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51.
基于GA-BP的汽车风振噪声声品质预测模型 总被引:1,自引:1,他引:0
目前对于汽车风振噪声的优化研究主要以声压级(Sound pressure level,SPL)作为单一评价指标,既不能全面反映噪声的物理属性,也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声,引入声品质,运用大涡模拟(Large eddy simulation,LES)对风振噪声进行数值仿真,根据实车道路试验判断仿真的准确性;对仿真结果进行声品质客观评价与主观评价,综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型;利用遗传算法(Genetic algorithm,GA),进一步对BP神经网络的结构参数进行优化,建立GA-BP声品质预测模型。研究结果表明,GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果,其预测值可以代替传统的声压级评价指标,为风振噪声提供更为准确合理的评价。 相似文献
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本文使用Prophet人工智能算法研究与预测移动通信网络“潮汐效应”现象,探索网络“潮汐效应”在优化网络资源配置实现网络降本增效的作用。Prophet人工智能算法是一种简单、有效,且易于实现的人工智能算法。通过facebook的人工智能开源框架fbprophet,研究4G网络PRB利用率等网络资源指标的“潮汐效应”,并预测这些网络资源指标在未来的变化趋势,用来指导当前4G网络减容、扩容和4/5G节电节能等,实现优化网络资源配置达到降本增效的目的。 相似文献
54.
针对人工进行珍珠形状分拣效率低、精度不稳定等问题,提出基于机器视觉的珍珠形状检测方法;采用背光成像方式消除珍珠表面纹理和光泽的影响,对获取的珍珠图像进行同态滤波等预处理算法,提高图像对比度;为了解决相互接触珍珠影响珍珠轮廓提取的问题,采用分水岭算法对珍珠图像进行分割,得到了独立存在的珍珠个体,再通过连通域标记、质心算法对珍珠进行定位;根据国家标准对珍珠形状的规定,基于珍珠图像信息建立珍珠形状参数模型,对珍珠形状进行量化;实验结果表明,不同形状的珍珠样本的检测误差为0.63%,形状统计精度为100%,算法耗时24 ms;该方法可准确高效地对珍珠进行分拣分级,具有一定的实用价值。 相似文献
55.
为了解决合闸过程中动、静触头接触引起的振动弹跳问题.本文建立了接触系统的二自由度运动微分方程,并利用遗传算法对交流接触器吸合过程进行优化,同时通过高速摄影实验对接触弹跳的全过程进行了观察和分析.结果表明:理论与实验结果高度一致,铁心在触头分离前发生碰撞,进一步加剧触头弹跳;铁芯弹跳再次碰撞时,触头的弹跳不受影响;在接触器运行过程中,动铁芯的运动会引起系统轻微振动;采用遗传算法优化的接触器触头弹跳时间和最大振幅均减小.研究结果为进一步控制和减小接触弹跳提供了理论依据. 相似文献
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Zhi Li Wenju Wang Meng Ye Xuedong Liang 《International Journal of Hydrogen Energy》2021,46(35):18453-18465
Lack of hydrogen refueling stations (HRSs) has hindered the diffusion of hydrogen fuel cell vehicles (HFCVs) in the Chinese transport market. By combining the agent-based model (ABM) and the experience weighted attraction (EWA) learning algorithm, this paper explores the impact of government subsidy strategy for HRSs on the market diffusion of HFCVs. The actions of the parties (government, HRS planning department and consumers) and their interactions are taken into account. The new model suggests dynamic subsidy mode based on EWA algorithm yields better results than static subsidy mode: HFCV purchases, HRS construction effort, total number of HRSs and expected HRS planning department profits all outperform static data by around 27%. In addition, choosing an appropriate initial subsidy strategy can increase the sales of HFCVs by nearly 40%. Early investment from government to establish initial HRSs can also increase market diffusion efficiency by more than 76.7%. 相似文献
58.
