Modeling and application of marketing and distribution data based on graph computing

Integrating marketing and distribution businesses is crucial for improving the coordination of equipment and the efficient management of multi-energy systems.New energy sources are continuously being connected to distribution grids;this,however,increases the complexity of the information structure of marketing and distribution businesses.The existing unified data model and the coordinated application of marketing and distribution suffer from various drawbacks.As a solution,this paper presents a data model of"one graph of marketing and distribution"and a framework for graph computing,by analyzing the current trends of business and data in the marketing and distribution fields and using graph data theory.Specifically,this work aims to determine the correlation between distribution transformers and marketing users,which is crucial for elucidating the connection between marketing and distribution.In this manner,a novel identification algorithm is proposed based on the collected data for marketing and distribution.Lastly,a forecasting application is developed based on the proposed algorithm to realize the coordinated prediction and consumption of distributed photovoltaic power generation and distribution loads.Furthermore,an operation and maintenance(O&M)knowledge graph reasoning application is developed to improve the intelligent O&M ability of marketing and distribution equipment.

THE STATIONARY DISTRIBUTION OF A CONTINUOUS－TIME RANDOM GRAPH PROCESS WITH INTERACTING EDGES

In previous papers, the stationary distributions of a class of discrete and continuoustime random graph processes with state space consisting of the simple and directed graphs on Nvenices were studied. In this paper, the random graph graph process is extended one impotent stepfurther by allowing interaction of edges. Similarly, We obtha the expressions of the stationarydistributions and prove that the process is ergodic under different editions.

Brain Functional Network Generation Using Distribution-Regularized Adversarial Graph Autoencoder with Transformer for Dementia Diagnosis

The topological connectivity information derived from the brain functional network can bring new insights for diagnosing and analyzing dementia disorders.The brain functional network is suitable to bridge the correlation between abnormal connectivities and dementia disorders.However,it is challenging to access considerable amounts of brain functional network data,which hinders the widespread application of data-driven models in dementia diagnosis.In this study,a novel distribution-regularized adversarial graph auto-Encoder(DAGAE)with transformer is proposed to generate new fake brain functional networks to augment the brain functional network dataset,improving the dementia diagnosis accuracy of data-driven models.Specifically,the label distribution is estimated to regularize the latent space learned by the graph encoder,which canmake the learning process stable and the learned representation robust.Also,the transformer generator is devised to map the node representations into node-to-node connections by exploring the long-term dependence of highly-correlated distant brain regions.The typical topological properties and discriminative features can be preserved entirely.Furthermore,the generated brain functional networks improve the prediction performance using different classifiers,which can be applied to analyze other cognitive diseases.Attempts on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset demonstrate that the proposed model can generate good brain functional networks.The classification results show adding generated data can achieve the best accuracy value of 85.33%,sensitivity value of 84.00%,specificity value of 86.67%.The proposed model also achieves superior performance compared with other related augmentedmodels.Overall,the proposedmodel effectively improves cognitive disease diagnosis by generating diverse brain functional networks.

The Visualization Analysis of Research Hotspot and Frontier Technology of the Smart Power Distribution and Utilization Based on the Cite Space

In order to make an intensive study of the development of smart power distribution and utilization technology in China, their research hotspots and frontier technology are selected out through combining the informatics method, and using the CiteSpace which can take keyword cooccurrence analysis and draw the visualization graph. According to this result, we can infer the development trend of smart power distribution and utilization in the future, and providing reference for the researcher whose engage in this domain. The electric related literature was collected from the CNKI database in China. Under the smart power distribution and utilization domain, we also analyze the development of the power quality and the energy internet in detail.

Effects of Social Security Spending on Income Distribution and Poverty Reduction in China

Reasonable income distribution and eradication of rural poverty are vital for building a moderately prosperous society in all respects in China.This paper primarily examines the income distribution and poverty reduction effects of social security spending.Market income and redistribution policies are two determinants of income gaps.Based on CHIP2018 household survey data,we find that inadequate income redistribution policies have contributed to yawning income gaps,and that social security spending is more redistributive than personal income tax and social security contributions.After estimating the redistribution effects of social security spending and itemized incomes,we find that pension payments have contributed the most to household income gaps,and that subsistence protection and rural pension payments help improve income distribution.With respect to the poverty reduction effects of social security spending,we have estimated China’s current poverty incidence and the poverty reduction effects of pension payments,healthcare,and educational allowances with CHIP2018 data,and discover that an increase in social security spending may effectively reduce rural poverty.In building a moderately prosperous society in all respects,China should increase social security spending,focusing on specific target groups,and promote the role of social security spending in regulating income distribution and offering social protection to rural residents.

Similarity matching method of power distribution system operating data based on neural information retrieval

Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.

