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1.
The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems. 相似文献
2.
对射频电缆幅相稳定性进行了介绍,阐述了射频测试电缆相位和幅度变化的因素,并详细分析了射频电缆相位性能以及幅度性能的不同测试方法,最后通过实测数据的展示,总结说明了在日常测试中该如何正确使用测试电缆。 相似文献
3.
Recently, many researchers have concentrated on distant supervision relation extraction (DSRE). DSRE has solved the problem of the lack of data for supervised learning, however, the data automatically labeled by DSRE has a serious problem, which is class imbalance. The data from the majority class obviously dominates the dataset, in this case, most neural network classifiers will have a strong bias towards the majority class, so they cannot correctly classify the minority class. Studies have shown that the degree of separability between classes greatly determines the performance of imbalanced data. Therefore, in this paper we propose a novel model, which combines class-to-class separability and cost-sensitive learning to adjust the maximum reachable cost of misclassification, thus improving the performance of imbalanced data sets under distant supervision. Experiments have shown that our method is more effective for DSRE than baseline methods. 相似文献
4.
5.
Vector vortex beams (VVBs) possess ubiquitous applications from particle trapping to quantum information. Recently, the bulky optical devices for generating VVBs have been miniaturized by using metasurfaces. Nevertheless, it is quite challenging for the metasurface-generated VVBs to possess arbitrary polarization and phase distributions. More critical is that the VVBs' annular intensity profiles demonstrated hitherto are dependent on topological charges and are hence not perfect, posing difficulties in spatially shared co-propagation of multiple vortex beams. Here, a single-layer metasurface to address all those aforementioned challenges in one go is proposed, which consists of two identical crystal-silicon nanoblocks with varying positions and rotation angles (i.e., four geometric parameters throughout). Those four geometric parameters are found to be adequate for independent and arbitrary control of the amplitude, phase, and polarization of light. Perfect VVBs with arbitrary polarization and phase distributions are successfully generated, and the constant intensity profiles independent of their topological charges and polarization orders are demonstrated. The proposed strategy casts a distinct perception that a minimalist design of just one single-layer metasurface can empower such robust and versatile control of VVBs. That provides promising opportunities for generating more complex vortex field for advanced applications in structural light, optical micromanipulation, and data communication. 相似文献
6.
Massive Open Online Course (MOOC) has become a popular way of online
learning used across the world by millions of people. Meanwhile, a vast amount of
information has been collected from the MOOC learners and institutions. Based on the
educational data, a lot of researches have been investigated for the prediction of the
MOOC learner’s final grade. However, there are still two problems in this research field.
The first problem is how to select the most proper features to improve the prediction
accuracy, and the second problem is how to use or modify the data mining algorithms for
a better analysis of the MOOC data. In order to solve these two problems, an improved
random forests method is proposed in this paper. First, a hybrid indicator is defined to
measure the importance of the features, and a rule is further established for the feature
selection; then, a Clustering-Synthetic Minority Over-sampling Technique (SMOTE) is
embedded into the traditional random forests algorithm to solve the class imbalance
problem. In experiment part, we verify the performance of the proposed method by using
the Canvas Network Person-Course (CNPC) dataset. Furthermore, four well-known
prediction methods have been applied for comparison, where the superiority of our
method has been proved. 相似文献
7.
ABSTRACTSocial licence to operate (SLO) is a term that is finding increasing acceptance in a number of industries. Like all new terms, its precise meaning and implications are still being investigated. Using data from previous studies, this paper offers an analysis of the SLO of two case studies with each study being viewed separately through the grid of a distinct theoretical framework. Case study 1 looks at the development of differential social licence negotiated in the Hamlet of Cambridge Bay, Nunavut, as a result of an impact and benefit agreement negotiated between Tahera Diamond Corp. and the Kitikmeot Inuit Organisation in 2004. The study demonstrates that general acceptance of resource development can be uneven and reflect an unequal distribution of decision-making power. In case study 2, stakeholders of a failed mineral development project were queried across time about the specifics of the proposed mine development and were queried about resource development across different levels of consciousness. Perhaps, SLO is variable across different levels of consciousness. The paper concludes with observations about the variable nature of SLO acceptance across populations and across levels of consciousness within individuals. Perhaps, the concept of SLO is, in fact, complex, difficult to define and measure and, at this point, of limited utility as a measure of resource development acceptance. 相似文献
8.
The present paper provides an extended analysis of a microgrid energy management framework based on Robust Optimization (RO). Uncertainties in wind power generation and energy consumption are described in the form of Prediction Intervals (PIs), estimated by a Non-dominated Sorting Genetic Algorithm (NSGA-II) – trained Neural Network (NN). The framework is tested and exemplified in a microgrid formed by a middle-size train station (TS) with integrated photovoltaic power production system (PV), an urban wind power plant (WPP) and a surrounding residential district (D). The system is described by Agent-Based Modelling (ABM): each stakeholder is modeled as an individual agent, which aims at a specific goal, either of decreasing its expenses from power purchasing or increasing its revenues from power selling. The aim of this paper is to identify which is the uncertainty level associated to the “extreme” conditions upon which robust management decisions perform better than a microgrid management based on expected values. This work shows how the probability of occurrence of some specific uncertain events, e.g., failures of electrical lines and electricity demand and price peaks, highly conditions the reliability and performance indicators of the microgrid under the two optimization approaches: (i) RO based on the PIs of the uncertain parameters and (ii) optimization based on expected values. 相似文献
9.
10.
针对宽带调制解调技术中广泛存在的IQ不平衡问题,在IQ不平衡模型及补偿原理的分析基础上提出了一种宽带数字接收机IQ不平衡估计与自适应补偿算法。首先利用解调数据对IQ不平衡参数进行实时估计,然后利用估计参数对接收信号进行自适应补偿。实验结果表明,所提算法可以有效解决宽带调制解调系统中普遍存在的IQ不平衡问题,提升系统误码性能。 相似文献