Spatiotemporal Coupling Research Articles

A Virtual Data Collection Model of Distributed PVs considering Spatio-Temporal Coupling and Affine Optimization Reference

The rapid development of distributed photovoltaic (DPV) made the shortage of data transmission channels and the difficulty of comprehensive coverage of measurement equipment becoming more significant. To enable a high-precision data collection of DPVs with fewer sensory devices and low computation costs, this paper proposes a virtual collection technology based on computational intelligence. To capture the spatial-temporal correlation of DPVs and find the optimal reference power station (RPS), a deep recurrent denoising autoencoder (D-RDAE)-based model is proposed in this paper. An affine artificial neural network (AANN) is constructed to tackle the uncertainty of solar radiation intensity and select RPSs. To address the high-dimensionality RPS selection, an improved honey badger algorithm (IHBA) with enhanced global search ability is proposed. The operation data of 33 DPVs in Nanjing, China, are used to train and verify the proposed method. The experimental results showed the effectiveness and superiority of the proposed method. Compared with DAE and RDAE, the deeply trained D-RDAE has the best capacity for finding the spatial-temporal correlation of DPVs. In addition, IHBA has the best global search ability compared with other 4 optimizers, and the AANN can better reduce the uncertainty of solar radiation intensity than robust and stochastic optimization techniques.

Ultra-compact post-compressor on-shot wavefront measurement for beam correction at PHELIX

Abstract In order to reach the highest intensities, modern laser systems use adaptive optics to control their beam quality. Ideally, the focal spot is optimized after the compression stage of the system in order to avoid spatio-temporal couplings. This also requires a wavefront sensor after the compressor, which should be able to measure the wavefront on-shot. At PHELIX, we have developed an ultra-compact post-compressor beam diagnostic due to strict space constraints, measuring the wavefront over the full aperture of 28 cm. This system features all-reflective imaging beam transport and a high dynamic range in order to measure the wavefront in alignment mode as well as on shot.

Spatio-temporal coupling relationship between territory spatial utilization efficiency and high-quality development in Wanjiang City Belt

Spatio-temporal coupling relationship between territory spatial utilization efficiency and high-quality development in Wanjiang City Belt

长三角城市群城市空间形态与碳收支时空耦合关系

长三角城市群城市空间形态与碳收支时空耦合关系

Single-frame measurement of complete spatiotemporal field of ultrashort laser pulses using frequency domain separate spectral interferometry

The spatiotemporal coupling distortion of large aperture ultra-high peak power laser will degrade the pulsed beam in both near-field and far-field. To accurately predict the light field distribution at the focus and compensate for the spatiotemporal coupling distortion, a single-frame measurement of full three-dimensional spatiotemporal coupling distortion is proposed based on the frequency domain separate spatial-spectral interference. The setup requires only a slit array attached to the front of an Imaging spectroradiometer. The whole procedure of carrier frequency distinguished spectral interference measurement is simulated in this study. The simulation results prove that the presented measuring method is correct and effective. The effectiveness of this method will be further verified experimentally in next step.

Attention-based 3DTCN-LSTM short-term network traffic prediction model considering multi-base station spatiotemporal coupling

Attention-based 3DTCN-LSTM short-term network traffic prediction model considering multi-base station spatiotemporal coupling

Influence of spatiotemporal coupling distortion on evaluation of pulse-duration-charactrization and focused intensity of ultra-fast and ultra-intensity laser

In a large-scale ultra-fast and ultra-intensity laser system, with the increase of spectral bandwidth and beam aperture, the spatiotemporal coupling distortion will become more and more significant. This effect will not only degrade the beam quality and reduce the focusing intensity of the laser, but also invalidate the conventional evaluation method for laser far-field parameters. A pair of beam-expanding lenses, which may bring spatiotemporal coupling distortion to an ultrashort laser pulse, is taken as an example. And the influence of spatiotemporal coupling distortion on laser parameter measurement is analyzed in detail. It shows that in an ultrashort pulse laser system, an ordinary beam-expanding lens-pair can reduce the far-field peak intensity dramatically, and the actual pulse duration in the far field is more than 10 times longer than that measured at the near field by a single-shot autocorrelator. In this case, the focusing intensity estimated by using the measured value of near-field pulse width will be one order of magnitude bigger than the real value. It is expected that the results will be helpful in the optimal design of a laser system, the accurate characterization of an ultrafast laser pulse and relevant physical experiments.