Spatial Distribution of Domestic Tourism Market in Inner Mongolia Autonomous Region and Its Development Strategies

This paper, based on the statistical data from the Sample Survey of Domestic Tourism in Inner Mongolia(2014), analyzed the distribution of the domestic tourism market across Inner Mongolia and its 4 tourism sections through indexes including market concentration ratio, geographic concentration ratio, variance, etc.. The results showed that:(1) the market within the autonomous region remained to be the largest one in those 4 sections;(2) Beijing was the largest domestic tourism market outside Inner Mongolia;(3) different sections were divided on the target market of domestic tourism:(1) Beijing-Tianjin-Hebei Region proved to be the primary market of Inner Mongolia at large;(2) Beijing and 3 provinces in Northwest China came as the primary markets of Hulun Buir-Hinggan section;(3) Beijing-Tanjin-Hebei Region and Liaoning Province were the primary markets of Xilingol-Chifeng-Tongliao section;(4) BeijingShanxi-Hebei Region turned out to be the primary market of Huhhot-Baotou-Erdos-UlanqabBayannur section;(5) Beijing and Gansu were the primary markets of Wuhai-Alxa section;(4) the market concentration ratio of domestic tourism in different sections varied from each other, and the east section was the highest one, followed by middle section, Inner Mongolia as a whole, west section, and northeast section. As a result, authors of this paper made recommendations on how to develop the domestic tourism in Inner Mongolia.

China's Air Transport Market and Distribution of airports

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Researches on the Distribution Domains of G(4) G(4)的分布域之研究

讨论了有固定的最大度△=4和n个顶点的一类无自环,无向、连通平面图G(△)的异构类的分布域R(v,n)(圈秩v=1---n+1)的三种情况,从而获得R(v,n)的A型、B型和C型的分布定理,并举例说明分布域在图论和碳氢化合物上的应用。

Data-driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

Reactive power optimization of distribution networks is traditionally addressed by physical model based methods,which often lead to locally optimal solutions and require heavy online inference time consumption.To improve the quality of the solution and reduce the inference time burden,this paper proposes a new graph attention networks based method to directly map the complex nonlinear relationship between graphs(topology and power loads)and reactive power scheduling schemes of distribution networks,from a data-driven perspective.The graph attention network is tailored specifically to this problem and incorporates several innovative features such as a self-loop in the adjacency matrix,a customized loss function,and the use of max-pooling layers.Additionally,a rulebased strategy is proposed to adjust infeasible solutions that violate constraints.Simulation results on multiple distribution networks demonstrate that the proposed method outperforms other machine learning based methods in terms of the solution quality and robustness to varying load conditions.Moreover,its online inference time is significantly faster than traditional physical model based methods,particularly for large-scale distribution networks.

PRICING EUROPEAN OPTION IN A DOUBLE EXPONENTIAL JUMP-DIFFUSION MODEL WITH TWO MARKET STRUCTURE RISKS AND ITS COMPARISONS

Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.

State-of-the-Art Analysis and Perspectives for Peer-to-Peer Energy Trading

As a promising solution to address the“energy trilemma”confronting human society,peer-to-peer(P2P)energy trading has emerged and rapidly developed in recent years.When carrying out P2P energy trading,customers with distributed energy resources(DERs)are able to directly trade and share energy with each other.This paper summarizes and analyzes the global development of P2P energy trading based on a comprehensive review of related academic papers,research projects,and industrial practice.Key aspects in P2P energy trading are identified and discussed,including market design,trading platforms,physical infrastructure and information and communication technology(ICT)infrastructure,social science perspectives,and policy.For each key aspect,existing research and practice are critically reviewed and insights for future development are presented.Comprehensive concluding remarks are provided at the end,summarizing the major findings and perspectives of this paper.P2P energy trading is a growing field with great potential and opportunities for both academia and industry across the world.

Importance of Generalized Logistic Distribution in Extreme Value Modeling

We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are the classical distributions for this problem. However, from 2004, [1] and many other researchers have been empirically showing that generalized logistic (GL) distribution is a better model than GEV and GP distributions in modeling extreme movement of stock market data. In this paper, we show that these results are not accidental. We prove the theoretical importance of GL distribution in extreme value modeling. For proving this, we introduce a general multivariate limit theorem and deduce some important multivariate theorems in probability as special cases. By using the theorem, we derive a limit theorem in extreme value theory, where GL distribution plays central role instead of GEV distribution. The proof of this result is parallel to the proof of classical extremal types theorem, in the sense that, it possess important characteristic in classical extreme value theory, for e.g. distributional property, stability, convergence and multivariate extension etc.

Robust Consensus Tracking Control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

In this paper,a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph.It is of two-degree-of-freedom nature.Specifically,a robust distributed controller is designed for consensus tracking,while a local disturbance estimator is designed for each agent without requiring the input channel information of disturbances.The condition for asymptotic disturbance rejection is derived.Moreover,even when the disturbance model is not exactly known,the developed method also provides good disturbance-rejection performance.Then,a robust stabilization condition with less conservativeness is derived for the whole multi-agent system.Further,a design algorithm is given.Finally,comparisons with the conventional one-degree-of-freedombased distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.

