145 resultados para evolutionary algorithms


Relevância:

20.00% 20.00%

Publicador:

Resumo:

The increasing demand for cheaper-faster-better services anytime and anywhere has made radio network optimisation much more complex than ever before. In order to dynamically optimise the serving network, Dynamic Network Optimisation (DNO), is proposed as the ultimate solution and future trend. The realization of DNO, however, has been hindered by a significant bottleneck of the optimisation speed as the network complexity grows. This paper presents a multi-threaded parallel solution to accelerate complicated proprietary network optimisation algorithms, under a rigid condition of numerical consistency. ariesoACP product from Arieso Ltd serves as the platform for parallelisation. This parallel solution has been benchmarked and results exhibit a high scalability and a run-time reduction by 11% to 42% based on the technology, subscriber density and blocking rate of a given network in comparison with the original version. Further, it is highly essential that the parallel version produces equivalent optimisation quality in terms of identical optimisation outputs.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A connection between a fuzzy neural network model with the mixture of experts network (MEN) modelling approach is established. Based on this linkage, two new neuro-fuzzy MEN construction algorithms are proposed to overcome the curse of dimensionality that is inherent in the majority of associative memory networks and/or other rule based systems. The first construction algorithm employs a function selection manager module in an MEN system. The second construction algorithm is based on a new parallel learning algorithm in which each model rule is trained independently, for which the parameter convergence property of the new learning method is established. As with the first approach, an expert selection criterion is utilised in this algorithm. These two construction methods are equivalent in their effectiveness in overcoming the curse of dimensionality by reducing the dimensionality of the regression vector, but the latter has the additional computational advantage of parallel processing. The proposed algorithms are analysed for effectiveness followed by numerical examples to illustrate their efficacy for some difficult data based modelling problems.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

The optimal and the zero-forcing beamformers are two commonly used algorithms in the subspace-based blind beamforming technology. The optimal beamformer is regarded as the algorithm with the best output SINR. The zero-forcing algorithm emphasizes the co-channel interference cancellation. This paper compares the performance of these two algorithms under some practical conditions: the effect of the finite data length and the existence of the angle estimation error. The investigation reveals that the zero-forcing algorithm can be more robust in the practical environment than the optimal algorithm.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

This paper uses genetic algorithms to optimise the mathematical model of a beer fermentation process that operates in batch mode. The optimisation is based in adjusting the temperature profile of the mixture during a fixed period of time in order to reach the required ethanol levels but considering certain operational and quality restrictions.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Two so-called “integrated” polarimetric rate estimation techniques, ZPHI (Testud et al., 2000) and ZZDR (Illingworth and Thompson, 2005), are evaluated using 12 episodes of the year 2005 observed by the French C-band operational Trappes radar, located near Paris. The term “integrated” means that the concentration parameter of the drop size distribution is assumed to be constant over some area and the algorithms retrieve it using the polarimetric variables in that area. The evaluation is carried out in ideal conditions (no partial beam blocking, no ground-clutter contamination, no bright band contamination, a posteriori calibration of the radar variables ZH and ZDR) using hourly rain gauges located at distances less than 60 km from the radar. Also included in the comparison, for the sake of benchmarking, is a conventional Z = 282R1.66 estimator, with and without attenuation correction and with and without adjustment by rain gauges as currently done operationally at Météo France. Under those ideal conditions, the two polarimetric algorithms, which rely solely on radar data, appear to perform as well if not better, pending on the measurements conditions (attenuation, rain rates, …), than the conventional algorithms, even when the latter take into account rain gauges through the adjustment scheme. ZZDR with attenuation correction is the best estimator for hourly rain gauge accumulations lower than 5 mm h−1 and ZPHI is the best one above that threshold. A perturbation analysis has been conducted to assess the sensitivity of the various estimators with respect to biases on ZH and ZDR, taking into account the typical accuracy and stability that can be reasonably achieved with modern operational radars these days (1 dB on ZH and 0.2 dB on ZDR). A +1 dB positive bias on ZH (radar too hot) results in a +14% overestimation of the rain rate with the conventional estimator used in this study (Z = 282R^1.66), a -19% underestimation with ZPHI and a +23% overestimation with ZZDR. Additionally, a +0.2 dB positive bias on ZDR results in a typical rain rate under- estimation of 15% by ZZDR.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Background: Serine proteases are major components of viper venom and target various stages of the blood coagulation system in victims and prey. A better understanding of the diversity of serine proteases and other enzymes present in snake venom will help to understand how the complexity of snake venom has evolved and will aid the development of novel therapeutics for treating snake bites. Methodology and Principal Findings: Four serine protease-encoding genes from the venom gland transcriptome of Bitis gabonica rhinoceros were amplified and sequenced. Mass spectrometry suggests the four enzymes corresponding to these genes are present in the venom of B. g. rhinoceros. Two of the enzymes, rhinocerases 2 and 3 have substitutions to two of the serine protease catalytic triad residues and are thus unlikely to be catalytically active, though they may have evolved other toxic functions. The other two enzymes, rhinocerases 4 and 5, have classical serine protease catalytic triad residues and thus are likely to be catalytically active, however they have glycine rather than the more typical aspartic acid at the base of the primary specificity pocket (position 189). Based on a detailed analysis of these sequences we suggest that alternative splicing together with individual amino acid mutations may have been involved in their evolution. Changes within amino acid segments which were previously proposed to undergo accelerated change in venom serine proteases have also been observed. Conclusions and Significance: Our study provides further insight into the diversity of serine protease isoforms present within snake venom and discusses their possible functions and how they may have evolved. These multiple serine protease isoforms with different substrate specificities may enhance the envenomation effects and help the snake to adapt to new habitats and diets. Our findings have potential for helping the future development of improved therapeutics for snake bites.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

The authors consider the problem of a robot manipulator operating in a noisy workspace. The manipulator is required to move from an initial position P(i) to a final position P(f). P(i) is assumed to be completely defined. However, P(f) is obtained by a sensing operation and is assumed to be fixed but unknown. The authors approach to this problem involves the use of three learning algorithms, the discretized linear reward-penalty (DLR-P) automaton, the linear reward-penalty (LR-P) automaton and a nonlinear reinforcement scheme. An automaton is placed at each joint of the robot and by acting as a decision maker, plans the trajectory based on noisy measurements of P(f).