Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: Region covariance (RC) descriptor is an effective
and efficient feature for visual tracking. Current RC-based tracking
algorithms use the whole RC matrix to track the target in video
directly. However, there exist some issues for these whole RCbased
algorithms. If some features are contaminated, the whole RC
will become unreliable, which results in lost object-tracking. In
addition, if some features are very discriminative to the
background, other features are still processed and thus reduce the
efficiency. In this paper a new robust tracking method is proposed,
in which the whole RC matrix is decomposed into several low rank
matrices. Those matrices are dynamically chosen and processed so
as to achieve a good tradeoff between discriminability and
complexity. Experimental results have shown that our method is
more robust to complex environment changes, especially either
when occlusion happens or when the background is similar to the
target compared to other RC-based methods.
Abstract: This paper considers H∞ performance for Markovian jump systems with Time-varying delays. The systems under consideration involve disturbance signal, Markovian switching and timevarying delays. By using a new Lyapunov-Krasovskii functional and a convex optimization approach, a delay-dependent stability condition in terms of linear matrix inequality (LMI) is addressed, which guarantee asymptotical stability in mean square and a prescribed H∞ performance index for the considered systems. Two numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed main results. All these results are expected to be of use in the study of stochastic systems with time-varying delays.
Abstract: In this paper the gradient based iterative algorithms are presented to solve the following four types linear matrix equations: (a) AXB = F; (b) AXB = F, CXD = G; (c) AXB = F s. t. X = XT ; (d) AXB+CYD = F, where X and Y are unknown matrices, A,B,C,D, F,G are the given constant matrices. It is proved that if the equation considered has a solution, then the unique minimum norm solution can be obtained by choosing a special kind of initial matrices. The numerical results show that the proposed method is reliable and attractive.
Abstract: By using a new set of arithmetic operations on interval numbers, we discuss some arithmetic properties of interval matrices which intern helps us to compute the powers of interval matrices and to solve the system of interval linear equations.
Abstract: This paper presents a heuristic approach to solve the Generalized Assignment Problem (GAP) which is NP-hard. It is worth mentioning that many researches used to develop algorithms for identifying the redundant constraints and variables in linear programming model. Some of the algorithms are presented using intercept matrix of the constraints to identify redundant constraints and variables prior to the start of the solution process. Here a new heuristic approach based on the dominance property of the intercept matrix to find optimal or near optimal solution of the GAP is proposed. In this heuristic, redundant variables of the GAP are identified by applying the dominance property of the intercept matrix repeatedly. This heuristic approach is tested for 90 benchmark problems of sizes upto 4000, taken from OR-library and the results are compared with optimum solutions. Computational complexity is proved to be O(mn2) of solving GAP using this approach. The performance of our heuristic is compared with the best state-ofthe- art heuristic algorithms with respect to both the quality of the solutions. The encouraging results especially for relatively large size test problems indicate that this heuristic approach can successfully be used for finding good solutions for highly constrained NP-hard problems.
Abstract: In this paper we study some numerical methods to solve a model one-dimensional convection–diffusion equation. The semi-discretisation of the space variable results into a system of ordinary differential equations and the solution of the latter involves the evaluation of a matrix exponent. Since the calculation of this term is computationally expensive, we study some methods based on Krylov subspace and on Restrictive Taylor series approximation respectively. We also consider the Chebyshev Pseudospectral collocation method to do the spatial discretisation and we present the numerical solution obtained by these methods.
Abstract: The load flow study in a power system constitutes a study of paramount importance. The study reveals the electrical performance and power flows (real and reactive) for specified condition when the system is operating under steady state. This paper gives an overview of different techniques used for load flow study under different specified conditions.
Abstract: This article presents a numerical study of the doublediffusive
mixed convection in a vertical channel filled with porous
medium by using non-equilibrium model. The flow is assumed
fully developed, uni-directional and steady state. The controlling
parameters are thermal Rayleigh number (RaT ), Darcy number (Da),
Forchheimer number (F), buoyancy ratio (N), inter phase heat transfer
coefficient (H), and porosity scaled thermal conductivity ratio
(γ). The Brinkman-extended non-Darcy model is considered. The
governing equations are solved by spectral collocation method. The
main emphasize is given on flow profiles as well as heat and solute
transfer rates, when two diffusive components in terms of buoyancy
ratio are in favor (against) of each other and solid matrix and fluid
are thermally non-equilibrium. The results show that, for aiding flow
(RaT = 1000), the heat transfer rate of fluid (Nuf ) increases upto a
certain value of H, beyond that decreases smoothly and converges
to a constant, whereas in case of opposing flow (RaT = -1000),
the result is same for N = 0 and 1. The variation of Nuf in (N,
Nuf )-plane shows sinusoidal pattern for RaT = -1000. For both cases
(aiding and opposing) the flow destabilize on increasing N by inviting
point of inflection or flow separation on the velocity profile. Overall,
the buoyancy force have significant impact on the non-Darcy mixed
convection under LTNE conditions.
Abstract: In this paper, we represent protein structure by using
graph. A protein structure database will become a graph database.
Each graph is represented by a spectral vector. We use Jacobi
rotation algorithm to calculate the eigenvalues of the normalized
Laplacian representation of adjacency matrix of graph. To measure
the similarity between two graphs, we calculate the Euclidean
distance between two graph spectral vectors. To cluster the graphs,
we use M-tree with the Euclidean distance to cluster spectral vectors.
Besides, M-tree can be used for graph searching in graph database.
