Train timetabling with the general learning environment and multi-agent deep reinforcement learning

This paper proposes a multi-agent deep reinforcement learning approach for the train timetabling problem of different railway systems. A general train timetabling learning environment is constructed to model the problem as a Markov decision process, in which the objectives and complex constraints of the problem can be distributed naturally and elegantly. Through subtle changes, the environment can be flexibly switched between the widely used double-track railway system and the more complex single-track railway system. To address the curse of dimensionality, a multi-agent actor–critic algorithm framework is proposed to decompose the large-size combinatorial decision space into multiple independent ones, which are parameterized by deep neural networks. The proposed approach was tested using a real-world instance and several test instances. Experimental results show that cooperative policies of the single-track train timetabling problem can be obtained by the proposed method within a reasonable computing time that outperforms several prevailing methods in terms of the optimality of solutions, and the proposed method can be easily generalized to the double-track train timetabling problem by changing the environment slightly

Intuitionistic Fuzzy Subalgebras (Ideals) with Thresholds (λ,μ) of BCI-algebras

Based on the theory of intuitionistic fuzzy sets, the concepts of intuitionistic fuzzy subalgebras with thresholds (λ,μ) and intuitionistic fuzzy ideals with thresholds (λ,μ) of BCI-algebras are introduced and some properties of them are discussed

Analysis of the Network of Protected Areas in China Based on a Geographic Perspective: Current Status, Issues and Integration

With the continued growth of protected areas (PAs) in China in terms of the number, coverage and varieties of protected objects, how to efficiently manage the protected areas to ensure both resource protection and environmental protection has become a crucial research question. By applying a geographic perspective in an analysis of the development and evolution of protected areas in China, this paper presents the results of an analysis focused on the status and the types of current approaches to the management of natural protected areas to reveal the problems that exist in their management and to further explore an integration strategy for the protected area network. It proposes that the future management of protected areas should prioritize their legal status, the sustainable livelihood of individuals living in close proximity to them, and the establishment of a unified database to achieve grid and information management of the protected areas

Spatiotemporal Dynamics and Drivers of Farmland Changes in Panxi Mountainous Region, China

Due to the multiple impacts of landform effects, spatial heterogeneity and land use policies, farmland dynamics in mountainous areas are complicated. This study investigated farmland dynamics based on land use data from a typical mountainous area, Panxi, in China for 1990, 2000 and 2010, discussed the relationship between altitude, slope and farmland changes and presented an analysis of the driving forces of farmland change. Our findings are as follows: (1) from 1990 to 2010, the area of converted farmland was relatively small (313 km2), accounting for only 2.6% of the region’s farmland. Farmland was mainly converted to forest and grassland as a result of the Returning Farmland to Forest Program; (2) The spatial distribution of land use types differed significantly. The presence of water bodies influenced farmland and built-up land, while forest and grassland showed “landform-oriented” characteristics. Built-up land was especially variable in distribution, indicating that it was more vulnerable to human activities; (3) The vertical differentiation of farmland changes was obvious. At altitudes <2500 m, the data displayed a trend of conversion from forest to farmland, while at >2500 m, this trend reversed. Thus, 2500 m serves as an altitudinal boundary between farmland and forest in Panxi. The largest area of forest-farmland transfer occurred on slopes steeper than 15°, not 25°, as defined by China’s policy of Returning Farmland to Forest; (4) The driving forces of farmland changes varied. Decreases in farmland were negatively correlated with proximity to rivers and roads. Increases in farmland were positively related to temperature and negatively related to both population density and altitude

Optimal Distributed Broadcasting with Per-neighbor Queues in Acyclic Overlay Networks with Arbitrary Underlay Capacity Constraints

Abstract—Broadcasting system such as P2P streaming systems represent important network applications that support up to millions of online users. An efficient broadcasting mechanism is at the core of the system design. Despite substantial efforts on developing efficient broadcasting algorithms, the following important question remains open: How to achieve maximum broadcast rate in a distributed manner with each user maintaining information queues only for its direct neighbors? In this work, we first derive an innovative formulation of the problem over acyclic overlay networks with arbitrary underlay capacity constraints. Then, based on the formulation, we develop a distributed algorithm to achieve the maximum broadcast rate and every user only maintains one queue per-neighbor. Due to its lightweight nature, our algorithm scales very well with network size and remains robust against high system dynamics. Finally, by conducting simulations we validate the optimality of our algorithm under different network capacity models. Simulation results further indicate that the convergence time of our algorithm grows linearly with the network size, which suggests an interesting direction for future investigation. I

Measuring the Coordinated Development of Ecological and Economic Systems in Hengduan Mountain Area

