Scale Expansion Research Articles

Model Research of Vehicle Intelligent Scheduling Problem in Distribution Center Based on Improved Differential Evolution Algorithm

With the continuous expansion of the city scale and the increasing population, people have put forward higher requirements for the speed, reliability and economy of logistics distribution. Although there have been many achievements in the research on the vehicle optimal scheduling decision model and its solution algorithm, there are some problems such as low solution efficiency, long time consumption, and easy to fall into the local optimal solution. The purpose of this paper is to study the model of vehicle scheduling problem in distribution center based on improved differential evolution algorithm. This paper firstly makes a simple analysis of the vehicle distribution route optimization problem, and points out the main factors that constitute the route optimization problem; then analyzes the principle of the differential evolution algorithm, and on this basis, the differential evolution algorithm is improved. In the experimental part, this paper takes a distribution center as the research object, and proposes the implementation steps of the algorithm of the vehicle scheduling problem based on the improved differential evolution algorithm. And test the running cost of the improved differential evolution algorithm and differential evolution algorithm. Experimental results show that applying the improved differential evolution algorithm to vehicle scheduling problems has certain practicality. When the number of iterations reaches 60, the running cost of the improved differential evolution algorithm is 1,200 yuan, and the running cost of the differential evolution algorithm is 1,300 yuan.

GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems

Owing to the expansion of the grid interconnection scale, the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important. These characteristics can provide effective support in coordinated security control. However, traditional model-based frequency- prediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models. Therefore, this study presents a rolling frequency-prediction model based on a graph convolutional network (GCN) and a long short-term memory (LSTM) spatiotemporal network and named as STGCN-LSTM. In the proposed method, the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input. An improved GCN embedded with topology information is used to extract the spatial features, while the LSTM network is used to extract the temporal features. The spatiotemporal-network-regression model is further trained, and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information. The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response. The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems.

Analysis of maneuverability of X-rudder submarine considering environmental disturbance and jamming situations

The main goal of this study is to analyze the dynamic characteristics of the × rudder submarine by performing modeling and simulation of the dynamics. The maneuverability of the × rudder submarine is quantitatively analyzed by modeling the external forces that makes it suitable to express the maneuvering motion of the × rudder submarine, and performing standard maneuvering simulations, such as turning, zigzag, and meander, based on this model. The comparative maneuverability of + rudder and × rudder submarines during environmental disturbances, such as underwater currents and waves near the water surface, is evaluated. To analyze the effect of waves on the near surface, a two-time scale expansion method was applied, and based on this, the basis that × rudder submarines have robust dynamic characteristics amid environmental disturbances is also explained. In particular, for the × rudder submarine, the jamming cases of control planes were classified and the dynamic characteristics of each jamming case were analyzed. For a total of 14 cases of control plane jamming, the quantitative performance of horizontal and vertical dynamic characteristics, including the possibility of maneuvering, was analyzed.

Analysis of energy efficiency in China’s export trade: A perspective based on the synergistic reduction of CO2 and SO[formula omitted

China has become the world’s largest energy consumer with its energy consumption growth accounts for three-quarters of the global growth. It is necessary to measure its energy efficiency reasonably. Previous studies mainly investigated energy use efficiency from the perspective of direct energy consumption without considering the energy consumption related to intermediate production, and did not eliminate the influence of random errors and environmental variables, resulting in deviations in energy efficiency measurement results. Combining a non-competitive input–output model and a three-stage data envelopment analysis, and based on the perspective of synergistic CO2 and SO2 emission reduction, this study constructs a new environmentally extended energy efficiency model to elucidate the true energy efficiency of China’s export trade. The results are as follows. (1) The implied energy efficiency of China’s export trade is generally on the rise under environmental constraints. Although its real efficiency in excluding external environmental factors has declined, its potential for improvement is still great. (2) Technological innovation and the expansion of export trade scale are conducive to the improvement of energy efficiency. Due to overcapacity, increasing industry capital investment will not greatly improve energy efficiency, but will increase the energy consumption and pollution emissions. (3) The average energy saving potential of China’s export trade is 8.91%, and the average emission reduction potential is 11.77%. (4) From 2002 to 2017, the average annual growth rate of implied energy efficiency in export trade was 8.9%, and technological progress was the main source of growth.

