Entropic risk analysis by a high level decision support system (e-FDSS) for construction SMEs

The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects.

A self-structured adaptive decision feedback equalizer

In a decision feedback equalizer (DFE), the structural parameters, including the decision delay, the feedforward filter (FFF), and feedback filter (FBF) lengths, must be carefully chosen, as they greatly influence the performance. Although the FBF length can be set as the channel memory, there is no closed-form expression for the FFF length and decision delay. In this letter, first we analytically show that the two-dimensional search for the optimum FFF length and decision delay can be simplified to a one-dimensional search and then describe a new adaptive DFE where the optimum structural parameters can be self-adapted.

Nonlinear set-membership estimation: a support vector machine approach

In this paper a support vector machine (SVM) approach for characterizing the feasible parameter set (FPS) in non-linear set-membership estimation problems is presented. It iteratively solves a regression problem from which an approximation of the boundary of the FPS can be determined. To guarantee convergence to the boundary the procedure includes a no-derivative line search and for an appropriate coverage of points on the FPS boundary it is suggested to start with a sequential box pavement procedure. The SVM approach is illustrated on a simple sine and exponential model with two parameters and an agro-forestry simulation model.

Fast identification algorithms for Gaussian process model

A class identification algorithms is introduced for Gaussian process(GP)models.The fundamental approach is to propose a new kernel function which leads to a covariance matrix with low rank,a property that is consequently exploited for computational efficiency for both model parameter estimation and model predictions.The objective of either maximizing the marginal likelihood or the Kullback–Leibler (K–L) divergence between the estimated output probability density function(pdf)and the true pdf has been used as respective cost functions.For each cost function,an efficient coordinate descent algorithm is proposed to estimate the kernel parameters using a one dimensional derivative free search, and noise variance using a fast gradient descent algorithm. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.

Holocene tidal palaeochannels, Severn Estuary Levels, UK: a search for granulometric and foraminiferal criteria

Holocene tidal palaoechannels, Severn Estuary Levels, UK: a search for granulometric and foraminiferal criteria. Proceedings of the Geologists' Association, 117, 329-344. Grain-size characteristics (by laser granulometry) and foraminiferal assemblages have been established for silts accumulated in five, dissimilar tidal palaeochannels of mid or late Holocene age in the Severn Estuary Levels, representative of muddy tidal systems. For purposes of general comparison, similar data were obtained from a representative active tidal inlet in the area, but all of these channels have been subject to human interference and are not relied upon as a model for environmental interpretation. Although the palaeochannel deposits differ substantially in their bedding characteristics and stratigraphical relationships from the level-bedded salt-marsh platform and mudflat deposits with which they are associated, and although the channel environment is distinctive morphologically and hydraulically, no critical textural differences could be found between the channel deposits and the associated facies. Similarly, no foraminiferal assemblages distinctive of a tidal channel were encountered. Instead, the assemblages compare with those from mudflats and salt-marsh platforms. It is concluded that the sides of the subfossil channels carried some vegetation, as was observed to be the case in the modern inlet. An alternative approach is necessary if concealed palaeochannel deposits are to be recognized in muddy systems from limited numbers of subsurface samples. Although the palaeochannels afforded no characteristic textural signature, they yield transverse grain-size patterns pointing to coastal movements during their evolution. Concave-up trends suggest outward coastal building, whereas convex-up ones point to marsh-edge retreat.

LVB: parsimony and simulated annealing in the search for phylogenetic trees

Summary: The program LVB seeks parsimonious phylogenies from nucleotide alignments, using the simulated annealing heuristic. LVB runs fast and gives high quality results.

Argon predissociation spectroscopy of the OH-center dot H2O and Cl-center dot H2O complexes in the 1000-1900 cm(-1) region: Intramolecular bending transitions and the search for the shared-proton fundamental in the hydroxide monohydrate

We present argon predissociation vibrational spectra of the OH-.H2O and Cl-.H2O complexes in the 1000-1900 cm(-1) energy range, far below the OH stretching region reported in previous studies. This extension allows us to explore the fundamental transitions of the intramolecular bending vibrations associated with the water molecule, as well as that of the shared proton inferred from previous assignments of overtones in the higher energy region. Although the water bending fundamental in the Cl-.H2O spectrum is in very good agreement with expectations, the OH-.H2O spectrum is quite different than anticipated, being dominated by a strong feature at 1090 cm(-1). New full-diniensionality calculations of the OH-.H2O vibrational level structure using diffusion Monte Carlo and the VSCF/CI methods indicate this band arises from excitation of the shared proton.