1,339 research outputs found
CIXL2: A Crossover Operator for Evolutionary Algorithms Based on Population Features
In this paper we propose a crossover operator for evolutionary algorithms
with real values that is based on the statistical theory of population
distributions. The operator is based on the theoretical distribution of the
values of the genes of the best individuals in the population. The proposed
operator takes into account the localization and dispersion features of the
best individuals of the population with the objective that these features would
be inherited by the offspring. Our aim is the optimization of the balance
between exploration and exploitation in the search process. In order to test
the efficiency and robustness of this crossover, we have used a set of
functions to be optimized with regard to different criteria, such as,
multimodality, separability, regularity and epistasis. With this set of
functions we can extract conclusions in function of the problem at hand. We
analyze the results using ANOVA and multiple comparison statistical tests. As
an example of how our crossover can be used to solve artificial intelligence
problems, we have applied the proposed model to the problem of obtaining the
weight of each network in a ensemble of neural networks. The results obtained
are above the performance of standard methods
Utilization of the discrete differential evolution for optimization in multidimensional point clouds
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.Web of Scienceart. no. 632953
Robustness of circadian clocks to daylight fluctuations: hints from the picoeucaryote Ostreococcus tauri
The development of systemic approaches in biology has put emphasis on
identifying genetic modules whose behavior can be modeled accurately so as to
gain insight into their structure and function. However most gene circuits in a
cell are under control of external signals and thus quantitative agreement
between experimental data and a mathematical model is difficult. Circadian
biology has been one notable exception: quantitative models of the internal
clock that orchestrates biological processes over the 24-hour diurnal cycle
have been constructed for a few organisms, from cyanobacteria to plants and
mammals. In most cases, a complex architecture with interlocked feedback loops
has been evidenced. Here we present first modeling results for the circadian
clock of the green unicellular alga Ostreococcus tauri. Two plant-like clock
genes have been shown to play a central role in Ostreococcus clock. We find
that their expression time profiles can be accurately reproduced by a minimal
model of a two-gene transcriptional feedback loop. Remarkably, best adjustment
of data recorded under light/dark alternation is obtained when assuming that
the oscillator is not coupled to the diurnal cycle. This suggests that coupling
to light is confined to specific time intervals and has no dynamical effect
when the oscillator is entrained by the diurnal cycle. This intringuing
property may reflect a strategy to minimize the impact of fluctuations in
daylight intensity on the core circadian oscillator, a type of perturbation
that has been rarely considered when assessing the robustness of circadian
clocks
The Role of Inertia in Modeling Decisions from Experience with Instance-Based Learning
One form of inertia is the tendency to repeat the last decision irrespective of the obtained outcomes while making decisions from experience (DFE). A number of computational models based upon the Instance-Based Learning Theory, a theory of DFE, have included different inertia implementations and have shown to simultaneously account for both risk-taking and alternations between alternatives. The role that inertia plays in these models, however, is unclear as the same model without inertia is also able to account for observed risk-taking quite well. This paper demonstrates the predictive benefits of incorporating one particular implementation of inertia in an existing IBL model. We use two large datasets, estimation and competition, from the Technion Prediction Tournament involving a repeated binary-choice task to show that incorporating an inertia mechanism in an IBL model enables it to account for the observed average risk-taking and alternations. Including inertia, however, does not help the model to account for the trends in risk-taking and alternations over trials compared to the IBL model without the inertia mechanism. We generalize the two IBL models, with and without inertia, to the competition set by using the parameters determined in the estimation set. The generalization process demonstrates both the advantages and disadvantages of including inertia in an IBL model
Polarization-ring-switching for nonlinearity-tolerant geometrically-shaped four-dimensional formats maximizing generalized mutual information
In this paper, a new four-dimensional 64-ary polarization ring switching
(4D-64PRS) modulation format with a spectral efficiency of 6 bit/4D-sym is
introduced. The format is designed by maximizing the generalized mutual
information (GMI) and by imposing a constant-modulus on the 4D structure. The
proposed format yields an improved performance with respect to state-of-the-art
geometrically shaped modulation formats for bit-interleaved coded modulation
systems at the same spectral efficiency. Unlike previously published results,
the coordinates of the constellation points and the binary labeling of the
constellation are jointly optimized. When compared with
polarization-multiplexed 8-ary quadrature-amplitude modulation (PM-8QAM), gains
of up to 0.7 dB in signal-to-noise ratio are observed in the additive white
Gaussian noise (AWGN) channel. For a long-haul nonlinear optical fiber system
