Research on Interpolation Method for Missing Electricity Consumption Data

Missing value is one of the main factors that cause dirty data.Without high-quality data,there will be no reliable analysis results and precise decision-making.Therefore,the data warehouse needs to integrate high-quality data consistently.In the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate.For the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity data.First,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data information.All missing data are randomly interpolated within the upper and lower limits.Then,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption data.At last,this process is implemented iteratively until the missing values do not change.Under a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete data.Also,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

GRU-based Buzzer Ensemble for Abnormal Detection in Industrial Control Systems

Recently,Industrial Control Systems(ICSs)have been changing from a closed environment to an open environment because of the expansion of digital transformation,smart factories,and Industrial Internet of Things(IIoT).Since security accidents that occur in ICSs can cause national confusion and human casualties,research on detecting abnormalities by using normal operation data learning is being actively conducted.The single technique proposed by existing studies does not detect abnormalities well or provide satisfactory results.In this paper,we propose a GRU-based Buzzer Ensemble for AbnormalDetection(GBE-AD)model for detecting anomalies in industrial control systems to ensure rapid response and process availability.The newly proposed ensemble model of the buzzer method resolves False Negatives(FNs)by complementing the limited range that can be detected in a single model because of the internal models composing GBE-AD.Because the internal models remain suppressed for False Positives(FPs),GBE-AD provides better generalization.In addition,we generated mean prediction error data in GBE-AD and inferred abnormal processes using soft and hard clustering.We confirmed that the detection model’s Time-series Aware Precision(TaP)suppressed FPs at 97.67%.The final performance was 94.04%in an experiment using anHIL-basedAugmented ICS(HAI)Security Dataset(ver.21.03)among public datasets.

Research of Order Allocation Model Based on Cloud and Hybrid Genetic Algorithm Under Ecommerce Environment

For massive order allocation problem of the third party logistics （TPL） in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm （GA）, implementing cloud deployable MapReduce （MR） code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming （MIP） as fitness flmction to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform （LIP） in near future, implementing fast auto-allocation for massive concurrent orders, with great application value.

An efficient three-party password-based key agreement protocol using extended chaotic maps

Three-party password-based key agreement protocols allow two users to authenticate each other via a public channel and establish a session key with the aid of a trusted server. Recently, Farash et al. [Farash M S, Attari M A 2014 ＂An efficient and provably secure three-party password-based authenticated key exchange protocol based on Chebyshev chaotic maps＂, Nonlinear Dynamics 77（7）： 399-411] proposed a three-party key agreement protocol by using the extended chaotic maps. They claimed that their protocol could achieve strong security. In the present paper, we analyze Farash et al.＇s protocol and point out that this protocol is vulnerable to off-line password guessing attack and suffers communication burden. To handle the issue, we propose an efficient three-party password-based key agreement protocol using extended chaotic maps, which uses neither symmetric cryptosystems nor the server＇s public key. Compared with the relevant schemes, our protocol provides better performance in terms of computation and communication. Therefore, it is suitable for practical applications.

Studies on the Belt and Road Initiative and the China—Mongolia—Russia Culture Industry Corridor

Culture is the concentrated reflection of national spirit and civilization, and is an important part of foreign exchanges since ancient times. Under the guidance of the Belt and Road Initiative, with the goal of reviving the Prairie Silk Road and Culture Industry Corridor suited to the China-Mongolia-Russia Economic Corridor, in accordance with the requirements in the China, Mongolia and Russia Tripartite Cooperation Medium-term Road Map approved by the three countries, government organs, enterprises and social organizations should make appropriate plans to develop cultural tourism in advance, highlight its characteristics, build the brand, build investment and financing platforms, new media platforms and carry out large-project-driving strategies, so that the value of cultural resources along the Prairie Silk Road can be fully tapped and resources can be integrated for industrial and economic advantages. The interconnection of China's Belt and Road Initiative, Mongolia's Prairie Road and Russia's Eurasian Economic Union will help establish closer cooperation between the three countries and form an arena of culture competition in Northeast Asia. This is of great practical significance and has promising prospects.

Review of IT/IS Adoption and Decision-Making Behavior in Small Businesses

The increased use of information technologies has led to more research on information technology/information system （IT/IS） adoption and decision-making behavior in small businesses to improve information utilization. This paper presents an extensive review of the literature on IT/IS adoption to identify the key factors affecting small businesses based on comparison analysis. The review identifies the current interest in the adoption of Internet based IT and points out that the factors affecting different stages of the business lifecycle and research variables should be selected in terms of the different technology types. Especially, the review emphasizes the characteristics of external openings on the network in the research on e-commerce adoption. Future studies should focus on IT/IS adoption and implementation in small and medium-sized businesses during the development of small and medium-sized industrial clusters and specialty towns.