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1.
Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics. 相似文献
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Islamic financial institutions are being pressurized by critics to offer profit and loss sharing (PLS) financing, such as venture capital (VC) financing, for the purpose of entrepreneurial development aligned to the principle of equity risk sharing. Our study aims to link PLS investments with portfolio optimization opportunities for the Islamic asset managers. Using portfolio analysis with dynamic conditional correlation, Markov switching, and maximal overlap discrete wavelet transformation, our findings tend to indicate that there is indeed a portfolio optimization opportunity in investment universe for the fund managers who invested in PLS investments in the context of VC asset class over the long run. 相似文献
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为了解决宏蜂窝与飞蜂窝构成的两层异构网络上行干扰与资源分配问题,提出了一种在认知型飞蜂窝的双层异构网中结合子信道分配和功率控制进行资源分配的框架。通过对异构网中跨层干扰问题进行分析与建模,将求解最优子信道分配矩阵和用户发射功率矩阵作为干扰管理问题的解决方法。模型中认知型飞蜂窝网络子信道和飞蜂窝网络用户构成非合作博弈,双方利用效用函数最优值进行匹配,构成初始信道分配矩阵;再由接入控制器根据接入条件从初始信道分配矩阵中筛选用户,并优化接入用户的发射功率矩阵,得到最优子信道分配矩阵和功率矩阵。仿真结果表明,优化框架提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网中跨层干扰。 相似文献
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This study examines the relationship between oil prices and economic activity in the G-7 economies during the period 1960M1–2014M07 using a wavelet approach. The results show significant differences in the relationship between these two variables depending on the frequencies. Furthermore, we find that oil price shocks affect economic activity at low frequencies (long run) in all G-7 countries, while the effect at high frequencies (short run) is limited to a few countries. 相似文献
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《Bulletin of economic research》2018,70(1):E29-E49
This paper examines co‐movement between stock returns and changes in 10‐year government bond yields as well as flight‐to‐quality behaviour in G7 countries. We conduct the wavelet squared coherence analysis to explore the dynamics in both time and frequency domain. Our results provide evidence of positive co‐movements, which vary over time and across investment horizon. The higher co‐movement is found to be more concentrated in the lower frequency bands. We further analyse the dynamic nature of the scale‐dependent wavelet correlations and find that the correlations are highly volatile and significantly increase across different time scales during the episodes of equity market turbulence. The increase in correlations reflects flights from stocks to safer bond investments as a result of dramatic changes in investor sentiment and risk aversion at times of market stress. 相似文献
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Cancellations are a key aspect of hotel revenue management because of their impact on room reservation systems. In fact, very little is known about the reasons that lead customers to cancel, or how it can be avoided. The aim of this paper is to propose a means of enabling the forecasting of hotel booking cancellations using only 13 independent variables, a reduced number in comparison with related research in the area, which in addition coincide with those that are most often requested by customers when they place a reservation. For this matter, machine-learning techniques, among other artificial neural networks optimised with genetic algorithms were applied achieving a cancellation rate of up to 98%. The proposed methodology allows us not only to know about cancellation rates, but also to identify which customer is likely to cancel. This approach would mean organisations could strengthen their action protocols regarding tourist arrivals. 相似文献
8.
地理信息系统(Geographic Information System,GIS)和多目标算法为异构网络基站部署问题带来新的突破。ArcGIS系列是GIS专业化的管理软件,采用ArcGIS软件对包含学校、医院等场景的中国某市密集城区进行建模分析,并且提出基于目标权重因子的多目标离散粒子群算法(Multi-objective Discrete Particle Swarm Optimization algorithm based on Target Weight Factor,MDPSO/TWF),基于多个目标函数整体最优研究异构网络基站部署问题。仿真结果表明,所提的MDPSO/TWF算法具有可行性和先进性,可以综合考虑网络负载和网络能效多个优化目标,将业务需求与实际基站选址相结合,在满足业务需求的基础上尽可能达到节能的目的。 相似文献
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维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。 相似文献
10.
火山灰云中的颗粒物能够降低能见度,损害航空器的飞行控制系统和机身,威胁飞行安全。火山灰云监测预警的研究对减少航空事故和经济损失具有很重要的作用。卫星遥感方法能有效地监测火山灰云,逐渐成为火山灰云监测的主要手段。介绍监测火山灰云的传感器类型和卫星遥感监测火山灰云的常用方法,并总结了对这些方法在实际运用中的优缺点,重点介绍了美国的ABI-VAA(高级基线成像火山灰算法)。 相似文献