Flight Test Sensor Fault Diagnosis Based on Data-Fusion and Machine Learning Method

Fault diagnosis and classification (FDC) is an important part of prognostics and health management for ensuring safety and performance in the flight. However, it is challenging to achieve accurate FDC only based on single senor readings. In this paper, a fused FDC model among multiple different sensors is stabled by a hybrid deep learning architecture combining a sparse autoencoder (SAE) and a convolutional neural network (CNN). The hybrid model uses the SAE to enhance the hidden fault signal features in the multiple sensor signals, and then classifies the obtained feature map using the CNN. This method, which combines the advantages of the SAE in feature extraction and of the CNN in local feature recognition, fully utilizes the spatiotemporal coupling characteristics of multi-sensor signals. The FDC accuracy obtained by the proposed method when applied to a flight test data set is 93.78%, compared with 66.67% obtained using the combined SAE and feedforward neural network method and 83.11% obtained using the CNN only.

Investigating spatio-temporal characteristics and evaluation of heavy goods vehicle risky driving behaviours based on vehicle networking dataset during naturalistic driving

This study analysed the factors that affect vehicle warnings driving incidents caused by risky distracted driving behaviours of Heavy Goods Vehicles (HGV) drivers. The analysis was based on the natural driving networking dataset collected over a 6-month period and comprising 81 fleets made by 5396 HGV drivers in Guangdong, China. First, the spatio-temporal coupling characteristics of warning incidents on HGV risky driving behavior and various levels of roads were established. Then, a global Moran index was built to measure the comprehensive score of risky driving behaviour, based on which the safety level of driving behaviour of HGV drivers was assessed. Results showed that 50% of the HGV drivers tended to drive in a substantially dangerous driving way, and HGV drivers received the highest total number of driving warning events in September, with the dangerous warning types being mainly deviation or blocking cameras and smoking.

Attention-based 3DTCN-LSTM short-term network traffic prediction model considering multi-base station spatiotemporal coupling

Attention-based 3DTCN-LSTM short-term network traffic prediction model considering multi-base station spatiotemporal coupling

Coordinating multiple resources for enhancing distribution system resilience against extreme weather events considering multi-stage coupling

Under extreme weather events with a certain warning time, the prevention and restoration of distribution systems (DSs) involve multiple processes, including pre-event prevention, DS degradation, and post-event fault isolation and service restoration. Multiple resources are coupled and interact with each other in the above processes, which makes it a complicated task to develop resilience enhancement strategies for DSs. In this paper, a multi-resource DS resilience enhancement method is proposed to assist DS operators in making decisions against extreme weather events. On one hand, in the proposed method, the prevention and restoration of DSs are formulated as multiple stages based on the physical process of DSs when affected by extreme weather events. On the other hand, distributed generations (DGs), mobile emergency generators (MEGs), remote-controlled switches (RCSs), manual switches (MSs) and operation crew teams are fully coordinated to enhance the resilience of DSs against extreme weather events. And multiple coupling relationships are considered, including the topology coupling relationships among each stage, the spatiotemporal coupling relationships of mobile resources, and the switching coupling relationships between MSs and operation crew teams. The proposed method is mathematically formulated as a mixed-integer linear programming (MILP) model. Several cases are introduced to verify the effectiveness of the proposed method. The results demonstrate that the degradation of the DS can be effectively reduced by the coordination of network pre-reconfiguration and resources pre-positioning before events. The recovery process can be significantly speeded up by the coordination of the network reconfiguration and the real-time dispatching of MEGs and operation crew teams after events.

Spatial-Temporal Features of Coordination Relationship between Regional Urbanization and Rail Transit-A Case Study of Beijing.