Research on the Main Points of Parallel Programming Technology Based on Heterogeneous System

In recent years, with the continuous improvement of high-performance computing hardware platform, the application of high performance for a wide range of high-performance, traditional parallel programming environment tools cannot meet the growing demand for high-performance applications and the face of parallel software development environment in a relatively backward state. The heterogeneous system of the new coprocessor with a high performance and power ratio can have high performance computing needs to provide the task to accelerate. As a result, heterogeneous systems are becoming a new trend in high performance computing. However, with the introduction of the new coprocessor and the expansion of the system scale, heterogeneous systems are difficult to program the problem is also increasingly prominent. In view of this problem, this paper adopts the abstract technology to enhance the granularity of parallel programming, and designs a structured parallel programming prototype system which can achieve different levels of implicit parallelism.

Social Capital, Environmental Knowledge, and Pro-Environmental Behavior.

As the value form of public access to environmental information, the impact of social capital on pro-environmental behavior cannot be ignored. Based on the data of the Chinese General Social Survey 2013 (CGSS2013), this study measures social capital from four aspects—social trust, social norms, social network, and social participation—and it empirically tests the impact of social capital on private and public pro-environmental behavior. The study finds that social capital helps promote pro-environmental behavior. Specifically, the more the public abides by social norms, the higher the degree of social participation, and the stronger the willingness to adopt private and public pro-environmental behaviors. However, the improvement of social trust only has a significant impact on the private environmental behaviors, and the expansion of the social network scale only has a significant impact on the public pro-environmental behaviors. The enhancement of social capital enriches environmental knowledge and promotes pro-environmental behaviors. The mechanism test shows that environmental knowledge plays an intermediary role in the path of social capital affecting individual pro-environmental behavior. The improvement of social capital has a significant impact on the environmental knowledge of individuals with high subjective social class. The gender heterogeneity of social capital affecting environmental knowledge mainly stems from social trust and social network. The stronger the degree of social trust, the richer the environmental knowledge of women, and the social network mainly affects the knowledge level of men. In addition, the publics in the southern region are more likely to be affected by social trust and improve environmental knowledge. Based on the above research conclusions, this paper puts forward policy suggestions on institutional aspects, such as increasing support for informal environmental organizations, carrying out differentiated sustainable development education, and improving the mechanism of environmental information communication.

Does Agricultural Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

Agricultural mechanization is an important factor to improve the green total factor productivity of the planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Based on the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of the output-oriented distance function to measure the green total factor productivity of China’s planting industry based on net carbon sinks, and empirically studies the impact of agricultural mechanization on the green total factor productivity in China’s planting industry. The main findings of this paper are as follows: (1) Agricultural mechanization can promote the planting green total factor productivity significantly, and this basic conclusion is still robust after using instrumental variables and sub sample regression. (2) The path of agricultural mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover, while the mechanisms of operation scale expansion, factor allocation optimization and technical efficiency change are not significant. (3) With the improvement in the mechanization level, the promotion effect of mechanization on planting GTFP will become clearer. Given these findings, the paper adds considerable value to the empirical literature and provides various policy and practical implications.

Propagation and modulational instability of Rossby waves in stratified fluids

Perturbation analysis and scale expansion are used to derive the (2+1)-dimensional coupled nonlinear Schrödinger (CNLS) equations that can describe interactions of two Rossby waves propagating in stratified fluids. The (2+1)-dimensional equations can reflect and describe the wave propagation more intuitively and accurately. The properties of the two waves in the process of propagation can be analyzed by the solution obtained from the equations using the Hirota bilinear method, and the influence factors of modulational instability are analyzed. The results suggest that, when two Rossby waves with slightly different wave numbers propagate in the stratified fluids, the intensity of bright soliton decreases with the increases of dark soliton coefficients. In addition, the size of modulational instable area is related to the amplitude and wave number in y direction.

