A memetic particle swarm optimisation algorithm for dynamic multi-modal optimisation problems

Copyright @ 2011 Taylor & Francis.Many real-world optimisation problems are both dynamic and multi-modal, which require an optimisation algorithm not only to find as many optima under a specific environment as possible, but also to track their moving trajectory over dynamic environments. To address this requirement, this article investigates a memetic computing approach based on particle swarm optimisation for dynamic multi-modal optimisation problems (DMMOPs). Within the framework of the proposed algorithm, a new speciation method is employed to locate and track multiple peaks and an adaptive local search method is also hybridised to accelerate the exploitation of species generated by the speciation method. In addition, a memory-based re-initialisation scheme is introduced into the proposed algorithm in order to further enhance its performance in dynamic multi-modal environments. Based on the moving peaks benchmark problems, experiments are carried out to investigate the performance of the proposed algorithm in comparison with several state-of-the-art algorithms taken from the literature. The experimental results show the efficiency of the proposed algorithm for DMMOPs.This work was supported by the Key Program of National Natural Science Foundation (NNSF) of China under Grant no. 70931001, the Funds for Creative Research Groups of China under Grant no. 71021061, the National Natural Science Foundation (NNSF) of China under Grant 71001018, Grant no. 61004121 and Grant no. 70801012 and the Fundamental Research Funds for the Central Universities Grant no. N090404020, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant no. EP/E060722/01 and Grant EP/E060722/02, and the Hong Kong Polytechnic University under Grant G-YH60

Security detection of network intrusion: application of cluster analysis method

In order to resist network malicious attacks, this paper briefly introduced the network intrusion detection model and K-means clustering analysis algorithm, improved them, and made a simulation analysis on two clustering analysis algorithms on MATLAB software. The results showed that the improved K-means algorithm could achieve central convergence faster in training, and the mean square deviation of clustering center was smaller than the traditional one in convergence. In the detection of normal and abnormal data, the improved K-means algorithm had higher accuracy and lower false alarm rate and missing report rate. In summary, the improved K-means algorithm can be applied to network intrusion detection

A back-propagation neural network for mineralogical mapping from AVIRIS data

Imaging spectrometers have the potential to identify surface mineralogy based on the unique absorption features in pixel spectra. A back-propagation neural network (BPN) is introduced to classify Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) of the Cuprite mining district (Nevada) data into mineral maps. The results are compared with the traditional acquired surface mineralogy maps from spectral angle mapping (SAM). There is no misclassification for the training set in the case of BPN; however 17 percent misclassification occurs in SAM. The validation accuracy of the SAM is 69 percent, whereas BPN results in 86 per cent accuracy. The calibration accuracy of the BPN is higher than that of the SAM, suggesting that the training process of BPN is better than that of the SAM. The high classification accuracy obtained with the BPN can be explained by: (1)its ability to deal with complex relationships (e.g., 40 dimensions) and (2) the nature of the dataset, the minerals are highly concentrated and they are mostly represented by pure pixels. This paper demonstrates that BPN has superior classification ability when applied to imaging spectrometer data.Remote SensingImaging Science & Photographic TechnologySCI(E)EI29ARTICLE197-1102

Virtual Enterprises Risk Management DSS under Electronic Commerce

Risk management is important to the development of enterprise as well as social-economic prosperity. Virtual enterprise is the potential mode of future enterprise under electronic commerce environment and the risk management for it is a popular research area recently. Due to the complexity of its risk management a decision support system (DSS) with 3-bases-1-cell structure was designed. By coordinating data base, model base, algorithm base and dialogue cell, the functions of project management, risk identification, risk assessment, risk evaluation and risk programming was supported. The user-friendly system has such main characteristics as generality for verity virtual enterprise as well as different projects and the flexibility of model and algorithm, ensuring a standardized, scientific and informational risk management for virtual enterprises

Risk Evaluation for Virtual Enterprise

Virtual Enterprise is the potential mode of enterprise in the future. The risk management for virtual enterprise is the new research area recently. In virtual enterprise, the enterprise operation is always organized by project mode and there is always less historical data and there are many uncertain factors. Hence, in this paper, the fuzzy synthetic evaluation model for the risk evaluation of virtual enterprise is established focus on the project mode and uncertain characteristics of virtual enterprise. In the 5 levels model, the goal and sub-goal of the enterprise, the process of the project, as well as the risk event and risk factors are considered. The case study suggests that the method is useful

A REAL TIME MONITORING MODEL OF THE CALCIUM CARBONATE FOULING INDUCTION PERIOD BASED ON THE CONDUCTANCE TITRATION

A new method has been developed to monitor the calcium carbonate fouling induction period (CCFIP) in real time. Based on the conductance titration, this paper investigated the forming process of CCFIP by a staticdynamic combined simulation experiment unit. With the help of titration analysis (that is titrimetry), an accurate definition of CCFIP and the corresponding real time monitoring model were built up. The investigation results show that the proposed model applies not only to measure the CCFIP in real time, but also applies to an investigation of the influence of various factors on the CCFIP

A Nonlinear Force-Free Magnetic Field Approximation Suitable for Fast Forward-Fitting to Coronal Loops. II. Numeric Code and Tests

Based on a second-order approximation of nonlinear force-free magnetic field solutions in terms of uniformly twisted field lines derived in Paper I, we develop here a numeric code that is capable to forward-fit such analytical solutions to arbitrary magnetogram (or vector magnetograph) data combined with (stereoscopically triangulated) coronal loop 3D coordinates. We test the code here by forward-fitting to six potential field and six nonpotential field cases simulated with our analytical model, as well as by forward-fitting to an exactly force-free solution of the Low and Lou (1990) model. The forward-fitting tests demonstrate: (i) a satisfactory convergence behavior (with typical misalignment angles of $\mu \approx 1^\circ-10^\circ$), (ii) relatively fast computation times (from seconds to a few minutes), and (iii) the high fidelity of retrieved force-free $\alpha$-parameters ($\alpha_{\rm fit}/\alpha_{\rm model} \approx 0.9-1.0$ for simulations and $\alpha_{\rm fit}/\alpha_{\rm model} \approx 0.7\pm0.3$ for the Low and Lou model). The salient feature of this numeric code is the relatively fast computation of a quasi-forcefree magnetic field, which closely matches the geometry of coronal loops in active regions, and complements the existing {\sl nonlinear force-free field (NLFFF)} codes based on photospheric magnetograms without coronal constraints.Comment: Solar PHysics, (in press), 25 pages, 11 figure

Evaluation of the BCS Approximation for the Attractive Hubbard Model in One Dimension

The ground state energy and energy gap to the first excited state are calculated for the attractive Hubbard model in one dimension using both the Bethe Ansatz equations and the variational BCS wavefunction. Comparisons are provided as a function of coupling strength and electron density. While the ground state energies are always in very good agreement, the BCS energy gap is sometimes incorrect by an order of magnitude, particularly at half-filling. Finite size effects are also briefly discussed for cases where an exact solution in the thermodynamic limit is not possible. In general, the BCS result for the energy gap is poor compared to the exact result.Comment: 25 pages, 5 Postscript figure