Managing Channels of Distribution Under the Environment of Electronic Commerce

Business Marketing Management over the Internet has been receiving a“lot of ink”in current periodicals and to a lesser degree in academic literature.Practice changes so rapidly that principles emerging from last month’s successes may need revi- sion before they are derived and printed.The emergence of electronic commerce has created a new business paradigm,one that pre- sents marketers with noteworthy opportunities and challenges.Perhaps the greatest impact is in the area of channel management. The top issue for many business-to-business (B2B) firms today is channel conflict.In this paper,we analyze the weakness of traditional place model at first.On the basis of it,we set forth the processes and advantages of direct place and indirect place un- der the environment of electronic commerce.Then this paper presents that we should develop association net,express net,service net and production net in order to create place advantage under the environment of electronic commerce.

Precise Asymptotic Distribution of the Number of Isolated Nodes in Wireless Networks with Lognormal Shadowing

In this paper, we study the connectivity of multihop wireless networks under the log-normal shadowing model by investigating the precise distribution of the number of isolated nodes. Under such a realistic shadowing model, all previous known works on the distribution of the number of isolated nodes were obtained only based on simulation studies or by ignoring the important boundary effect to avoid the challenging technical analysis, and thus cannot be applied to any practical wireless networks. It is extremely challenging to take the complicated boundary effect into consideration under such a realistic model because the transmission area of each node is an irregular region other than a circular area. Assume that the wireless nodes are represented by a Poisson point process with densitynover a unit-area disk, and that the transmission power is properly chosen so that the expected node degree of the network equals lnn + ξ (n), where ξ (n) approaches to a constant ξ as n →?∞. Under such a shadowing model with the boundary effect taken into consideration, we proved that the total number of isolated nodes is asymptotically Poisson with mean e$ {-ξ}. The Brun’s sieve is utilized to derive the precise asymptotic distribution. Our results can be used as design guidelines for any practical multihop wireless network where both the shadowing and boundary effects must be taken into consideration.

Calculation of the Water Distribution Networks Based on the Theory of Slow Transient Flow

Urban water supply network is a modern urban survival and development of the infrastructure of a city,and its normal running conditions have important significance. The actual hydraulic process in the variableload water distribution networks can be treated as the slow transient flow which belongs to the unsteady flow. This paper analyzes the multi-loops network slow transient model based on graph theory,and the link flow matrix is treated as the variables of the discrete solution model to simulate the process of the slow transient flow in the network. With the simulation of hydraulic regime in an actual pipe network,the changing laws of the flow in the pipes,nodal hydraulic heads and other hydraulic factors with the passage of time are obtained. Since the transient processes offer much more information than a steady process,the slow transient theory is not only practical on analyzing the hydraulic condition of the network,but also on identifying hydraulic resistance coefficients of pipes and detecting the leakage in networks.

The Security Correction of Large Consumers Long-Term Direct Power Trading Based on DC Power Transfer Distribution Factor

The experiments of large consumers direct power trading is conducting in china nationwide, and it’s important to the reform of electricity market. To compensated efficiencies in security correction of large consumers direct power trading, a novel security correction method based on DC power transfer distribution factor was proposed. Using the presented method to comply security correction, all the transactions that satisfy the specific requirements of maximizing social welfare are able to enter security correction process, and when the power of transmission line is out of limit, this method avoid the transaction which causes this problem is abandoned directly by introducing supplement transactions. The simulation has shown that the proposed security correction method of large consumers direct power trading based on DC power transfer distribution factor is effective.

Distribution of Market Share in the World Soft-Drink Industry

The distribution of market shares within an industry is a relevant performance measure for managers and policy makers, for it allow to determine whether a given industry is competitive or not. Usually, the perfect competition model is the reference to judge the efficiency of markets. However, there is enough empirical evidence that shows that one of the most evident features of global firms is that both their size and market are Zipf-distributed. In this paper, we show that the distribution of market shares in the world cola-drink market is skewed, but it does not follow Zipf＇s law, thus it is inadequate to generalize it to any kind of market.

Modeling the Proposal of the Simultaneous Purchases and Sales of Electricity and Gas for the Energy Market in a Microgrid Using the Harmony Search Algorithm

The use of different energy carriers together,known as an energy hub,has been a hot topic of research in recent years amongst scientists and researchers.The term energy hub refers to the simultaneous operation of various infrastructures for energy generation and transfer,which has gained momentum in the form of microgrids(MGs).This paper introduces a new strategy for the optimal performance of an MG consisting of different energy carriers for each day.In a smart distribution network(DN),MGs can reduce their own costs in the previous-day market by bidding on sales and purchases.The sales and purchases bidding problem is challenging due to different uncertainties,however.This paper proposes a two-stage strategy for making an optimal bid on electricity sales and purchases with electricity and gas price dependency in the previous-day and real-time markets for an energy hub.In this model,the MG behavior regarding the electricity and gas energy sales/purchase,the simultaneous effects of electricity and gas prices,as well as the energy carriers’dependence on one another are all examined.Due to the inherent uncertainty in the sources of clean energy production,the probabilistic model and the production and reduction scenario have been used in the paper to cover this issue.In the proposed grid,energy sales/purchases are presented in a multi-carrier MG in a two-stage model.This model is solved by using the harmony search algorithm in MATLAB.Numeric results demonstrate the benefits of this model in reducing energy hub costs of operation.