An Improved Adaptive Clone Genetic Algorithm for Task Allocation Optimization in ITWSNs

Research on intelligent transportation wireless sensor networks (ITWSNs) plays a very important role in an intelligent transportation system. ITWSNs deploy high-yield and low-energy-consumption traffic remote sensing sensor nodes with complex traffic parameter coordination on both sides of the road and use the self-organizing capabilities of each node to automatically establish the entire network. In the large-scale self-organization process, the importance of tasks undertaken by each node is different. It is not difficult to prove that the task allocation of traffic remote sensing sensors is an NP-hard problem, and an efficient task allocation strategy is necessary for the ITWSNs. This paper proposes an improved adaptive clone genetic algorithm (IACGA) to solve the problem of task allocation in ITWSNs. The algorithm uses a clonal expansion operator to speed up the convergence rate and uses an adaptive operator to improve the global search capability. To verify the performance of the IACGA for task allocation optimization in ITWSNs, the algorithm is compared with the elite genetic algorithm (EGA), the simulated annealing (SA), and the shuffled frog leaping algorithm (SFLA). The simulation results show that the execution performance of the IACGA is higher than EGA, SA, and SFLA. Moreover, the convergence speed of the IACGA is faster. In addition, the revenue of ITWSNs using IACGA is higher than those of EGA, SA, and SFLA. Therefore, the proposed algorithm can effectively improve the revenue of the entire ITWSN system.

Structural Formability of ABO3-Type Perovskite Compounds: Bond Valence Analysis

On the basis of a total of 382 ABO3-type compounds, the structural formability of ABO3-type perovskite compounds is investigated by using the bond valence model method. A new two-dimensional structural map approach for predicting the formability of ABO3-type perovskite compounds that relies on the ideal bond distances with the combination of bond valence parameter, coordination number and oxidation state is proposed. The sample points representing compounds of forming perovskite and non-perovskite are distributed in distinctively different regions. Some misclassified compounds are analyzed and some new compounds are tested within the new structure map. The developed approach can be used to search for new perovskite and perovskite-related compounds by screening all possible elemental combinations.

The Coordination and Optimization Study of PSS Parameters of Multiple Generators

For the parameter coordination and optimization of PSS in a multi-machine power system, this paper proposes a new method based on the Phillips-Heffron model to search the optimal install locations of PSS, which employs the sensitivity of the system eigenvalue to the PSS gain as the indicator of its install location, i.e. the larger this sensitivity is, the more the system damping can be improved effectively when the PSS is installed at the corresponding generator. Moreover, based on the block matrix theory and the Newton-Raphson iterative algorithm, the proposed method optimizes the parameters of multiple PSS, where the unknown parameters of each PSS is incorporated into the system state equations and solved by the Newton-Raphson iterative algorithm. Such a method takes the interaction among multiple PSS into account, so that the parameters of multiple PSS can be optimally coordinated. The proposed method is applied to the Sichuan Power Grid under different operating modes, and engineering practices shows that the proposed method is effective and robust.