The fuzzy optimization problem is one of the prominent topics in the broad area of artificial intelligence. It is applicable in the field of non-linear fuzzy programming. Its application as well as practical realizati...
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The fuzzy optimization problem is one of the prominent topics in the broad area of artificial intelligence. It is applicable in the field of non-linear fuzzy programming. Its application as well as practical realization can been seen in all the real world problems. In this paper a large scale non-linear fuzzy programming problem was solved by hybrid optimization techniques like Line Search (LS), Simulated Annealing (SA) and Pattern Search (PS). An industrial production planning problem with a cubic objective function, eight decision variables and 29 constraints was solved successfully using the LS-SA-PS hybrid optimization techniques. The computational results for the objective function with respect to vagueness factor and level of satisfaction has been provided in the form of 2D and 3D plots. The outcome is very promising and strongly suggests that the hybrid LS-SA-PS algorithm is very efficient and productive in solving the large scale non-linear fuzzy programming problem. (C) 2011 Elsevier Ltd. All rights reserved.
Optimization of neural network topology, weights and neuron activation functions for given data set and problem is not an easy task. In this article, a technique for automatic configuration of parameters topology for ...
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Optimization of neural network topology, weights and neuron activation functions for given data set and problem is not an easy task. In this article, a technique for automatic configuration of parameters topology for feedforward artificial neural networks (ANN) is presented. The determination of optimal parameters is formulated as an optimization problem, solved with the use of meta-heuristic Multiple Particle Collision Algorithm (MPCA). The self-configuring networks are applied to predict the mesoscale climate for the precipitation field. The results obtained from the neural network using the method of data reduction by the Theory of Rough Sets and the self-configuring network by MPCA were compared.
Summary form only given. Typical greedy algorithms for sparse reconstruction problems, such as orthogonal matching pursuit and iterative thresholding, seek strictly sparse solutions. Recent work in the literature sugg...
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ISBN:
(纸本)9781479934188
Summary form only given. Typical greedy algorithms for sparse reconstruction problems, such as orthogonal matching pursuit and iterative thresholding, seek strictly sparse solutions. Recent work in the literature suggests that given a priori knowledge of the distribution of the sparse signal coefficients, better results can be obtained by a weighted averaging of several sparse solutions. Such a combination of solutions, while not strictly sparse, approximates an MMSE estimator and can outperform strictly sparse solvers in terms of l-2 reconstruction error. We introduce a novel method for obtaining such an approximate MMSE estimator by replacing the deterministic thresholding operator of Iterative Hard Thresholding with a randomized version. We demonstrate the improvement in performance experimentally for both synthetic 1D signals and real images.
Stationary bubbles simulated by the multiphase lattice Boltzmann method (LBM) lead to eight symmetric eddies at the interfaces of two-phase flows. A distribution function is introduced in the lattice Boltzmann equatio...
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Stationary bubbles simulated by the multiphase lattice Boltzmann method (LBM) lead to eight symmetric eddies at the interfaces of two-phase flows. A distribution function is introduced in the lattice Boltzmann equation. Numerical simulations conform that eight symmetric eddies at the interfaces of two-phase flows are eliminated effectively by using this method, and the spurious velocities are reduces effectively.
In this paper, a comprehensive study of the downlink performance in a heterogeneous cellular network (or hetnet) is conducted. A general hetnet model is considered consisting of an arbitrary number of open-access and ...
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We present an efficient algorithm for calculating the minimum energy path(MEP)and energy barriers between local minima on a multidimensional potential energy surface(PES).Such paths play a central role in the understa...
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We present an efficient algorithm for calculating the minimum energy path(MEP)and energy barriers between local minima on a multidimensional potential energy surface(PES).Such paths play a central role in the understanding of transition pathways between metastable *** method relies on the original formulation of the string method[***.B,66,052301(2002)],*** evolve a smooth curve along a direction normal to the *** algorithm works by performing minimization steps on hyperplanes normal to the *** the problem of finding MEP on the PES is remodeled as a set of constrained minimization *** provides the flexibility of using minimization algorithms faster than the steepest descent method used in the simplified string method[***.,126(16),164103(2007)].At the same time,it provides a more direct analog of the finite temperature string *** applicability of the algorithm is demonstrated using various examples.
Networks often possess mesoscale structures, and studying them can yield insights into both structure and function. It is most common to study community structure, but numerous other types of mesoscale structures also...
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Networks often possess mesoscale structures, and studying them can yield insights into both structure and function. It is most common to study community structure, but numerous other types of mesoscale structures also exist. In this paper, we examine core-periphery structures based on both density and transport. In such structures, core network components are well-connected both among themselves and to peripheral components, which are not well-connected to anything. We examine core-periphery structures in a wide range of examples of transportation, social, and financial networks—including road networks in large urban areas, a rabbit warren, a dolphin social network, a European interbank network, and a migration network between counties in the United States. We illustrate that a recently developed transport-based notion of node coreness is very useful for characterizing transportation networks. We also generalize this notion to examine core versus peripheral edges, and we show that the resulting diagnostic is also useful for transportation networks. To examine the properties of transportation networks further, we develop a family of generative models of roadlike networks. We illustrate the effect of the dimensionality of the embedding space on transportation networks, and we demonstrate that the correlations between different measures of coreness can be very different for different types of networks.
We have applied the fluorescence quenching modeling to study the process of interaction of sulpiride with human serum albumin (HSA) and bovine (BSA). Albumin is more abundant protein in blood and it emits fluorescence...
We have applied the fluorescence quenching modeling to study the process of interaction of sulpiride with human serum albumin (HSA) and bovine (BSA). Albumin is more abundant protein in blood and it emits fluorescence when excited by 260-295 nm. Sulpiride is an atypical antipsychotic used in the treatment of many psychiatric disorders. As sulpiride is fluorescent, we developed a mathematical model to analyzing the interaction of two fluorescent substances. This model was able to separate the albumin fluorescence from the quencher fluorescence. Results have shown that sulpiride quenches the fluorescence of both albumins by a static process, due to the complex formation drugalbumin. The association constants calculated for sulpiride-HSA was 2.20 (± 0.08) × 104 M−1 at 37° C, and 5.46 (± 0.20) × 104 M−1, 25 ° C, and the primary binding site to sulpiride in the albumin is located closer to the subdomain IB.
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