The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation...The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation and evolution of Meizhou pomelo industry cluster in China,focusing on its role in restructuring rural socio-economic systems and integrating the whole value chains.Based on a case study employing qualitative methods such as in-depth interviews and participatory observation,the agricultural cluster evolution of Meizhou pomelo was categorized into three key phases of initial decentralization,self-organized scaling,and reorganized clustering.Geographical proximity and industrial agglomeration constitute the physical foundation,while vertical/horizontal linkages,technologic-al innovation,and policy support enhance competitiveness.Special mechanisms emerge through localized social networks,farmer co-operatives’activation,and cross-regional market expansion.The cluster’s impact is manifested in the shift from extensive to standard-ized and modernized production,diversified and flexible livelihood of farmers,and the integration of agriculture with industry and ser-vices.The development of the whole value chain based on agricultural cluster represents a critical pathway for achieving agricultural modernization,encompassing both internal and external value chain optimization.Through quality assurance systems,product diversi-fication strategies,operational efficiency improvements,and brand enhancement,these clusters amplify product value propositions and market competitiveness.This systemic approach facilitates supply-demand coordination,enables resource synergies,and optimizes eco-nomic returns across the horizontal and vertical value chain.This paper argues that agricultural clusters serve as strategic catalysts for sustainable rural development by reconstructing local production systems,fostering innovation ecosystems,and aligning agricultural modernization.It contributes to debates on rural vitalization by demonstrating how agricultural clustering can reconfigure rural areas as hubs of ecological modernization,rather than mere urban peripheries.展开更多
To illustrate how firms and customers co-create value in business to business （B2B） e-commerce, an integrated value co-creation model is proposed based on information systems （IS） application capabilities from the...To illustrate how firms and customers co-create value in business to business （B2B） e-commerce, an integrated value co-creation model is proposed based on information systems （IS） application capabilities from the relational view. IS application capabilities, relational assets, customer agility and relational value are constructed and tested by empirical analysis. The empirical research tests and verifies the mediating effect of customer agility, and the interactions of IS application capabilities and relational assets, as well as their effect on relational value. This model expands the research framework of value co-creation in service dominant logic, and reveals the mechanism of how f＇n＇ms and customers co-create value in B2B e-commerce based on IS application capabilities, which provides the basis for further theory development and a practice guide.展开更多
Enforcing initial and boundary conditions(I/BCs)poses challenges in physics-informed neural networks(PINNs).Several PINN studies have gained significant achievements in developing techniques for imposing BCs in static...Enforcing initial and boundary conditions(I/BCs)poses challenges in physics-informed neural networks(PINNs).Several PINN studies have gained significant achievements in developing techniques for imposing BCs in static problems;however,the simultaneous enforcement of I/BCs in dynamic problems remains challenging.To overcome this limitation,a novel approach called decoupled physics-informed neural network(d PINN)is proposed in this work.The d PINN operates based on the core idea of converting a partial differential equation(PDE)to a system of ordinary differential equations(ODEs)via the space-time decoupled formulation.To this end,the latent solution is expressed in the form of a linear combination of approximation functions and coefficients,where approximation functions are admissible and coefficients are unknowns of time that must be solved.Subsequently,the system of ODEs is obtained by implementing the weighted-residual form of the original PDE over the spatial domain.A multi-network structure is used to parameterize the set of coefficient functions,and the loss function of d PINN is established based on minimizing the residuals of the gained ODEs.In this scheme,the decoupled formulation leads to the independent handling of I/BCs.Accordingly,the BCs are automatically satisfied based on suitable selections of admissible functions.Meanwhile,the original ICs are replaced by the Galerkin form of the ICs concerning unknown coefficients,and the neural network(NN)outputs are modified to satisfy the gained ICs.Several benchmark problems involving different types of PDEs and I/BCs are used to demonstrate the superior performance of d PINN compared with regular PINN in terms of solution accuracy and computational cost.展开更多
Investigating the ecological impact of land use change in the context of the construction of national water network project is crucial,as it is imperative for achieving the sustainable development goals of the nationa...Investigating the ecological impact of land use change in the context of the construction of national water network project is crucial,as it is imperative for achieving the sustainable development goals of the national water network and guaranteeing regional ecological stability.Using the Danjiangkou Reservoir Area(DRA),China as the study area,this paper first examined the spatiotemporal dynamics of natural landscape patterns and ecosystem service values(ESV)in the DRA from 2000 to 2018 and then investigated the spatial clustering characteristics of the ESV using spatial statistical analysis tools.Finally,the patch-generating land use simulation(PLUS)model was used to simulate the natural landscape and future changes in the ESV of the DRA from 2018 to 2028 under four different development scenarios:business as usual(BAU),economic development(ED),ecological protection(EP),and shoreline protection(SP).The results show that:during 2000-2018,the construction of water facilities had a significant impact on regional land use/land cover(LULC)change,with a 24830 ha increase in watershed area.ESV exhibited an increasing trend,with a significant and growing spatial clustering effect.The transformation of farmland to water bodies led to accelerated ESV growth,while the transformation of forest land to farmland led to a decrease in the ESV.Normalized difference vegetation index(NDVI)had the strongest effect on the ESV.ESV exhibited a continuous increase from 2018 to 2028 under all the simulation scenarios.The EP scenario had the greatest increase in ESV,while the ED scenario had the smallest increase.The findings suggest that projected land use patterns under different scenarios have varied impacts on ecosystem services(ESs)and that the management and planning of the DRA should balance social,economic,ecological,and security benefits.nomic,ecological,and security benefits.展开更多
