52,897 research outputs found
Development of an automated aircraft subsystem architecture generation and analysis tool
Purpose – The purpose of this paper is to present a new computational framework to address future
preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate
technologies forming subsystem architectures is enabled with the provision of automated architecture
generation, analysis and optimization. Main focus lies with a demonstration of the frameworks
workings, as well as the optimizers performance with a typical form of application problem.
Design/methodology/approach – The core aspects involve a functional decomposition, coupled
with a synergistic mission performance analysis on the aircraft, architecture and component levels.
This may be followed by a complete enumeration of architectures, combined with a user defined
technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on
ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both
component composition and design parameters. The optimizer is tested on a generic architecture
design problem combined with modified Griewank and parabolic functions for the continuous space.
Findings – Insights from the generalized application problem show consistent rediscovery of the
optimal architectures with the optimizer, as compared to a full problem enumeration. In addition
multi-objective optimization reveals a Pareto front with differences in component composition as well
as continuous parameters.
Research limitations/implications – This paper demonstrates the frameworks application on a
generalized test problem only. Further publication will consider real engineering design problems.
Originality/value – The paper addresses the need for future conceptual design methods of complex
systems to consider a mixed concept space of both discrete and continuous nature via automated methods
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Intelligent Learning Algorithms for Active Vibration Control
YesThis correspondence presents an investigation into the
comparative performance of an active vibration control (AVC) system
using a number of intelligent learning algorithms. Recursive least square
(RLS), evolutionary genetic algorithms (GAs), general regression neural
network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS)
algorithms are proposed to develop the mechanisms of an AVC system.
The controller is designed on the basis of optimal vibration suppression
using a plant model. A simulation platform of a flexible beam system
in transverse vibration using a finite difference method is considered to
demonstrate the capabilities of the AVC system using RLS, GAs, GRNN,
and ANFIS. The simulation model of the AVC system is implemented,
tested, and its performance is assessed for the system identification models
using the proposed algorithms. Finally, a comparative performance of the
algorithms in implementing the model of the AVC system is presented and
discussed through a set of experiments
Hybrid Iterative Multiuser Detection for Channel Coded Space Division Multiple Access OFDM Systems
Space division multiple access (SDMA) aided orthogonal frequency division multiplexing (OFDM) systems assisted by efficient multiuser detection (MUD) techniques have recently attracted intensive research interests. The maximum likelihood detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher order modulation schemes. By contrast, the minimum mean-square error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward error correction (FEC) schemes such as, for example, turbo trellis coded modulation (TTCM), may be efficiently combined with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided code division multiple access (CDMA) systems. In this contribution, a GA-aided MMSE MUD is proposed for employment in a TTCM assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its optimum MLD-aided counterpart at a significantly lower complexity, especially at high user loads. Moreover, when the proposed biased Q-function based mutation (BQM) assisted iterative GA (IGA) MUD is employed, the GA-aided system’s performance can be further improved, for example, by reducing the bit error ratio (BER) measured at 3 dB by about five orders of magnitude in comparison to the TTCM assisted MMSE-SDMA-OFDM benchmarker system, while still maintaining modest complexity
Fiscal crises in US cities: Structural and non-structural causes
Financial difficulties of U.S. cities have recently become a major issue of concern. However, there is little agreement on why certain cities experience crises while others do not. Two arguments are put forward: Cities suffer from (1) structural problems like high immigration, congestion etc. (2) nonstructural political problems like the weakness of the mayor, union-power etc. Starting from a common pool model of municipal goods we estimate demand equations for spending and debt with structural variables. The estimation is based on 900 US cities in 1985, 1991 and 1999. Structural factors predicted by the model explain most of the variation of spending and debt levels. Furthermore coefficients are stable over time. However, excessively high debt burdens as indicators of potential crisis, and high spending levels are outliers and not explained by structural factors. --
The market for salmon futures: an empirical analysis of fish pool using the Schwartz multifactor model
Using the popular Schwartz 97 two-factor approach, we study future contracts written on fresh farmed salmon, which have been actively traded at the Fish Pool Market in Norway since 2006. This approach features a stochastic convenience yield for the salmon spot price. We connect this approach with the classical literature on fish-farming and aquaculture using first principles, starting by modeling the aggregate salmon farming production process and modeling the demand using a Cobb-Douglas utility function for a representative consumer. The model is estimated by means of Kalman filtering, using a rich data set of contracts with different maturities traded at Fish Pool between 12/06/2006 and 22/03/2012. The results are then discussed in the context of other commodity markets, specifically live cattle which acts as a substitute
Combining isotonic regression and EM algorithm to predict genetic risk under monotonicity constraint
In certain genetic studies, clinicians and genetic counselors are interested
in estimating the cumulative risk of a disease for individuals with and without
a rare deleterious mutation. Estimating the cumulative risk is difficult,
however, when the estimates are based on family history data. Often, the
genetic mutation status in many family members is unknown; instead, only
estimated probabilities of a patient having a certain mutation status are
available. Also, ages of disease-onset are subject to right censoring. Existing
methods to estimate the cumulative risk using such family-based data only
provide estimation at individual time points, and are not guaranteed to be
monotonic or nonnegative. In this paper, we develop a novel method that
combines Expectation-Maximization and isotonic regression to estimate the
cumulative risk across the entire support. Our estimator is monotonic,
satisfies self-consistent estimating equations and has high power in detecting
differences between the cumulative risks of different populations. Application
of our estimator to a Parkinson's disease (PD) study provides the age-at-onset
distribution of PD in PARK2 mutation carriers and noncarriers, and reveals a
significant difference between the distribution in compound heterozygous
carriers compared to noncarriers, but not between heterozygous carriers and
noncarriers.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS730 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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