With the expansion of the concept of sustainable development, it has become increasingly important to investigate the means for achieving sustainable eco-economic development. On the basis of Landsat imagery of Hengduan Mountain area of China acquired in 1990, 2000, and 2010, we analyzed the coordination relationships, evolution characteristics, and aggregation modes of the economy and ecology in this region using ecosystem service value (ESV) and ecological economic harmony (eco-economic harmony, EEH) models. The following results were obtained. (1) There was a significant transition in land cover, wherein grassland increased the most and farmland decreased the most, by 1.18 × 104 km2 and 9.41 × 103 km2, respectively. These trends were related to urban expansion and the implementation of ecological measures; (2) From 1990 to 2000, there was a deterioration in the ecological system, whereas after 2000, the ecosystem improved due to implementation of the Chinese government’s “Returning Farmland to Forest (Grassland)” scheme, thereby illustrating the importance of forest to ecosystem stability; (3) Spatially, the EEH index showed a dual-core structure centered on a low conflict zone and potential crisis zone, which signified that there was a trend of coordinated development between the economy and ecology; however, this was not stable; (4) There were four types of EEH evolution zones—low conflict, potential crisis, slight improvement, and significant improvement zones—of which the improvement zones accounted for 55.15% of the area, thereby indicating that over time the economy has played a positive role in shaping the ecological environment; (5) The spatial aggregation modes of EEH evolution were band coordinated mode, group uncoordinated mode and group improvement mode, which meant the relationship of ecology and economy was always in lowest coordinated state in a banded form, in uncoordinated state and a significant increase in a block form, respectively. These modes were intended to provide a reference for the sustainable development in southwest China

An Experimental Investigation on the Relationship between MS Frequency Response and Coal and Gas Outburst

Microseismic (MS) frequency response is an important part of high-efficiency data mining to achieve the aim of coal and gas outburst (CGOB) early warning. Based on the variation pattern of acoustic emission (AE) signal in the coal failure process, the experimental characteristics of MS activity and typical signals CGOB were obtained in this study. First, the AE behavior of coal failure experiment was studied, and an explanation of laws was provided as follows: the fracture behavior of coal sample exhibits certain characteristics of AE response in terms of AE event count, signal amplitude, and frequency; each stage has its own physical meaning during the process of loading test. Based on these laws, CGOB experiments were carried out using a large CGOB physical simulation system with a MS monitoring system. Notching filter and wavelet packet transform technique were used in the denoising and feature extraction of six typical MS events (signals). The features of each stage, including the time-frequency domain, were extracted and quantitatively expressed. We finally arrive at the following conclusions: (1) CGOB exhibits significantly periodic characteristics, and each CGOB stage corresponds to the significant response characteristics of MS. CGOB presents varying characteristics, such as “valley-peaks-valley”. (2) From the incubation stage to happen stage of outburst, the spectrum significantly moved from extremely low frequency (100-200 Hz) to high-frequency band (approach to 1600 Hz). During the residual stage, MS frequency manifested the concentration distribution (50 Hz) and offered the advantage of energy concentration. (3) The phenomenon of signal energy also shows the trend of energy transform low to high and to low modes along with the process. Signals total energy distribution (42.81%, 1,437.5-1,812.5 Hz) in the happen stage are markedly larger than those of events in incubation stage (7.01%) and residual stage (1.44%). The methodology presented in this paper for CGOB signal analysis provides a new method to obtain MS response precursor and predict CGOB disaster. This approach can be useful for rockburst anticipation and control during mining in gas and highly stressed coal mines.Peer Reviewe

Multi-Scale Spectral-Spatial Attention Network for Hyperspectral Image Classification Combining 2D Octave and 3D Convolutional Neural Networks

Traditional convolutional neural networks (CNNs) can be applied to obtain the spectral-spatial feature information from hyperspectral images (HSIs). However, they often introduce significant redundant spatial feature information. The octave convolution network is frequently utilized instead of traditional CNN to decrease spatial redundant information of the network and extend its receptive field. However, the 3D octave convolution-based approaches may introduce extensive parameters and complicate the network. To solve these issues, we propose a new HSI classification approach with a multi-scale spectral-spatial network-based framework that combines 2D octave and 3D CNNs. Our method, called MOCNN, first utilizes 2D octave convolution and 3D DenseNet branch networks with various convolutional kernel sizes to obtain complex spatial contextual feature information and spectral characteristics, separately. Moreover, the channel and the spectral attention mechanisms are, respectively, applied to these two branch networks to emphasize significant feature regions and certain important spectral bands that comprise discriminative information for the categorization. Furthermore, a sample balancing strategy is applied to address the sample imbalance problem. Expansive experiments are undertaken on four HSI datasets, demonstrating that our MOCNN approach outperforms several other methods for HSI classification, especially in scenarios dominated by limited and imbalanced sample data