Compared with common intelligent service,full-scene intelligent service has its uniqueness in high integration,synergy,and technological spillover.However,the traditional service or business model theories cannot prec...Compared with common intelligent service,full-scene intelligent service has its uniqueness in high integration,synergy,and technological spillover.However,the traditional service or business model theories cannot precisely elaborate its sociotechnical contextual nature and value creation logic.To fill this knowledge gap,we provide initial insights into the value co-creation logic in full-scene intelligent service by exploring the value co-creation elements using a data-driven text mining approach.We analyzed 171 business reports on the full-scene intelligent service by the topic modeling using the Latent Dirichlet Allocation(LDA).The findings reveal three main clusters:value proposition,participants,and connection platform.This study presents a theoretical framework for a further exploratory case study and quantitative research on full-scene intelligent service.This study also helps small and medium-sized enterprises to explore and exploit value co-creation opportunities.展开更多
Establishing a sense of ritual within tourism consumption scenarios offers tourists the opportunity for interactive engagement.Drawing upon the value co-creation theory,this study constructed an influence mechanism mo...Establishing a sense of ritual within tourism consumption scenarios offers tourists the opportunity for interactive engagement.Drawing upon the value co-creation theory,this study constructed an influence mechanism model to examine tourists'active engagement in the process of co-creating tourism experience values.It employed Partial Least Squares Structural Equation Modeling(PLS-SEM)to empirically test the proposed hypotheses.The findings demonstrate that the model constructed in the present study exhibits robust reliability,validity,and explanatory power.The perception of the sense of ritual in tourism exerts a significant positive influence on tourists’co-creation of tourism experience values,thereby significantly enhancing both the communitas and flow experienced by tourists during their travels.Moreover,such communitas and flow can mediate the influence of the sense of ritual in tourism on tourists’co-creation of tourism experience values.This study contributes to advancing the current research on tourists’co-creation of tourism experience values and the sense of ritual in tourism,thereby providing theoretical foundations for cultivating a sense of ritual within tourism consumption scenarios.展开更多
Today,the e-commerce live broadcast industry has formed a huge market,and it has become one of the important ways for most netizens to purchase goods.Live streaming has brought new opportunities for e-commerce and new...Today,the e-commerce live broadcast industry has formed a huge market,and it has become one of the important ways for most netizens to purchase goods.Live streaming has brought new opportunities for e-commerce and new growth for brand value.The interaction between brands and customers has gradually expanded,in this case,the importance of value co-creation has become more and more prominent.This article will take e-commerce live broadcast marketing as the research object,and the brand value co-creation as the research perspective,then provide a direction based on the value co-creation perspective for the healthy and long-term development of e-commerce live broadcast marketing by studying and analyzing the cases of brand value co-creation.展开更多
Rapid and accurate identification of high-quality patents can accelerate the transformation process of scientific and technological achievements, optimize the management of intellectual property rights and enhance the...Rapid and accurate identification of high-quality patents can accelerate the transformation process of scientific and technological achievements, optimize the management of intellectual property rights and enhance the vitality of innovation. Aiming at the shortcomings of the traditional high-value patent assessment method, which is relatively simple and seldom considers the influence of patentees, this paper proposes a high-quality patent method HMFM (High-Value Patent Multi-Feature Fusion Method) that fuses multi-dimensional features. A weighted node importance assessment method in complex network called GLE (Glob-Local-struEntropy) based on improved structural entropy is designed to calculate the influence of the patentee to form the patentee’s features, and the patent text features are extracted by BERT-DPCNN deep learning model, which is supplemented to the basic patent indicator system. Finally a machine learning algorithm is used to assess the value of patents. Experiment results show that our method can identify high-value patents more effectively and accurately.展开更多
By defining fuzzy valued simple functions and giving L1(μ) approximations of fuzzy valued integrably bounded functions by such simple functions, the paper analyses by L1(μ)-norm the approximation capability of four-...By defining fuzzy valued simple functions and giving L1(μ) approximations of fuzzy valued integrably bounded functions by such simple functions, the paper analyses by L1(μ)-norm the approximation capability of four-layer feedforward regular fuzzy neural networks to the fuzzy valued integrably bounded function F : Rn → FcO(R). That is, if the transfer functionσ: R→R is non-polynomial and integrable function on each finite interval, F may be innorm approximated by fuzzy valued functions defined as to anydegree of accuracy. Finally some real examples demonstrate the conclusions.展开更多
