期刊：
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT,2020年234(10):1117-1128 ISSN：0954-4097
通讯作者：
Zhou, Hui
作者机构：
[Wang, Da; Xie, Suchao; Feng, Zhejun; Zhou, Hui; Du, Xuanjin] Cent South Univ, Key Lab Traff Safety Track, Minist Educ, Changsha, Hunan, Peoples R China.;[Wang, Da; Xie, Suchao; Feng, Zhejun; Zhou, Hui; Du, Xuanjin] Joint Int Res Lab Key Technol Rail Traff Safety, Changsha, Hunan, Peoples R China.;[Wang, Da; Xie, Suchao; Feng, Zhejun; Zhou, Hui; Du, Xuanjin] Cent South Univ, Sch Traff & Transportat Engn, 22 South Shaoshan St, Changsha 410083, Hunan, Peoples R China.;[Zhou, Hui] Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha, Hunan, Peoples R China.
通讯机构：
[Zhou, Hui] C;Cent South Univ, Sch Traff & Transportat Engn, 22 South Shaoshan St, Changsha 410083, Hunan, Peoples R China.
关键词：
Train collision;dynamics analysis;energy absorbing device;finite element analysis;crashworthiness
摘要：
In this study, the crashworthiness of a subway train was assessed by establishing a finite element model for the first three carriages of the train and the track using the Hypermesh software. By utilising the *MAT_HONEYCOMB material model, a honeycomb in an anti-climbing energy-absorbing device was simulated. Moreover, the process of a subway train - travelling at a speed of 25 km/h - colliding with another identical train in a stationary and non-braking state was simulated by employing the finite element analysis software Hypermesh and LS-DYNA. The process of simulation analysis was divided into two parts: (1) analysis of the anti-climbing energy-absorbing devices under static compression for the investigation of energy absorption and (2) collision analysis of the whole train. The contributions of the proposed energy-absorbing structure - at the end of driver's cab, the coupler and draft gears on each section - to the overall energy absorption in a train collision were calculated. Furthermore, based on the EN15227 standard, the crashworthiness of the train with respect to the survival space for occupants, train acceleration and uplift of wheels relative to the track was evaluated. The coupler of the first carriage fails in a collision at 25 km/h, and the coupler and draft gear are the main energy-absorbing devices. *MAT_HONEYCOMB was used to define the honeycomb materials in anti-climbing energy-absorbing devices and could simulate the mechanical performance thereof. The crashworthiness of the train meets the relevant standard requirements.
作者机构：
[Chen Qun; Pan Shuangli] Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.;[Pan Shuangli] Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha 410004, Peoples R China.;[Zheng Guijun] Cent South Univ Forestry & Technol, Sch Business, Changsha 410004, Peoples R China.
通讯机构：
[Chen Qun] C;Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.
关键词：
give up driving;parking constraints;psychological factors;theory of planned behavior;structural equation model
摘要：
Parking restrictions can affect the use of cars and become an effective means to promote the sustainable development of urban traffic. To understand the influencing factors of car owners giving up driving due to parking constraints, the research constructs a theoretical model of psychological decision process about giving up driving under parking constraints, based on the Theory of Planned Behavior (TPB), and taking the public transit perception as a mediating variable, considering psychological factors. The empirical data were used to verify and modify the model by the Structural Equation Model (SEM) method, and finally the model was determined. The result shows that the choice of travel mode under the constraint of parking berth is not only affected by individual social and economic attributes and travel mode characteristics, but also by psychological latent variables such as behavioral attitude, subjective norms, perceived behavior control, public transportation perception and behavior intention. The subjective norms of car owners about giving up driving have a positive effect on perceived behavioral control and behavioral attitude; perceived behavior control also has an effect on behavior attitude; the behavior attitudes, subjective norms and perceived behavior control all have positive effects on the behavior intention of giving up driving due to parking constraints, among which public transit perception plays a positive adjustable intermediary role. The Integration of Choice and Latent Variable (ICLV) model considering psychological latent variables has a higher fitting degree to empirical data than the traditional Multinomial Logit (MNL) model. Based on the analysis results, some suggestions for auxiliary measures to implement the optimization strategy of parking supply are put forward.
