Applied Mechanics and Materials Vols. 433-435

Abstract: In order to obtain accurate Compressive Sensing UWB (CS-UWB) channel estimation coefficients, a method of constructing adaptive sensing matrix is proposed via incoherence criterion, making the greedy reconstruction algorithms obtain optimal atoms from redundancy dictionary. The modified OMP algorithm without a prior of sparsity and SNR information is also presented for convenient using. Simulation results show that much improvement on UWB channel estimation is obtained based on the adaptive sensing matrix using the proposed algorithm.

Abstract: Through analyzing prior conditional probability of signal reconstruction in compressed sensing, the paper puts forward an improved method toward serials greedy pursuit algorithms. This method can achieve more accurate selection when select columns in perception matrix that is the most correlated with the residual. Meanwhile, this paper reviews most of greedy pursuit algorithms, and simulations validate the efficacy of the proposed method.

Abstract: The discovery of public opinion hotspot is an important aspect of public opinion research, and because many similarities and relevance exist between hot topics, we propose a hot topic clustering algorithm to find the hotspot in public opinions. Since fuzzy set can handle non-precision data well, the fuzzy algorithm can reduce the influences of the uncertainty of public opinion data. Based on LDA topic extraction we cluster the topical words by fuzzy method, and take the topic probability as word membership to the cluster. It can reduce the noise data and improve the ability of hotspot discovery that aggregate the similar and related topic to one class. The topical key words with high probability in cluster are the hotspot, and singular cluster with few words can be looked as outlier. The algorithm is demonstrated by example analysis in detail.

Abstract: Intelligent diagnosis technology has been one of the hotspot researches with the artificial neural net. Anti-lock braking system (ABS) is an important safety device of automobile. In this paper, using BP neural net, established the fault diagnosis neural net model of ABS, training and diagnosing the net by the fault samples. The results show that this method is feasible. The simulation is done by using MATLAB.

Abstract: This paper presents a novel decoding algorithm for bit-interleaved coded modulation iterative decoding (BICM-ID) embedded turbo codes. It can yield good bit error rate (BER) performance with much lower complexity. The improved algorithm exploits a linear interpolation and optimal mean square approximation function to replace the logarithmic correction in the Jacobian logarithmic function based on the MacLaurin Series, which avoids complicated logarithm look-up table operations in Log-MAP. Simulation results show that the novel algorithm obtains can offer almost equivalent performance to the optimal algorithm. Compared with the improved MAX-Log-MAP algorithm, the proposed algorithm can reduce about 34% of computational complexity, meanwhile it achieves 0.1db-0.16db performance gains.

Abstract: Cellular genetic algorithm (cGA) is a subclass of genetic algorithm (GA) in which the population diversity and exploration are enhanced thanks to the existence of small overlapped neighborhoods. Such a kind of structured algorithms is specially well suited for complex problems. Shop scheduling problem is a kind of problem with practical significance, and it belongs to a combinational optimization problem called NP-hard problem. In this paper we establish the model of job-shop problem (JSP) and solve the job-shop scheduling problem with cGA and traditional genetic algorithms (sGA).From the experimental results and analysis, we find cGA has better search efficiency and convergence performance than sGA.

Abstract: The heat exchange station of centralized heating system has the characteristics of large time delay and large lag which will affect the heating quality directly. Furthermore, a scheme of temperature control system of heat exchange station based on intelligent three-states Pang-Pang is designed .It chooses the average temperature of supply and return water in secondary network as the controlled parameters is based on mechanism analysis. Actual control effect shows that the scheme improves the controllability of the system. It not only decreases the overshoot but also improves the heating quality especially has the referential and extending significance for heat exchange station transforming open loop to closed-loop control.

Abstract: Multi-objective cellular genetic algorithm is obviously superior to the traditional multi-objective evolutionary algorithms in terms of testing performance of algorithm. However, the algorithm still needs to be used in practical engineering problems. In consideration of the above, this paper tries to apply the multi-objective cellular genetic algorithm to solve the problem of design of I-beam. Finally, the results show that multi-objective cellular genetic algorithm has more advantages than the traditional multi-objective evolutionary algorithms in solving this kind of multi-objective problems, no matter in uniformity or expansibility of best solutions.

Abstract: This paper mainly studies on the optimization and algorithm of multimodal transport path. The algorithm considered the transportation time, freight, the different transport ways, and the possibility of occurrence of facelift premise between each node. All of this determined the best path and the mixture of intermodal transport, which minimize the total freight fee. Take the complexity of multimodal optimization into account, this paper optimized the genetic algorithm to transport scheme. The certain population of crossover and mutation rules in application will continue to evolve by coding each path, finally achieve the solution of concrete steps.

Abstract: For studying the sensitivity of PSO to control parameter choices, this paper proposes a special model of PSO theoretically. This model divides the position sequence of particle into the odd and even sub-sequences. The theorem demonstrates the position sequence of particle is affected by the parameter choices, the initialized position and velocity. Simulations for benchmark functions illustrate the validity of the odd-even property of particle trajectory.