In this paper, we give a smoothing neural network algorithm for absolute value equations (AVE). By using smoothing function, we reformulate the AVE as a differentiable unconstrained optimization and we establish a ste...In this paper, we give a smoothing neural network algorithm for absolute value equations (AVE). By using smoothing function, we reformulate the AVE as a differentiable unconstrained optimization and we establish a steep descent method to solve it. We prove the stability and the equilibrium state of the neural network to be a solution of the AVE. The numerical tests show the efficient of the proposed algorithm.展开更多
The Maroochy River, which is located on east coast of Australia, provides a variety of uses and values to the community. Changes in structure, function and management of the river will influence the value that the com...The Maroochy River, which is located on east coast of Australia, provides a variety of uses and values to the community. Changes in structure, function and management of the river will influence the value that the community derives from it. Therefore, critical to the river’s continued management is the development of policy relevant tools based on the community’s value of the river. This paper focuses on estimating the fi-nancial value the local residents derive from living close to the river through investigation of changes in residential property values due to attributes of the Maroochy River. It is a complex analysis since there are several confounding geographical and property variables. Given a large and complete dataset of 28,000 properties for the Maroochy region, Artificial Neural Networks (ANN) was applied to estimate the economic value of the properties. This ANN was then able to simulate scenarios for property values with respect to changes in environmental features. It showed the Maroochy River contributed AU$900,000,000 to the unim-proved capital value of the whole region, a value that could not be estimated previously, and much higher than anticipated. Calculating potential annual payments to the Shire Council through land tax analysis from these property values, provides the council with means to justify expenditure to maintain a standard of water quality and ecosystem health.展开更多
Objective To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific...Objective To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific countermeasures. Methods A three-layer BP network was built to simulate topology and process of the eco-economy system of Xiangfan. Historical data of ecological environmental factors and socio-economic factors as inputs, and corresponding historical data of ecosystem service value (ESV) and GDP as target outputs, were presented to train and test the network. When predicted input data after 2001 were presented to trained network as generalization sets, ESVs and GDPs of 2002, 2003, 2004... till 2050 were simulated as output in succession. Results Up to 2050, the area would have suffered an accumulative total ESV loss of RMB 104.9 billion, which accounted for 37.36% of the present ESV. The coinstantaneous GDP would change asynchronously with ESV, it would go through an up-to-down process and finally lose RMB89.3 billion, which accounted for 18.71% of 2001. Conclusions The simulation indicates that ESV loss means damage to the capability of socio-economic sustainable development, and suggests that artificial neural networks (ANNs) provide a feasible and effective method and have an important potential in ESV modeling.展开更多
Purpose:With the availability and utilization of Inter-Country Input-Output(ICIO)tables,it is possible to construct quantitative indices to assess its impact on the Global Value Chain(GVC).For the sake of visualizatio...Purpose:With the availability and utilization of Inter-Country Input-Output(ICIO)tables,it is possible to construct quantitative indices to assess its impact on the Global Value Chain(GVC).For the sake of visualization,ICIO networks with tremendous low-weight edges are too dense to show the substantial structure.These redundant edges,inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis(SNA).In this case,we need a method to filter such edges and obtain a sparser network with only the meaningful connections.Design/methodology/approach:In this paper,we propose two parameterless pruning algorithms from the global and local perspectives respectively,then the performance of them is examined using the ICIO table from different databases.Findings:The Searching Paths(SP)method extracts the strongest association paths from the global perspective,while Filtering Edges(FE)method captures the key links according to the local weight ratio.The results show that the FE method can basically include the SP method and become the best solution for the ICIO networks.Research limitations:There are still two limitations in this research.One is that the computational complexity may increase rapidly while processing the large-scale networks,so the proposed method should be further improved.The other is that much more empirical networks should be introduced to testify the scientificity and practicability of our methodology.Practical implications:The network pruning methods we proposed will promote the analysis of the ICIO network,in terms of community detection,link prediction,and spatial econometrics,etc.Also,they can be applied to many other complex networks with similar characteristics.Originality/value:This paper improves the existing research from two aspects,namely,considering the heterogeneity of weights and avoiding the interference of parameters.Therefore,it provides a new idea for the research of network backbone extraction.展开更多