of 8,000 km, gains of up to 0.27 bit/4D-sym (5.5% data capacity increase) are
observed. These gains translate into a reach increase of approximately 16%
(1,100 km). The proposed modulation format is also shown to be more tolerant to
nonlinearities than PM-8QAM. Results with LDPC codes are also presented, which
confirm the gains predicted by the GMI.Comment: 12 pages, 12 figure
An Auxin Transport-Based Model of Root Branching in Arabidopsis thaliana
Root architecture is a crucial part of plant adaptation to soil heterogeneity and is mainly controlled by root branching. The process of root system development can be divided into two successive steps: lateral root initiation and lateral root development/emergence which are controlled by different fluxes of the plant hormone auxin. While shoot architecture appears to be highly regular, following rules such as the phyllotactic spiral, root architecture appears more chaotic. We used stochastic modeling to extract hidden rules regulating root branching in Arabidopsis thaliana. These rules were used to build an integrative mechanistic model of root ramification based on auxin. This model was experimentally tested using plants with modified rhythm of lateral root initiation or mutants perturbed in auxin transport. Our analysis revealed that lateral root initiation and lateral root development/emergence are interacting with each other to create a global balance between the respective ratio of initiation and emergence. A mechanistic model based on auxin fluxes successfully predicted this property and the phenotype alteration of auxin transport mutants or plants with modified rythms of lateral root initiation. This suggests that root branching is controlled by mechanisms of lateral inhibition due to a competition between initiation and development/emergence for auxin
Optimisation and Decision Support during the Conceptual Stage of Building Design
Merged with duplicate record 10026.1/726 on 28.02.2017 by CS (TIS)Modern building design is complex and involves many different disciplines operating in a
fragmented manner. Appropriate computer-based decision support (DS) tools are sought
that can raise the level of integration of different activities at the conceptual stage, in order
to help create better designs solutions. This project investigates opportunities that exist for
using techniques based upon the Genetic Algorithm (GA) to support critical activities of
conceptual building design (CBD). Collective independent studies have shown that the
GA is a powerful optimisation and exploratory search technique with widespread
application. The GA is essentially very simple yet it offers robustness and domain
independence. The GA efficiently searches a domain to exploit highly suitable
information. It maintains multiple solutions to problems simultaneously and is well suited
to non-linear problems and those of a discontinuous nature found in engineering design.
The literature search first examines traditional approaches to supporting conceptual design.
Existing GA techniques and applications are discussed which include pioneering studies in
the field of detailed structural design. Broader GA studies are also reported which have
demonstrated possibilities for investigating geometrical, topological and member size
variation. The tasks and goals of conceptual design are studied. A rationale is introduced,
aimed at enabling the GA to be applied in a manner that provides the most effective
support to the designer. Numerical experiments with floor planning are presented. These
studies provide a basic foundation for a subsequent design support system (DSS) capable
of generating structural design concepts.
A hierarchical Structured GA (SGA) created by Dasgupta et al [1] is investigated to
support the generation of diverse structural design concepts. The SGA supports variation
in the size, shape and structural configuration of a building and in the choice of structural
frame type and floor system. The benefits and limitations of the SGA approach are
discussed. The creation of a prototype DSS system, abritrarily called Designer-Pro
(DPRO), is described. A detailed building design model is introduced which is required
for design development and appraisal. Simplifications, design rationale and generic
component modelling are mentioned. A cost-based single criteria optimisation problem
(SCOP) is created in which other constraints are represented as design parameters.
The thesis describes the importance of the object-oriented programming (OOP) paradigm
for creating a versatile design model and the need for complementary graphical user
interface (GUI) tools to provide human-computer interaction (HCI) capabilities for control
and intelligent design manipulation. Techniques that increase flexibility in the generation
and appraisal of concept are presented. Tools presented include a convergence plot of
design solutions that supports cursor-interrogation to reveal the details of individual
concepts. The graph permits study of design progression, or evolution of optimum design
solutions. A visualisation tool is also presented.
The DPRO system supports multiple operating modes, including single-design appraisal
and enumerative search (ES). Case study examples are provided which demonstrate the
applicability of the DPRO system to a range of different design scenarios. The DPRO
system performs well in all tests. A parametric study demonstrates the potential of the
system for DS. Limitations of the current approach and opportunities to broaden the study
form part of the scope for further work. Some suggestions for further study are made,
based upon newly-emerging techniques
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