Can international students help enhance China's urban innovation?

The growing number of international students coming to China has injected new vitality into the development of an innovative economy in the mainland. In this paper, we employ a panel fixed-effect model to examine how international students affect China's technological innovation. Our paper finds that international students in China have significantly promoted urban innovation in China, reflected not only in the expansion of urban innovation scale but also in the improvement of the urban patent structure and innovation quality. This highlights the need to increase the scale of international education and improve the quality of international education.

A computational efficient optimization of flow shop scheduling problems

Flow shop scheduling problems are NP-hard problems. Heuristic algorithms and evolutionary metaheuristic algorithms are commonly used to solve this kind of problem. Although heuristic algorithms have high solving speed, the solution quality is not good. Evolutionary algorithms make up for this defect in small-scale problems, but the solution performance will deteriorate with the expansion of the problem scale and there will be premature problems. In order to improve the solving accuracy of flow shop scheduling problems, a computational efficient optimization approach combining NEH and niche genetic algorithm (NEH-NGA) is developed. It is strengthened in the following three aspects: NEH algorithm is used to optimize the initial population, three crossover operators are used to enhance the genetic efficiency, and the niche mechanism is used to control the population distribution. A concrete application scheme of the proposed method is introduced. The results of compared with NEH heuristic algorithm and standard genetic algorithm (SGA) evolutionary metaheuristic algorithm after testing on 101 FSP benchmark instances show that the solution accuracy has been significantly improved.

Opening the black box of capacity governance: Environmental regulation and capacity utilization of microcosmic firms in China

The existing literature primarily explores overcapacity governance from the perspective of industrial policies, and few studies have directly examined the relationship between environmental regulation and overcapacity. However, the production scale expansion caused by neglecting environmental costs is the key reason for overcapacity. Based on the matching data of Chinese firms in the years 2000–2010, this study empirically explores the influence and channels of environmental regulation on the capacity utilization of firms. A benchmark analysis finds that environmental regulation improves the capacity utilization of firms. On exploring the plausible channels, we show that environmental regulation improves capacity utilization by promoting technical progress and correcting market distortion and inhibits capacity utilization by increasing production costs. This study opens the black box of capacity governance from a micro perspective and provides a scientific basis for realizing capacity governance.

Modulated wave pattern stability in chain neural networks under high–low frequency magnetic radiation

The dynamics of localized modulated action potential induced through modulational instability (MI) in a diffusive array of coupled neurons under high–low frequency magnetic radiation is investigated both analytically and numerically in the frame work of the improved Integrate and Fire model. The improved model includes the magnetic flux variable which takes into account the effect of electromagnetic induction set up from the variation in intracellular distribution of ions concentration during action potential propagation. The coupling between the magnetic flux variable and the membrane potential variable is realized using the memristor. High–low frequency magnetic radiation is imposed as periodic forcing currents on the magnetic flux variable. Through the powerful discrete multiple scale expansion, the nonlinear system of coupled equations are simplified to a lone nonlinear amplitude differential equation, on which linear stability analysis is carried out. It is found that high memristive coupling stabilizes the growth rate of instability. The stable and unstable zones of MI portrait are clearly dependent on the memristive coupling. Numerical experiment is performed and it confirms data picked from the unstable zone lead to the formation of localized modulated wave patterns with some traits of synchronization. Extensive numerical simulations revealed higher memristive coupling suppresses the excitability of the lattice to quiescent state, with homogeneous spatiotemporal patterns. The sample time series of the membrane potential showed high–low frequency magnetic radiation factor (N) promotes mode transition from spiking to bursting-like state. This could provide new insights to develop a new therapy in controlling abnormal brain state using magnetic radiation.