Waste reduction is gaining importance as the preferred means of pollution prevention. Reactor network synthesis is one of the key parts of chemical process synthesis. In this study, a geometric approach to reactor net...Waste reduction is gaining importance as the preferred means of pollution prevention. Reactor network synthesis is one of the key parts of chemical process synthesis. In this study, a geometric approach to reactor network synthesis for waste reduction is presented. The bases of the approach are potential environment impact （PEI） rate-law expression, PEI balance and the instantaneous value of environmental indexes. The instantaneous value can be derived using the PEI balance, PEI rate-law expression and the environmental indexes. The optimal reactor networks with the minimum generation of potential environment impact are geometrically derived by comparing with areas of the corresponding regions. From the case study involving complex reactions, the approach does not involve solving the complicated mathematical problem and can avoid the dimension limitation in the attainable region approach.展开更多
GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distributi...GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distribution and generalized Pareto distribution assumptions are adopted re- spectively to simulate the random component in the model. The demonstration of the quantile of network traffic series indicates that common GARCH-M model can partially deal with the "fat tail" problem. However, the "fat tail" characteristic of the random component directly affects the accura- cy of the calculation. Even t distribution is based on the assumption for all the data. On the other hand, extreme value theory, which only concentrates on the tail distribution, can provide more ac- curate result for high quantiles. The best result is obtained based on the generalized Pareto distribu- tion assumption for the random component in the GARCH-M model.展开更多
Cross-border investment is essential for western China’s globalization.Global value chain(GVC)forms cross-border investment networks between industries in western China and overseas cities.Focusing on GVC,this study ...Cross-border investment is essential for western China’s globalization.Global value chain(GVC)forms cross-border investment networks between industries in western China and overseas cities.Focusing on GVC,this study uses the social network analysis method,entropy method,multi-index comprehensive evaluation method,and quadratic assignment procedure analysis method to examine the characteristics and influencing factors of the urban networks of research and development(R&D),production,and sales formed as a result of the overseas investments of listed manufacturing companies in western China.Results showed that the three types of investment networks involved multiple industry types and multiple central cities with differentiated diversity and multicentrality.The R&D urban network’s leading sub-industries were the mechanical equipment and instruments,medicine and biological products,and metal and nonmetal industries.The destination cities were mostly those home to educational and scientific research centers.The production urban network’s leading sub-industries were the mechanical equipment,instrument,and food and beverage industries.The destination cities were mostly regional central cities in developing countries.The sales urban network’s leading sub-industries were the mechanical equipment and instrument,metal and nonmetal,and petrochemical and plastics industries.The destination cities were numerous and scattered.In addition,the R&D urban network easily formed specialized clusters,core nodes easily controlled the production urban network,and individual nodes did not easily control the sales urban network.Technological and economic system advantages greatly impacted the three network types.Considering the different influencing factors,this study suggests optimizing the institutional investment environment to narrow the institutional gap,adjusting and optimizing the investment layout to expand overseas markets,and increasing R&D funds to stimulate technological progress and overseas investments in western China.展开更多
Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions(EOC),which are inevitable in the normal inspection of ci...Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions(EOC),which are inevitable in the normal inspection of civil and mechanical structures.This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network(1D-CNN).After singular value decomposition-based feature extraction processing,a temporal robust damage index(TRDI)is extracted,and the effect of EOCs is well removed.Hence,even for the signals with a very large temperature-varying range and low signal-to-noise ratios(SNRs),the final damage detection and localization accuracy retain perfect 100%.Verifications are conducted on two different experimental datasets.The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises,and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20℃to 60℃.It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly,showing great potential for application in complex and unknown EOC.展开更多
Recurrent Neural Networks were invented a long time ago, and dozens of different architectures have been published. In this paper we generalize recurrent architectures to a state space model, and we also generalize th...Recurrent Neural Networks were invented a long time ago, and dozens of different architectures have been published. In this paper we generalize recurrent architectures to a state space model, and we also generalize the numbers the network can process to the complex domain. We show how to train the recurrent network in the complex valued case, and we present the theorems and procedures to make the training stable. We also show that the complex valued recurrent neural network is a generalization of the real valued counterpart and that it has specific advantages over the latter. We conclude the paper with a discussion of possible applications and scenarios for using these networks.展开更多
In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fu...In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.展开更多