摘要：
Effectively balancing the convergence and diversity in dynamic environments is a challenging task. In order to handle the issue, this paper proposes a novel prediction strategy based on change degree of decision variables for dynamic multi-objective optimization (CDDV), which has the ability to detect the change degree in the decision space and design the different prediction strategy to make the population adapt to the new environment. The proposed method can adaptively increase population diversity according to the analysis of change degree, when an environmental change is detected. In order to study the efficacy and usefulness of the novel change degree on evolutionary algorithms, a range of dynamic multi-objective benchmark problems are selected to evaluate the performance of the proposed algorithm. The results demonstrate the effectiveness of proposed algorithm in compared with four other state-of-the-art methods.
摘要：
This paper presents an experimental study on an integrated agile earth observation satellite (AEOS) scheduling problem involving the satellite memory environments of the partially erasable memory (PEM) and the holistically erasable memory (HEM). The integrated AEOS scheduling problem simultaneously considers the satellite observation and transmission events, in which the onboard memory functions as a very important connective resource. To address the memory constraints in the AEOS scheduling problem, an integrated AEOS scheduling model that is suitable for both the PEM and HEM environments is proposed in this paper. Based on commonly used construction heuristic and meta-heuristics, two hybrid approaches, Tabu-simulated annealing (TSA) and Tabu late acceptance (TLA) algorithms, are adopted to solve this problem. The highlights in this paper are the formulation of novel adaptive memory constraints for the AEOS scheduling and the quantitatively scheduling comparison of separated and integrated modeling methods. Experimental results indicate that (1) the memory environment has a direct influence on the AEOS integrated scheduling results, where the PEM environment sufficiently utilizes memory resources and advances the efficiency of the AEOS a lot. (2) The integrated scheduling method enables the reduction in resource consumption and obtains a better result than the separated scheduling method, especially in the HEM environment, (3) and the hybrid meta-heuristics TLA and TSA that show better overall performance are suggested for addressing the studied AEOS integrated scheduling problem.
摘要：
Although hyperspectral remote sensing images have rich spectral features, for small samples of remote sensing images, feature selection, feature mining, and feature integration are very important. A single model is difficult to apply to multiple tasks such as feature selection, feature mining, and feature integration during training, resulting in poor classification results for small sample classification of hyperspectral images. To improve the classification of small samples, a sequential joint deep learning algorithm is proposed in this paper. (In this algorithm, the deep features of multiscale convolution under an attention mechanism are integrated by using Bidirectional Long Short-Term Memory(Bi-LSTM) and AML.) First, we used principal component analysis (PCA) to reduce the dimensionality of the hyperspectral data and retain their key features. Second, the model uses an integrated attention mechanism to distribute the probability weight of the key input feature. Third, the model uses multiscale convolution to mine features after the distribution weight to obtain deep features. Fourth, the model uses bidirectional long short-term memory (Bi-LSTM) to integrate the convolution results at different scales. Finally, the softmax classifier is used to complete the classification of multiclass hyperspectral remote sensing images. Experiments were carried out on three public hyperspectral data sets, and the results proved that our proposed AML algorithm is effective, thus demonstrating powerful performance in the prediction of hyperspectral images (HSIs) of small samples.
摘要：
Data streams are characterized by high volatility, and they drastically change in an unpredictable way over time. In the typical case, newer data are the most important, as the concept of aging is based on their timing. These flows require real-time processing in order to extract meaningful information that will allow for essential and targeted responses to changing circumstances. Knowledge mining is a real-time process performed on a subset of the data streams, which contains a small but recent part of the observations. Timely security requirements call for further quest of optimal approaches, capable of improving the reliability and the accuracy of the employed classifiers. This research introduces a real-time evolving spiking restricted Boltzmann machine approach, for efficient anomaly detection in data streams. Testing has proved that the proposed algorithm maximizes the classification accuracy and at the same time minimizes the computational resources requirements. A comparative analysis has shown that it outperforms other data flow analysis algorithms.
