基于特征进化的混合遗传算法

对于遗传算法存在早熟性收敛和收敛速度慢等问题,可通过保护存在于种群中的最小诱导模式和属于收敛优化解或全局最优解的有效基因块,得到有效的改善.通过对种群中个体之间关系分析,建立特征保护策略及特征进化算子,由此改进的混合遗传算法具有较高的收敛速度,并能收敛于规模小于2 000个城市的旅行商问题全局最优解.     

Selecting informative genes from microarray data by using hybrid methods for cancer classification

Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

An ant colony optimization approach to multi-objective optimal design of symmetric hybrid laminates for maximum fundamental frequency and minimum cost

An ant colony optimization algorithm for optimum design of symmetric hybrid laminates is described. The objective is simultaneous maximization of fundamental frequency and minimization of cost. Number of surface and core layers made of high-stiffness and low-stiffness materials, respectively, and fiber orientations are the design variables. Optimal stacking sequences are given for hybrid graphite/epoxy-glass/epoxy laminated plates with different aspect ratios and number of plies. The results obtained by ant colony optimization are compared to results obtained by a genetic algorithm and simulated annealing. The effectiveness of the hybridization concept for reducing the weight and keeping the fundamental frequency at a reasonable level is demonstrated. Furthermore, it is shown that the proposed ant colony algorithm outperforms the two other heuristics.     

On hybrid control of a class of stochastic non-linear Markovian switching systems

In this paper, we address the problem of hybrid control for a class of stochastic non-linear Markovian switching systems. First, a hybrid controller is introduced for the systems. Then under some appropriate assumptions, the stabilization condition for the systems under pure impulsive control is given. Further under impulsive control, the output feedback stabilization problem of the systems is discussed and linear output feedback controllers are designed. Finally a numerical example is provided to illustrate the effectiveness of the proposed methods.     

Adaptive multi-mode switching strategy for the spherical underwater robot with hybrid thrusters

The conventional autonomous cruise and tracking system cannot transition and change its motion mode according to the underwater environment during operation, so it is of great significance to study the multi-mode switching of cruise control for Autonomous Underwater Vehicles (AUVs). In this paper, a Multi-Mode Adaptive Switching (MMAS) strategy for the Spherical Underwater Robot with Hybrid Thruster (HPSUR) was proposed, which provided the possibility for the robot to choose optimal control mode according to the unpredictable operating environment. Then, the dynamic and force of the hybrid thruster are analyzed to improve the accuracy of multi-mode switching, and the MMAS strategy is developed linking the attitude adjustment and switching problems. Furthermore, a series of multi-mode switching experiments were conducted using water-jet mode, propeller mode and hybrid mode. Finally, the experimental result was discussed, which verified the effectiveness and accuracy of the proposed MMAS strategy. The proposed control strategy has a certain reference value for the multi-mode switching of propulsion devices.     

An MRAS method for sensorless control of induction motor over a wide speed range

This paper addresses the problem of wide speed range sensorless control of induction motor.The proposed method is based on model reference adaptive system (MRAS),in which the current model serves as the adjustable model,and a novel hybrid model integrating the modified voltage model (MVM) and high-frequency signal injection method (HFSIM) are established to serve as the reference model.The HFSIM works together with MVM to improve the performance of the rotor speed and rotor flux position estimation at low speed,whereas at high speed,the MVM acts alone.In addition,a rotor resistance online estimation scheme is proposed to update the rotor resistance contained in the adjustable model and to ensure the estimation accuracy further.Experimental results show that the proposed MRAS method is very effective from low to high speed range,including zero speed.     

Markov Jump Linear Systems with switching transition rates: Mean square stability with dwell-time

The stability of a class of Markov Jump Linear Systems characterized by piecewise-constant transition rates and system dynamics is investigated. For these Switching Markov Jump Linear Systems, mean square stability is analyzed through the time evolution of the second-order moment of the state. The main result is a sufficient condition that guarantees mean square stability under constraints on the dwell-time between switching instants. An alternative condition based on Kronecker calculus is worked out. It is shown that both the stability criteria admit an LMI implementation.     

Hybrid microdata using microaggregation

Statistical disclosure control (also known as privacy-preserving data mining) of microdata is about releasing data sets containing the answers of individual respondents protected in such a way that: (i) the respondents corresponding to the released records cannot be re-identified; (ii) the released data stay analytically useful. Usually, the protected data set is generated by either masking (i.e. perturbing) the original data or by generating synthetic (i.e. simulated) data preserving some pre-selected statistics of the original data. Masked data may approximately preserve a broad range of distributional characteristics, although very few of them (if any) are exactly preserved; on the other hand, synthetic data exactly preserve the pre-selected statistics and may seem less disclosive than masked data, but they do not preserve at all any statistics other than those pre-selected. Hybrid data obtained by mixing the original data and synthetic data have been proposed in the literature to combine the strengths of masked and synthetic data. We show how to easily obtain hybrid data by combining microaggregation with any synthetic data generator. We show that numerical hybrid data exactly preserving means and covariances of original data and approximately preserving other statistics as well as some subdomain analyses can be obtained as a particular case with a very simple parameterization. The new method is competitive versus both the literature on hybrid data and plain multivariate microaggregation.     

Hybrid LES/RANS modelling of free surface flow through vegetation

Vegetated channels are environmentally friendly and frequently used to convey water for drainage and recreational purposes. The design and assessment of these channels often requires the use of numerical models which are based on the Reynolds Averaged Navier-Stokes (RANS) approach or Large Eddy Simulations (LES). It is well accepted that both approaches have their advantages and disadvantages. To overcome these disadvantages a hybrid model combining the RANS and LES methodologies is proposed in this work. The major task for the model development is to couple the RANS and the LES models effectively. Various methods have been investigated and the results are as follows. At the inflow boundary of the computational domain, a semi-analytical velocity profile for submerged vegetation is used as the RANS inflow condition to shorten the unrealistic flow transition region. At the interface of the upstream RANS region and the downstream LES region, turbulence fluctuations are artificially generated using a spectral line processor, with the mean velocity determined by using the frozen cloud assumption. At the interface of the upstream LES region and the downstream RANS region, a virtual momentum sink is imposed to dissipate the sub-grid scale fluctuations and to shorten the transition region. The final model has been verified against experiments of flow through submerged and emergent vegetation, as well as a partly vegetated channel.