Network selection and resource allocation( NS-RA) are the processes of determining network and radio resource which provide the service to user. Optimizing these processes is an important step towards maximizing the u...Network selection and resource allocation( NS-RA) are the processes of determining network and radio resource which provide the service to user. Optimizing these processes is an important step towards maximizing the utilization of current and future networks. In this paper,we proposed a preference value-based network selection and resource allocation,in which the NS scheme was performed by the joint radio resource management( JRRM) entity and the RA scheme was performed by the network. In the NS step,the JRRM entity selected the preferable network for users according to the preference value of each network,which took the load balance,the received signal strength( RSS) and the relative position between the user and the network into account. In the second step,the network allocated the optimal sub-carrier to user for the downlink transmission each round according to the preference value of each user and the maximum reachable data rate calculated by users' perceived channel information,maximizing the spectrum efficiency as well as guaranteeing the fairness. The simulation results showed that the proposed NS-RA scheme achieves better performance in terms of load distribution,spectrum efficiency and user fairness,compared to the conventional strategies.展开更多
基金Under the auspices of the Key Projects of Philosophy and Social Sciences Research,Ministry of Education of China(No.23JZD008)National Natural Science Foundation of China(No.42171193)+2 种基金Key Project of Guangdong Provincial Philosophy and Social Sciences Planning(No.GD24ES013,GD25ZX04)2025 Guangzhou Basic and Applied Basic Research Special Project(No.2025A04J7127)Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.24wkjc11)。
文摘The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation and evolution of Meizhou pomelo industry cluster in China,focusing on its role in restructuring rural socio-economic systems and integrating the whole value chains.Based on a case study employing qualitative methods such as in-depth interviews and participatory observation,the agricultural cluster evolution of Meizhou pomelo was categorized into three key phases of initial decentralization,self-organized scaling,and reorganized clustering.Geographical proximity and industrial agglomeration constitute the physical foundation,while vertical/horizontal linkages,technologic-al innovation,and policy support enhance competitiveness.Special mechanisms emerge through localized social networks,farmer co-operatives’activation,and cross-regional market expansion.The cluster’s impact is manifested in the shift from extensive to standard-ized and modernized production,diversified and flexible livelihood of farmers,and the integration of agriculture with industry and ser-vices.The development of the whole value chain based on agricultural cluster represents a critical pathway for achieving agricultural modernization,encompassing both internal and external value chain optimization.Through quality assurance systems,product diversi-fication strategies,operational efficiency improvements,and brand enhancement,these clusters amplify product value propositions and market competitiveness.This systemic approach facilitates supply-demand coordination,enables resource synergies,and optimizes eco-nomic returns across the horizontal and vertical value chain.This paper argues that agricultural clusters serve as strategic catalysts for sustainable rural development by reconstructing local production systems,fostering innovation ecosystems,and aligning agricultural modernization.It contributes to debates on rural vitalization by demonstrating how agricultural clustering can reconfigure rural areas as hubs of ecological modernization,rather than mere urban peripheries.
基金The National Science&Technology Pillar Program of China(No.2012BAH29F01)the Innovation Project for Postgraduate Education of Jiangsu Province(No.3214003911)
文摘To illustrate how firms and customers co-create value in business to business （B2B） e-commerce, an integrated value co-creation model is proposed based on information systems （IS） application capabilities from the relational view. IS application capabilities, relational assets, customer agility and relational value are constructed and tested by empirical analysis. The empirical research tests and verifies the mediating effect of customer agility, and the interactions of IS application capabilities and relational assets, as well as their effect on relational value. This model expands the research framework of value co-creation in service dominant logic, and reveals the mechanism of how f＇n＇ms and customers co-create value in B2B e-commerce based on IS application capabilities, which provides the basis for further theory development and a practice guide.
基金Project supported by the Basic Science Research Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT(No.RS-2024-00337001)。
文摘Enforcing initial and boundary conditions(I/BCs)poses challenges in physics-informed neural networks(PINNs).Several PINN studies have gained significant achievements in developing techniques for imposing BCs in static problems;however,the simultaneous enforcement of I/BCs in dynamic problems remains challenging.To overcome this limitation,a novel approach called decoupled physics-informed neural network(d PINN)is proposed in this work.The d PINN operates based on the core idea of converting a partial differential equation(PDE)to a system of ordinary differential equations(ODEs)via the space-time decoupled formulation.To this end,the latent solution is expressed in the form of a linear combination of approximation functions and coefficients,where approximation functions are admissible and coefficients are unknowns of time that must be solved.Subsequently,the system of ODEs is obtained by implementing the weighted-residual form of the original PDE over the spatial domain.A multi-network structure is used to parameterize the set of coefficient functions,and the loss function of d PINN is established based on minimizing the residuals of the gained ODEs.In this scheme,the decoupled formulation leads to the independent handling of I/BCs.Accordingly,the BCs are automatically satisfied based on suitable selections of admissible functions.Meanwhile,the original ICs are replaced by the Galerkin form of the ICs concerning unknown coefficients,and the neural network(NN)outputs are modified to satisfy the gained ICs.Several benchmark problems involving different types of PDEs and I/BCs are used to demonstrate the superior performance of d PINN compared with regular PINN in terms of solution accuracy and computational cost.