Urban rail transit is an important transportation infrastructure that mitigates the congestion of the central city and realizes compact city space development. However, the literature on the spatiotemporal coupling of urbanization and rail transit from the urban scale and its influencing factors is still uncommon. Taking Beijing as an example, based on the theory of coupling coordination, we have constructed a comprehensive indicator system for regional urbanization (hereafter RU) (including population, economy, and spatial urbanization) and rail transit (hereafter RT). On this basis, we use the entropy method, coupling coordination degree model, and spatial autocorrelation analysis method to explore the spatiotemporal characteristics of the overall and pairwise coupling coordination between population, economy, spatial urbanization, and rail transit. Finally, we analyze the spatial correlation and standard deviational ellipse analysis of the coupling coordination degree between RU and RT. The results indicate the following: (1) In addition to population urbanization, the other urbanization indicators and the RT level all show a downward–rising–falling trend from 2006 to 2017, among which the level of economic urbanization is the highest. The degree of coupling coordination between RU and RT is unbalanced development and shows a trend of first rising and then falling. (2) The degree of coupling coordination between RU and RT presents an imbalanced distribution in various regions, and the coupling coordination degree in the central urban areas is significantly higher than that in the outer suburbs. (3) From 2006 to 2017, the spatial correlation of the coupling coordination degree between the various systems has a similar changing trend. Moreover, the distribution of the spatial agglomeration points of the coupling coordination degree between RU and the RT is similar, showing a decreasing trend from the central urban area to the surrounding urban area. Therefore, relevant departments can rationally plan the construction of urban rail transit according to the coordination relationship between RU and RT and the spatial aggregation degree to realize the benign and sustainable development between urban especially suburbanization and rail transit.

Spatio-Temporal Coupling Relationships between Rural Population and Farmland Change in Karst Mountainous Areas of Southwest China

Spatio-Temporal Coupling Relationships between Rural Population and Farmland Change in Karst Mountainous Areas of Southwest China

Multimode Mamyshev oscillator.

We present a spatiotemporally mode-locked Mamyshev oscillator. A wide variety of multimode mode-locked states, with varying degrees of spatiotemporal coupling, are observed. We find that some control of the modal content of the output beam is possible through the cavity design. Comparison of simulations with experiments indicates that spatiotemporal mode locking (STML) is enabled by nonlinear intermodal interactions and spatial filtering, along with the Mamyshev mechanism. This work represents a first, to the best of our knowledge, exploration of STML in an oscillator with a Mamyshev saturable absorber.

Coupling between surface processes and crustal deformation: Insights from the late Cenozoic development of the Qaidam Basin, China

A central issue when studying landscape evolution is to quantify the effect of surface processes on tectonic deformation. To address this question, we systematically examine the relationship between the late Cenozoic pattern of sedimentary dispersal system in the endorheic Qaidam Basin in the northern Tibetan Plateau and its spatiotemporal variation in hydrological conditions. At present, the depocenter of the Qaidam Basin is located in the southern Qaidam Basin, which correlates with the largest stream runoff, whereas smaller depressions are located in the northern Qaidam Basin owing to lower stream runoffs. The northwestern boundary without obvious runoff corresponds to large-scale modern erosion regions in the northwestern Qaidam Basin. Based on these findings, good spatiotemporal couplings between sedimentary depressions and hydrological conditions have been proved in the Qaidam Basin, indicating that the changing hydrological pattern in the basin-bounding ranges has played as a first-order role in controlling the Quaternary landscape evolution of the Qaidam Basin. • Spatiotemporal coupling of hydrological condition and basin infilling in Qaidam Basin. • Widespread Quaternary overlapping at all the three margins of Qaidam Basin. • Hydrological pattern changes Quaternary sedimentary distribution in Qaidam Basin.

Urban ecological land and natural-anthropogenic environment interactively drive surface urban heat island: An urban agglomeration-level study in China.

