大数据分析在电价执行情况监测中的预测与优化策略

本文聚焦于大数据分析在电价执行情况监测中的预测与优化策略,以探讨纯技术类应用。随着电力行业的不断发展和电力需求的增长,电价的执行情况监测变得至关重要。本文使用真实数据,通过大数据分析方法,提出了一种高效的电价执行情况预测与优化策略,以实现电力系统的有效管理和资源优化利用。本文的主论点是,大数据分析在电价执行情况监测中为电力技术领域提供了重要的工具和方法,可用于优化电力资源的分配和提高电网的稳定性。

Hybrid optimization model and its application in prediction of gas emission

According to the complex nonlinear relationship between gas emission and its effect factors, and the shortcomings that basic colony algorithm is slow, prone to early maturity and stagnation during the search, we introduced a hybrid optimization strategy into a max-rain ant colony algorithm, then use this improved ant colony algorithm to estimate the scope of RBF network parameters. According to the amount of pheromone of discrete points, the authors obtained from the interval of net- work parameters, ants optimize network parameters. Finally, local spatial expansion is introduced to get further optimization of the network. Therefore, we obtain a better time efficiency and solution efficiency optimization model called hybrid improved max-min ant system （H1-MMAS）. Simulation experiments, using these theory to predict the gas emission from the working face, show that the proposed method have high prediction feasibility and it is an effective method to predict gas emission.

Two-stage prediction and update particle filtering algorithm based on particle weight optimization in multi-sensor observation

The reasonable measuring of particle weight and effective sampling of particle state are consid- ered as two important aspects to obtain better estimation precision in particle filter. Aiming at the comprehensive treatment of above problems, a novel two-stage prediction and update particle filte- ring algorithm based on particle weight optimization in multi-sensor observation is proposed. Firstly, combined with the construction of muhi-senor observation likelihood function and the weight fusion principle, a new particle weight optimization strategy in multi-sensor observation is presented, and the reliability and stability of particle weight are improved by decreasing weight variance. In addi- tion, according to the prediction and update mechanism of particle filter and unscented Kalman fil- ter, a new realization of particle filter with two-stage prediction and update is given. The filter gain containing the latest observation information is used to directly optimize state estimation in the frame- work, which avoids a large calculation amount and the lack of universality in proposal distribution optimization way. The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.

Stability Control and Simulation Experiments of Biped Humanoid Robot Walking on Rough Terrains

In this paper, we provide several methods to solve the problem of humanoid robot walking on rough terrains. By using the Passive Inverted Pendulum Model（PIPM） and predictive control, with some optimizing strategy added, we realized the smooth walking on a slope with rocks on it.

利用通行能力余量的智能网联车队生态驾驶模型

针对非饱和城乡交通干道上存在通行能力余量和高燃油消耗的问题,提出一种利用通行能力余量的智能网联车队生态驾驶模型,该模型兼顾燃油经济性和通行能力两个目标,通过优化求解获取最优速度曲线,引导一系列小型车队平滑地通过非饱和城乡交通干道。提出近似的速度优化模型并采用遗传算法对其求解。定义3种控制方案对模型进行测试,仿真结果表明:与方案1相比,方案2燃油消耗量减少49.4%,通行能力增加200%,绿灯剩余时间减少14.7%;方案3燃油消耗量减少59.5%,通行能力增加200%,绿灯剩余时间减少23.5%。与方案2相比,方案3可以在不影响通行能力的前提下,通过绿灯剩余时间缩短10.3%和平均速度降低5.2%,燃油消耗量可以减少20%。结果表明,当信号交叉口存在通行能力余量时,可以通过调整车辆的行驶速度曲线以充分利用通行能力余量,明显改善燃油经济性。