The uncertainty associated with modeling and performance prediction of solar photovoltaic systems could be easily and efficiently solved by artificial intelligence techniques. During the past decade of 2009 to 2019, artificial neural network (ANN), fuzzy logic (FL), genetic algorithm (GA) and their hybrid models are found potential artificial intelligence tools for performance prediction and modeling of solar photovoltaic systems. In addition, during this decade there is no extensive review on applicability of ANN, FL, GA and their hybrid models for performance prediction and modeling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modeling, maximum power point tracking, fault detection and output power/efficiency prediction of solar photovoltaic systems using artificial intelligence techniques of the ANN, FL, GA and their hybrid models. In addition, the selected articles on the solar radiation prediction using ANN, FL, GA and their hybrid models are also summarized. Total of 122 articles are reviewed and summarized in the present review for the period of 2009 to 2019 with 90 articles in the field of {ANN, FL, GA and their hybrid models} + solar photovoltaic systems and 32 articles in the field of {ANN, FL, GA and their hybrid models} + solar radiation. The review shows the suitability and reliability of ANN, FL, GA and hybrid models for accurate prediction of the solar radiation and the performance characteristics of solar photovoltaic systems. In addition, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable prediction tool for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation. 相似文献
59.
Mohammadali Kiehbadroudinezhad Ali Rajabipour Michael Cada Majid Khanali 《国际能源研究杂志》2021,45(1):429-452
People in the Middle East are facing the problem of freshwater shortages. This problem is more intense for a remote region, which has no access to the power grid. The use of seawater desalination technology integrated with the generated energy unit by renewable energy sources could help overcome this problem. In this study, we refer a seawater reverse osmosis desalination (SWROD) plant with a capacity of 1.5 m3/h used on Larak Island, Iran. Moreover, for producing fresh water and meet the load demand of the SWROD plant, three different stand‐alone hybrid renewable energy systems (SAHRES), namely wind turbine (WT)/photovoltaic (PV)/battery bank storage (BBS), PV/BBS, and WT/BBS are modeled and investigated. The optimization problem was coded in MATLAB software. Furthermore, the optimized results were obtained by the division algorithm (DA). The DA has been developed to solve the sizing problem of three SAHRES configurations by considering the object function's constraints. These results show that this improved algorithm has been simpler, more precise, faster, and more flexible than a genetic algorithm (GA) in solving problems. Moreover, the minimum total life cycle cost (TLCC = 243 763$), with minimum loss of power supply probability (LPSP = 0%) and maximum reliability, was related to the WT/PV/BBS configuration. WT/PV/BBS is also the best configuration to use less battery as a backup unit (69 units). The batteries in this configuration have a longer life cycle (maximum average of annual battery charge level) than two other configurations (93.86%). Moreover, the optimized results have shown that utilizing the configuration of WT/PV/BBS could lead to attaining a cost‐effective and green (without environmental pollution) SAHRES, with high reliability for remote areas, with appropriate potential of wind and solar irradiance. 相似文献
60.
Bo Yang Chunyuan Zeng Long Wang Yinyuan Guo Guanghua Chen Zhengxun Guo Yijun Chen Danyang Li Pulin Cao Hongchun Shu Tao Yu Jiawei Zhu 《International Journal of Hydrogen Energy》2021,46(44):22998-23012
It is essential to develop an accurate model of proton exchange membrane fuel cell (PEMFC) for a reliable operation and analysis, in which unknown parameters usually need to be determined. The inherent nonlinear, strong coupling, and diversification of PEMFC model seriously hinder traditional methods to identify the parameters. For the sake of overcoming these thorny obstacles, Levenberg-Marquardt backpropagation (LMBP) algorithm based on artificial neural networks (ANNs) is proposed for PEMFC parameter identification. Furthermore, the performance of LMBP is thoroughly evaluated and compared with four typical meta-heuristic algorithms under three cases. Simulation results indicate that LMBP performs a higher accuracy and faster speed for parameter identification. In particular, accuracy and convergence speed can achieve as much as 99.8% and 95.9% growth via LMBP, respectively. 相似文献