Design and Implementation of Intelligent Vehicle Control System Based on Internet of Things and Intelligent Transportation

With the improvement of urbanization and the continuous expansion of transportation scale, traffic problem has become an important problem in our life. How to ensure traffic safety has become the key issue for the government to implement social management. Nowadays, Internet of Things (IOT) technology is widely used in the industrial technology field. It will have a great impact on human production and life. Intelligent transportation system is a research field involving many high and new technologies. This paper proposes an intelligent transportation system based on Internet of Things technology. This paper presents the optimal design structure of intelligent transportation system based on Internet of Things technology. The experimental results show that the intelligent transportation system can effectively realize the information interaction between the vehicle and the control center and understand the road conditions in advance. At the same time, the intelligent transportation system can improve the driving speed of vehicles on the road, make effective use of resources, reduce economic losses during vehicle operation, and reduce air pollution caused by gasoline emission.

Wealth inequality in pre‐industrial Europe: What role did associational organizations have?

AbstractA host of studies on wealth inequality in pre‐industrial Europe has recently been published. Out of these, a narrative emerges of rising inequality in a context of emerging markets and growing state taxation, punctuated by calamities. By surveying the available material, this article highlights an element that is less systematically discussed in this literature: the role of associational organizations. They developed less regressive forms of taxation and redistribution, embedded the transfer and use of land and capital in coordination systems that curtailed accumulation, and sometimes even imposed maximums of wealth ownership. The article tentatively argues that the resulting downward effect on wealth inequality was found most conspicuously in societies where associations of middling groups of owners‐producers held strong positions in economic and political life, even despite the exclusive character of their organizations. Such societies were gradually eroded in the early modern period, most notably as a result of the emergence of factor markets and state centralization, and the associated processes of proletarianization and scale enlargement. This did not happen without opposition and conflict, however, as the process was sometimes halted and showed distinct geographical patterns, which in turn influenced patterns of wealth inequality.

Homogenization of the wave equation with non-uniformly oscillating coefficients

The focus of our work is a dispersive, second-order effective model describing the low-frequency wave motion in heterogeneous (e.g., functionally graded) media endowed with periodic microstructure. For this class of quasi-periodic medium variations, we pursue homogenization of the scalar wave equation in , , within the framework of multiple scales expansion. When either or , this model problem bears direct relevance to the description of (anti-plane) shear waves in elastic solids. By adopting the lengthscale of microscopic medium fluctuations as the perturbation parameter, we synthesize the germane low-frequency behavior via a fourth-order differential equation (with smoothly varying coefficients) governing the mean wave motion in the medium, where the effect of microscopic heterogeneities is upscaled by way of the so-called cell functions. In an effort to demonstrate the relevance of our analysis toward solving boundary value problems (deemed to be the ultimate goal of most homogenization studies), we also develop effective boundary conditions, up to the second order of asymptotic approximation, applicable to one-dimensional (1D) shear wave motion in a macroscopically heterogeneous solid with periodic microstructure. We illustrate the analysis numerically in one dimension by considering (i) low-frequency wave dispersion, (ii) mean-field homogenized description of the shear waves propagating in a finite domain, and (iii) full-field homogenized description thereof. In contrast to (i) where the overall wave dispersion appears to be fairly well described by the leading-order model, the results in (ii) and (iii) demonstrate the critical role that higher-order corrections may have in approximating the actual waveforms in quasi-periodic media.

A Study into the Value and Development Path of Regional Joint Training Mode for Graduate Teaching Groups

Regional joint training for graduate teaching groups, as an attempt and pioneer action of volunteer training, has been carried out in Nanjing for nine years, and a number of excellent volunteers have been trained to make contributions to the West. Joint training, with its advantages of centralized teaching characteristics, aggregation effect and cohesion, has continuously attracted colleges and universities to join. Colleges and universities cooperate with each other to innovate the training mode, explore the development path, and break the talent training barrier between the exporting colleges and the undertaking colleges. However, the management problems and training caused by the expansion of scale are limited to the present, and the lack of follow-up always exists and needs to be solved. The regional joint training organized by Nanjing Normal University provides experience and ideas for improving the quality and efficiency of training and expanding the promotion.

