHP) method. An example of house selection process is given to illustrate the effectiveness of the proposed method.

Keywords: Soft set, Soft Matrix, Soft max-min decision making (SMmDM), Analytic hierarchy process (AHP)

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Authors: M. S. Bani, Z. A. Rashid, K. H. K. Hamid, M. E. Harbawi, A.B.Alias, M. J. Aris

Abstract:

Most Decision Support Systems (DSS) for waste management (WM) constructed are not widely marketed and lack practical applications. This is due to the number of variables and complexity of the mathematical models which include the assumptions and constraints required in decision making. The approach made by many researchers in DSS modelling is to isolate a few key factors that have a significant influence to the DSS. This segmented approach does not provide a thorough understanding of the complex relationships of the many elements involved. The various elements in constructing the DSS must be integrated and optimized in order to produce a viable model that is marketable and has practical application. The DSS model used in assisting decision makers should be integrated with GIS, able to give robust prediction despite the inherent uncertainties of waste generation and the plethora of waste characteristics, and gives optimal allocation of waste stream for recycling, incineration, landfill and composting.

Keywords: Review, decision support system, GIS and waste management.

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Authors: Kasim Terzic, Bernd Neumann

Abstract:

Scene interpretation systems need to match (often ambiguous) low-level input data to concepts from a high-level ontology. In many domains, these decisions are uncertain and benefit greatly from proper context. This paper demonstrates the use of decision trees for estimating class probabilities for regions described by feature vectors, and shows how context can be introduced in order to improve the matching performance.

Keywords: Classification, Decision Trees, Interpretation, Vision

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Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

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Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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Authors: Seung hee Kang, Jee-Hong Kim, Ji Seong Jang,

Abstract:

The purpose of this study was to investigate relationships between satisfaction with major and career decision efficacy and career attitude maturity of engineering college students by performing correlation analysis. Gender differences in between satisfaction with major and career decision efficacy and career attitude maturity were also examined by T-test. The results T-test revealed gender differences in only career decision efficacy. Male Students scored significantly higher than did female students on career decision efficacy and satisfaction with major. The results of correlation analysis showed a) satisfaction with major were significantly associated with career decision efficacy, b) satisfaction with major were significantly associated with career attitude maturity, and c) career decision efficacy were significantly associated with career attitude maturity. As a result,we found the importance of satisfaction in engineering college students- major studies when deciding their career.

Keywords: Satisfaction with major, career decision efficacy, career attitude maturity, engineering college student.

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