SUMMARYThe multi-core technology can not only provide the computation in parallel but also avoid the redundancy costs by the communication and maintenance of multi-machine network structure. This paper uses the multi-core technology to achieve the parallelism of wavelet and wavelet packet transforms, so that the computation speed is increasing and the time is shortening in the practical applications. The parallel algorithms of wavelet and wavelet packet transforms, respectively, on the basis of POSIX thread and OpenMP are proposed and realized. The parallel results can meet the requirements by comparing parallel algorithms with the serial algorithms of single-layer and multi-layer transforms. For OpenMP, the paper takes the guidance statements to parallelize the loops of serial programs. In addition, the paper proposes one kind of nesting and non-nesting parallel means of wavelet packet transform and compares the parallel results with the serial programs. The experimental results show that the speedup is increasing with the amount of data and finally closing to 2. It is shown that the proposed parallel algorithms can improve the transform speed significantly. These parallel algorithms are applied in the harmonic analysis and data compression of power system, and a parallel strategy for compression with bitmap is proposed. The results show that the parallel algorithms of wavelet and wavelet packet transforms can improve the analysis and compression speed significantly.

In this paper, a hybrid evolutionary algorithm based on Binary Particle Swarm Optimization (BPSO) and Genetic Algorithm (GA) is proposed to compute the minimal hitting sets in model-based diagnosis. And a minimal assurance strategy is proposed to ensure that the final output of algorithm is the minimal hitting sets. In addition, the logistic mapping of chaos theory is adopted to avoid the local optimum. The high efficiency of new algorithm is proved through comparing with other algorithms for different problem scales. Additionally, the new algorithm with logistic mapping could improve the realization rate to almost 100% from 96%. At last, the new algorithm is used in the model-based fault diagnosis of traction substation. The results show that the new algorithm makes full use of the advantages of GA and BPSO and finds all the minimal hitting sets in 0.2369s, which largely meet the real-time requirement of fault diagnosis in the traction substation.

In this paper, the rough set theory is applied to reduce the complexity of data space and to induct decision rules. It proposes the generic label correcting (GLC) algorithm incorporated with the decision rules to solve supply chain modeling problems. This proposed approach is agile because by combining various operators and comparators, different types of paths in the reduced networks can be solved with one algorithm.