基金Under the auspices of National Natural Science Foundation of China(No.42371315,41901213)Natural Science Foundation of Hubei Province(No.2020CFB856)Project of Changjiang Survey,Planning,Design and Research Co.,Ltd(No.CX2022Z23)。
文摘Investigating the ecological impact of land use change in the context of the construction of national water network project is crucial,as it is imperative for achieving the sustainable development goals of the national water network and guaranteeing regional ecological stability.Using the Danjiangkou Reservoir Area(DRA),China as the study area,this paper first examined the spatiotemporal dynamics of natural landscape patterns and ecosystem service values(ESV)in the DRA from 2000 to 2018 and then investigated the spatial clustering characteristics of the ESV using spatial statistical analysis tools.Finally,the patch-generating land use simulation(PLUS)model was used to simulate the natural landscape and future changes in the ESV of the DRA from 2018 to 2028 under four different development scenarios:business as usual(BAU),economic development(ED),ecological protection(EP),and shoreline protection(SP).The results show that:during 2000-2018,the construction of water facilities had a significant impact on regional land use/land cover(LULC)change,with a 24830 ha increase in watershed area.ESV exhibited an increasing trend,with a significant and growing spatial clustering effect.The transformation of farmland to water bodies led to accelerated ESV growth,while the transformation of forest land to farmland led to a decrease in the ESV.Normalized difference vegetation index(NDVI)had the strongest effect on the ESV.ESV exhibited a continuous increase from 2018 to 2028 under all the simulation scenarios.The EP scenario had the greatest increase in ESV,while the ED scenario had the smallest increase.The findings suggest that projected land use patterns under different scenarios have varied impacts on ecosystem services(ESs)and that the management and planning of the DRA should balance social,economic,ecological,and security benefits.nomic,ecological,and security benefits.
基金The authors thank seminar participants at the China Academic Conference on Computer Simulation and Information Technology for their helpful comments.
文摘Compared with common intelligent service,full-scene intelligent service has its uniqueness in high integration,synergy,and technological spillover.However,the traditional service or business model theories cannot precisely elaborate its sociotechnical contextual nature and value creation logic.To fill this knowledge gap,we provide initial insights into the value co-creation logic in full-scene intelligent service by exploring the value co-creation elements using a data-driven text mining approach.We analyzed 171 business reports on the full-scene intelligent service by the topic modeling using the Latent Dirichlet Allocation(LDA).The findings reveal three main clusters:value proposition,participants,and connection platform.This study presents a theoretical framework for a further exploratory case study and quantitative research on full-scene intelligent service.This study also helps small and medium-sized enterprises to explore and exploit value co-creation opportunities.
基金This study was supported by the Humanities and Social Sciences Project of the Ministry of Education(No.23YJA790070)the Graduate Innovation Research Project of Southwest Minzu University(No.YB2022621)the Research Project of BCIMY(No.BCIMY1910).
文摘Establishing a sense of ritual within tourism consumption scenarios offers tourists the opportunity for interactive engagement.Drawing upon the value co-creation theory,this study constructed an influence mechanism model to examine tourists'active engagement in the process of co-creating tourism experience values.It employed Partial Least Squares Structural Equation Modeling(PLS-SEM)to empirically test the proposed hypotheses.The findings demonstrate that the model constructed in the present study exhibits robust reliability,validity,and explanatory power.The perception of the sense of ritual in tourism exerts a significant positive influence on tourists’co-creation of tourism experience values,thereby significantly enhancing both the communitas and flow experienced by tourists during their travels.Moreover,such communitas and flow can mediate the influence of the sense of ritual in tourism on tourists’co-creation of tourism experience values.This study contributes to advancing the current research on tourists’co-creation of tourism experience values and the sense of ritual in tourism,thereby providing theoretical foundations for cultivating a sense of ritual within tourism consumption scenarios.
文摘Today,the e-commerce live broadcast industry has formed a huge market,and it has become one of the important ways for most netizens to purchase goods.Live streaming has brought new opportunities for e-commerce and new growth for brand value.The interaction between brands and customers has gradually expanded,in this case,the importance of value co-creation has become more and more prominent.This article will take e-commerce live broadcast marketing as the research object,and the brand value co-creation as the research perspective,then provide a direction based on the value co-creation perspective for the healthy and long-term development of e-commerce live broadcast marketing by studying and analyzing the cases of brand value co-creation.
文摘Rapid and accurate identification of high-quality patents can accelerate the transformation process of scientific and technological achievements, optimize the management of intellectual property rights and enhance the vitality of innovation. Aiming at the shortcomings of the traditional high-value patent assessment method, which is relatively simple and seldom considers the influence of patentees, this paper proposes a high-quality patent method HMFM (High-Value Patent Multi-Feature Fusion Method) that fuses multi-dimensional features. A weighted node importance assessment method in complex network called GLE (Glob-Local-struEntropy) based on improved structural entropy is designed to calculate the influence of the patentee to form the patentee’s features, and the patent text features are extracted by BERT-DPCNN deep learning model, which is supplemented to the basic patent indicator system. Finally a machine learning algorithm is used to assess the value of patents. Experiment results show that our method can identify high-value patents more effectively and accurately.