Our proposal method was tested with graph database of 100 graphs
representing 100 protein structures downloaded from Protein Data
Bank (PDB) and we compare the result with the SCOP hierarchical
structure.
Abstract: The influence of extrusion parameters on surface
quality and properties of AA6061+x% vol. SiC (x = 0; 2,5; 5; 7,5;10)
composites was discussed in this paper. The averages size of
AA6061 and SiC particles were 10.6 μm and 0.42 μm, respectively.
Two series of composites (I - compacts were preheated at extrusion
temperature through 0.5 h and cooled by water directly after process;
II - compacts were preheated through 3 hours and were not cooled)
were consolidated via powder metallurgy processing and extruded by
KoBo method. High values of density for both series of composites
were achieved. Better surface quality was observed for II series of
composites. Moreover, for these composites lower (compared to I
series) but more uniform strength properties over the cross-section of
the bar were noticed. Microstructure and Young-s modulus
investigations were made.
Abstract: Based on the classical algorithm LSQR for solving (unconstrained) LS problem, an iterative method is proposed for the least-squares like-minimum-norm symmetric solution of AXB+CYD=E. As the application of this algorithm, an iterative method for the least-squares like-minimum-norm biymmetric solution of AXB=E is also obtained. Numerical results are reported that show the efficiency of the proposed methods.
Abstract: This paper proposes improved delay-dependent stability conditions of the linear time-delay systems of neutral type. The proposed methods employ a suitable Lyapunov-Krasovskii’s functional and a new form of the augmented system. New delay-dependent stability criteria for the systems are established in terms of Linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical examples showed that the proposed method is effective and can provide less conservative results.
Abstract: This paper presents a method for functional projective H∞ synchronization problem of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both drive and response systems but also reduce the effect of external disturbance to an H∞ norm constraint.
Abstract: As a company competitiveness depends more and more on the relationship with its stakeholders, the topic of companystakeholder fit is becoming increasingly important. This fit affects the extent to which a stakeholder perceives CSR company commitment, values and behaviors and, therefore, stakeholder identification in a company and his/her loyalty to it. Consequently, it is important to measure the alignment or the gap between stakeholder CSR demands, values, preferences and perceptions, and the company CSR disclosed commitment, values and policies. In this paper, in order to assess the company-stakeholder fit about corporate responsibility, an innovative CSR fit positioning matrix is proposed. This matrix is based on the measurement of a company CSR disclosed commitment and stakeholder perceived and required commitment. The matrix is part of a more complex methodology based on Global Reporting Initiative (GRI) indicators, content analysis and stakeholder questionnaires. This methodology provides appropriate indications for helping companies to achieve CSR company-stakeholder fit, by leveraging both CSR commitment and communication. Moreover, it could be used by top management for comparing different companies and stakeholders, and for planning specific CSR strategies, policies and activities.
Abstract: This paper applies fuzzy clustering algorithm in classifying real estate companies in China according to some general financial indexes, such as income per share, share accumulation fund, net profit margins, weighted net assets yield and shareholders' equity. By constructing and normalizing initial partition matrix, getting fuzzy similar matrix with Minkowski metric and gaining the transitive closure, the dynamic fuzzy clustering analysis for real estate companies is shown clearly that different clustered result change gradually with the threshold reducing, and then, it-s shown there is the similar relationship with the prices of those companies in stock market. In this way, it-s great valuable in contrasting the real estate companies- financial condition in order to grasp some good chances of investment, and so on.
Abstract: In this paper, two matrix iterative methods are presented to solve the matrix equation A1X1B1 + A2X2B2 + ... + AlXlBl = C the minimum residual problem l i=1 AiXiBi−CF = minXi∈BRni×ni l i=1 AiXiBi−CF and the matrix nearness problem [X1, X2, ..., Xl] = min[X1,X2,...,Xl]∈SE [X1,X2, ...,Xl] − [X1, X2, ..., Xl]F , where BRni×ni is the set of bisymmetric matrices, and SE is the solution set of above matrix equation or minimum residual problem. These matrix iterative methods have faster convergence rate and higher accuracy than former methods. Paige’s algorithms are used as the frame method for deriving these matrix iterative methods. The numerical example is used to illustrate the efficiency of these new methods.
Abstract: Artificial atoms are growing fields of interest due to their physical and optoelectronicapplications. The absorption spectra of the proposed artificial atom inpresence of Tera-Hertz field is investigated theoretically. We use the non-perturbativeFloquet theory and finite difference method to study the electronic structure of ArtificialAtom. The effect of static electric field on the energy levels of artificial atom is studied.The effect of orientation of static electric field on energy levels and diploe matrix elementsis also highlighted.
Abstract: In this paper, we give the generalized alternating twostage method in which the inner iterations are accomplished by a generalized alternating method. And we present convergence results of the method for solving nonsingular linear systems when the coefficient matrix of the linear system is a monotone matrix or an H-matrix.
Abstract: A parallel block method based on Backward
Differentiation Formulas (BDF) is developed for the parallel solution
of stiff Ordinary Differential Equations (ODEs). Most common
methods for solving stiff systems of ODEs are based on implicit
formulae and solved using Newton iteration which requires repeated
solution of systems of linear equations with coefficient matrix, I -
hβJ . Here, J is the Jacobian matrix of the problem. In this paper,
the matrix operations is paralleled in order to reduce the cost of the
iterations. Numerical results are given to compare the speedup and
efficiency of parallel algorithm and that of sequential algorithm.