Distributed Model Predictive Coordinated Control for Combined Heat and Power Load of an Integrated Energy System

Due to the strong coupling and multiple constraints of combined heat and power (CHP) generation in an integrated energy system (IES), the model predictive control (MPC) is widely adopted as the lower layer coordination controller. However, with the upgrade of capacity and the expansion of scale, centralized MPC (CMPC) is no longer capable of dealing with heavy-data, high dimensional IES optimization problem. To address this concern, distributed MPC (DMPC) is applied to coordinate the energy supply of CHP-IES. In view of the characteristics of CHP-IES, DMPC should be endowed with the capability of offset-free tracking and disturbance rejection. Hence, the disturbance augmentation method and the modification of objective function have been applied to facilitate each DMPC controller with the required abilities. Through simulation comparison with CMPC on the same theoretical model, the performance of modified cooperative DMPC (CDMPC) is on par with CMPC, while the computational burden is drastically relieved.

The relation between deindustrialization and reindustrialization: a new perception of industrial structure upgrading

According to traditional industrial structure upgrading theory, the economic structure of a country should be transformed from agricultural economy to industrial economy and service economy. It is contrary to the current \re-industrialization\ strategy of developed countries such as the United States and European Union states. This paper indicates that traditional industrial structure upgrading theory doesn’t clarify the prerequisites for industrialization and deindustrialization and ignores the different characteristics of each industrial sector. The traditional industrial structure upgrading theory also emphasizes on the expansion of specific industrial sector scale and doesn’t take into account the interactions between them. Considering the interaction and integration of modern manufacturing sector and service sector, from the perspective of the improvement of social productivity, this paper explores the essential relationship between industrialization and deindustrialization using theoretical model analysis. This paper holds that simply pursuing the expansion of the scale of the service sector is inclined to lead to premature and excessive deindustrialization, which should not be the goal of industrial structure upgrading. The new theory of industrial structure upgrading should aim at the maximization of social productivity and constantly approach the equilibrium between manufacturing sector and service sector.

Research and Reflection on Constructing a Unified and Open Transportation Market——Taking Zhejiang Province as an Example

With the continuous expansion of the market scale since the reform and opening-up policy, the necessity and imperatives of building a unified national market have kept increasing daily. Building a unified and open transport market is the crucial premise and essential support for a unified national market. As a developed province along the east coast, Zhejiang has preliminarily explored building a unified and open transportation market in recent years. This paper mainly studies and thinks on constructing a unified and open transport market in Zhejiang from the current situation and its main problems. It also puts forward relevant measures and suggestions.

Public transport travel mode chain and its implications for commute satisfaction: Take Xi'an as an example

The continuous expansion of urban population and space scale, the continuous increase of daily average traffic trips and per capita travel distance, and the increasingly frequent urban economic activities have formed diversified travel demands. Based on the survey data, this study combs the commuter travel mode chain of Xi'an with public transport as the main body, and explores the satisfaction of current commuter bus passengers. First of all, the impact factors of each link of the public transport travel mode chain are sorted out. Based on the three levels of reachability, accessibility and connectivity, this paper proposes an evaluation index system of urban public transport commuting service, including convenience, safety, comfort, reliability and other specific indicators. Secondly, the commuting satisfaction evaluation scale is constructed to evaluate the subjective experience of travellers in the travel process. The results show that there is a gap between the expectation of commuters and the perception of public transport service attributes. Among them, "convenience" and "comfort" of public transport are the most important service quality attributes related to the satisfaction of commuters, and residents are the least satisfied with the convenience of transit, and public transport lines fail to meet the commuting needs of some residents. When transport operators provide services that meet passengers' expectations, passenger satisfaction and PBT utilization rate will be improved, service quality of public transport mode chain will be improved, sustainable transport will be promoted, and energy consumption and emissions will be reduced.