基金Supported by the National Natural Science Foundation of China(No:69872039)
文摘By defining fuzzy valued simple functions and giving L1(μ) approximations of fuzzy valued integrably bounded functions by such simple functions, the paper analyses by L1(μ)-norm the approximation capability of four-layer feedforward regular fuzzy neural networks to the fuzzy valued integrably bounded function F : Rn → FcO(R). That is, if the transfer functionσ: R→R is non-polynomial and integrable function on each finite interval, F may be innorm approximated by fuzzy valued functions defined as to anydegree of accuracy. Finally some real examples demonstrate the conclusions.
文摘In this paper, we give a smoothing neural network algorithm for absolute value equations (AVE). By using smoothing function, we reformulate the AVE as a differentiable unconstrained optimization and we establish a steep descent method to solve it. We prove the stability and the equilibrium state of the neural network to be a solution of the AVE. The numerical tests show the efficient of the proposed algorithm.
文摘The Maroochy River, which is located on east coast of Australia, provides a variety of uses and values to the community. Changes in structure, function and management of the river will influence the value that the community derives from it. Therefore, critical to the river’s continued management is the development of policy relevant tools based on the community’s value of the river. This paper focuses on estimating the fi-nancial value the local residents derive from living close to the river through investigation of changes in residential property values due to attributes of the Maroochy River. It is a complex analysis since there are several confounding geographical and property variables. Given a large and complete dataset of 28,000 properties for the Maroochy region, Artificial Neural Networks (ANN) was applied to estimate the economic value of the properties. This ANN was then able to simulate scenarios for property values with respect to changes in environmental features. It showed the Maroochy River contributed AU$900,000,000 to the unim-proved capital value of the whole region, a value that could not be estimated previously, and much higher than anticipated. Calculating potential annual payments to the Shire Council through land tax analysis from these property values, provides the council with means to justify expenditure to maintain a standard of water quality and ecosystem health.
文摘Objective To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific countermeasures. Methods A three-layer BP network was built to simulate topology and process of the eco-economy system of Xiangfan. Historical data of ecological environmental factors and socio-economic factors as inputs, and corresponding historical data of ecosystem service value (ESV) and GDP as target outputs, were presented to train and test the network. When predicted input data after 2001 were presented to trained network as generalization sets, ESVs and GDPs of 2002, 2003, 2004... till 2050 were simulated as output in succession. Results Up to 2050, the area would have suffered an accumulative total ESV loss of RMB 104.9 billion, which accounted for 37.36% of the present ESV. The coinstantaneous GDP would change asynchronously with ESV, it would go through an up-to-down process and finally lose RMB89.3 billion, which accounted for 18.71% of 2001. Conclusions The simulation indicates that ESV loss means damage to the capability of socio-economic sustainable development, and suggests that artificial neural networks (ANNs) provide a feasible and effective method and have an important potential in ESV modeling.
基金support from National Natural Science Foundation of China(Grant No.71971006)Humanities and Social Science Foundation of Ministry of Education of the People’s Republic of China(Grant No.19YJCGJW014).
文摘Purpose:With the availability and utilization of Inter-Country Input-Output(ICIO)tables,it is possible to construct quantitative indices to assess its impact on the Global Value Chain(GVC).For the sake of visualization,ICIO networks with tremendous low-weight edges are too dense to show the substantial structure.These redundant edges,inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis(SNA).In this case,we need a method to filter such edges and obtain a sparser network with only the meaningful connections.Design/methodology/approach:In this paper,we propose two parameterless pruning algorithms from the global and local perspectives respectively,then the performance of them is examined using the ICIO table from different databases.Findings:The Searching Paths(SP)method extracts the strongest association paths from the global perspective,while Filtering Edges(FE)method captures the key links according to the local weight ratio.The results show that the FE method can basically include the SP method and become the best solution for the ICIO networks.Research limitations:There are still two limitations in this research.One is that the computational complexity may increase rapidly while processing the large-scale networks,so the proposed method should be further improved.The other is that much more empirical networks should be introduced to testify the scientificity and practicability of our methodology.Practical implications:The network pruning methods we proposed will promote the analysis of the ICIO network,in terms of community detection,link prediction,and spatial econometrics,etc.Also,they can be applied to many other complex networks with similar characteristics.Originality/value:This paper improves the existing research from two aspects,namely,considering the heterogeneity of weights and avoiding the interference of parameters.Therefore,it provides a new idea for the research of network backbone extraction.
基金the Support Program for the Young Backbones of the College Teachers in Henan Province (No.[2005]461)the Key Technologies R &D Program of Henan Province (No.072102360052)
文摘Waste reduction is gaining importance as the preferred means of pollution prevention. Reactor network synthesis is one of the key parts of chemical process synthesis. In this study, a geometric approach to reactor network synthesis for waste reduction is presented. The bases of the approach are potential environment impact （PEI） rate-law expression, PEI balance and the instantaneous value of environmental indexes. The instantaneous value can be derived using the PEI balance, PEI rate-law expression and the environmental indexes. The optimal reactor networks with the minimum generation of potential environment impact are geometrically derived by comparing with areas of the corresponding regions. From the case study involving complex reactions, the approach does not involve solving the complicated mathematical problem and can avoid the dimension limitation in the attainable region approach.