The surface urban heat island effect (SUHI) that occurs during rapid urbanization increases the health risks associated with high temperatures. Urban ecological land (UEL) has been shown to play an important role in improving urban heat stress, however, the impact of UEL interactions with the natural-anthropogenic environment on SUHI at the urban agglomeration-scale is less explored. In this study, the Google Earth Engine and GeoDetector were applied to characterize the spatiotemporal patterns of UEL and SUHI in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2020 by extracting major built-up urban areas and quantifying the impacts of UEL and its interactions with the natural-anthropogenic factors on SUHI. The results show that the evolution of the UEL landscape structure exhibits clear spatiotemporal coupling with SUHI. Specifically, the UEL underwent a dispersion and degradation process in 2000-2015 and a convergence and restoration process in 2015-2020, the SUHI correspondingly transitioned from intensification and continuity to mitigation and contraction. The UEL landscape structure showed a notable impact on the SUHI reduction, and the dominance and richness of the patches explained an average of 19.95% and 16.03% of the SUHI, respectively. Moreover, the interaction between UEL and land urbanization rate and anthropogenic heat release had a dominant effect on SUHI, but this effect significantly declined from 2015 to 2020. With the implementation of ecological restoration projects, the interaction of UEL with topography rapidly increased and the SUHI gradually dominated by the joint interaction of UEL and natural-anthropogenic factors. A synthesis of the varying effects of several factors showed that the dynamic relationship between the development stages of the urban agglomeration's regional system and SUHI may conform to the Environmental Kuznets Curve. SUHI reduction strategies should therefore comprehensively optimize the rational allocation of UEL landscape structures and natural-human elements to promote the well-being of residents.

Spatiotemporal couplings through a nonlinear phase in broadband optical parametric amplification.

Optical parametric chirped-pulse amplification (OPCPA) is prone to undesired spatiotemporal couplings. This Letter studies a family of OPCPA couplings resulting from the nonlinear phase shift induced by frequency-dependent phase mismatch. These OPCPA couplings manifest as pulse-front deformation, transversely varying pulse duration, and spectrally varying wavefront curvature, which are directly linked with the phase-mismatch dispersion terms. The numerical study in this Letter also reveals that the focused signal intensity severely degrades with increasing signal bandwidth and pump depletion.

Spatiotemporal non-uniformly correlated beams

We present a new partially coherent source with spatiotemporal coupling. The stochastic light, which we call a spatiotemporal (ST) non-uniformly correlated (NUC) beam, combines space and time in an inhomogeneous (shift- or space-variant) correlation function. This results in a source that self-focuses at a controllable location in space-time, making these beams potentially useful in applications such as optical trapping, optical tweezing, and particle manipulation. We begin by developing the mutual coherence function for an ST NUC beam. We then examine its free-space propagation characteristics by deriving an expression for the mean intensity at any plane z ge 0. To validate the theoretical work, we perform Monte Carlo simulations, in which we generate statistically independent ST NUC beam realizations and compare the sample statistical moments to the corresponding theory. We observe excellent agreement amongst the results.

Erratum: Focused fields of ultrashort radially polarized laser pulses having low-order spatiotemporal couplings [Phys. Rev. A 103 , 033512 (2021)

Received 22 October 2021DOI:https://doi.org/10.1103/PhysRevA.104.059902©2021 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasUltrafast opticsAtomic, Molecular & Optical

A blockchain bee colony double inhibition labor division algorithm for spatio-temporal coupling task with application to UAV swarm task allocation

It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks. Using the idea of clustering, after clustering tasks according to spatio-temporal attributes, the clustered groups are linked into task sub-chains according to similarity. Then, based on the correlation between clusters, the child chains are connected to form a task chain. Therefore, the limitation is solved that the task chain in the bee colony algorithm can only be connected according to one dimension. When a sudden task occurs, a method of inserting a small number of tasks into the original task chain and a task chain reconstruction method are designed according to the relative relationship between the number of sudden tasks and the number of remaining tasks. Through the above improvements, the algorithm can be used to process tasks with spatio-temporal coupling and burst tasks. In order to reflect the efficiency and applicability of the algorithm, a task allocation model for the unmanned aerial vehicle (UAV) group is constructed, and a one-to-one correspondence between the improved bee colony double suppression division algorithm and each attribute in the UAV group is proposed. Task assignment has been constructed. The study uses the self-adjusting characteristics of the bee colony to achieve task allocation. Simulation verification and algorithm comparison show that the algorithm has stronger planning advantages and algorithm performance.