基金Supported by University and College Doctoral Subject Special Scientific Research Fund( No. 20040056041).
文摘GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distribution and generalized Pareto distribution assumptions are adopted re- spectively to simulate the random component in the model. The demonstration of the quantile of network traffic series indicates that common GARCH-M model can partially deal with the "fat tail" problem. However, the "fat tail" characteristic of the random component directly affects the accura- cy of the calculation. Even t distribution is based on the assumption for all the data. On the other hand, extreme value theory, which only concentrates on the tail distribution, can provide more ac- curate result for high quantiles. The best result is obtained based on the generalized Pareto distribu- tion assumption for the random component in the GARCH-M model.
基金Under the auspices of National Natural Science Foundation of China(No.41971198)。
文摘Cross-border investment is essential for western China’s globalization.Global value chain(GVC)forms cross-border investment networks between industries in western China and overseas cities.Focusing on GVC,this study uses the social network analysis method,entropy method,multi-index comprehensive evaluation method,and quadratic assignment procedure analysis method to examine the characteristics and influencing factors of the urban networks of research and development(R&D),production,and sales formed as a result of the overseas investments of listed manufacturing companies in western China.Results showed that the three types of investment networks involved multiple industry types and multiple central cities with differentiated diversity and multicentrality.The R&D urban network’s leading sub-industries were the mechanical equipment and instruments,medicine and biological products,and metal and nonmetal industries.The destination cities were mostly those home to educational and scientific research centers.The production urban network’s leading sub-industries were the mechanical equipment,instrument,and food and beverage industries.The destination cities were mostly regional central cities in developing countries.The sales urban network’s leading sub-industries were the mechanical equipment and instrument,metal and nonmetal,and petrochemical and plastics industries.The destination cities were numerous and scattered.In addition,the R&D urban network easily formed specialized clusters,core nodes easily controlled the production urban network,and individual nodes did not easily control the sales urban network.Technological and economic system advantages greatly impacted the three network types.Considering the different influencing factors,this study suggests optimizing the institutional investment environment to narrow the institutional gap,adjusting and optimizing the investment layout to expand overseas markets,and increasing R&D funds to stimulate technological progress and overseas investments in western China.
基金Supported by National Natural Science Foundation of China(Grant Nos.52272433 and 11874110)Jiangsu Provincial Key R&D Program(Grant No.BE2021084)Technical Support Special Project of State Administration for Market Regulation(Grant No.2022YJ11).
文摘Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions(EOC),which are inevitable in the normal inspection of civil and mechanical structures.This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network(1D-CNN).After singular value decomposition-based feature extraction processing,a temporal robust damage index(TRDI)is extracted,and the effect of EOCs is well removed.Hence,even for the signals with a very large temperature-varying range and low signal-to-noise ratios(SNRs),the final damage detection and localization accuracy retain perfect 100%.Verifications are conducted on two different experimental datasets.The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises,and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20℃to 60℃.It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly,showing great potential for application in complex and unknown EOC.
文摘Recurrent Neural Networks were invented a long time ago, and dozens of different architectures have been published. In this paper we generalize recurrent architectures to a state space model, and we also generalize the numbers the network can process to the complex domain. We show how to train the recurrent network in the complex valued case, and we present the theorems and procedures to make the training stable. We also show that the complex valued recurrent neural network is a generalization of the real valued counterpart and that it has specific advantages over the latter. We conclude the paper with a discussion of possible applications and scenarios for using these networks.
文摘In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.
基金Sponsored by the National Natural Science Funds of China(Grant No.61271182)the National High Technology Research and Development Program of China(Grant No.2012AA01A508)the Fundamental Research Funds for the Central Universities of China(Grant No.2013RC0112)
文摘Network selection and resource allocation( NS-RA) are the processes of determining network and radio resource which provide the service to user. Optimizing these processes is an important step towards maximizing the utilization of current and future networks. In this paper,we proposed a preference value-based network selection and resource allocation,in which the NS scheme was performed by the joint radio resource management( JRRM) entity and the RA scheme was performed by the network. In the NS step,the JRRM entity selected the preferable network for users according to the preference value of each network,which took the load balance,the received signal strength( RSS) and the relative position between the user and the network into account. In the second step,the network allocated the optimal sub-carrier to user for the downlink transmission each round according to the preference value of each user and the maximum reachable data rate calculated by users' perceived channel information,maximizing the spectrum efficiency as well as guaranteeing the fairness. The simulation results showed that the proposed NS-RA scheme achieves better performance in terms of load distribution,spectrum efficiency and user fairness,compared to the conventional strategies.
