10-12 March 2017
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[Front cover]
Publication Year: 2017, Page(s): 1|
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[Title page]
Publication Year: 2017, Page(s): 1|
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[Copyright notice]
Publication Year: 2017, Page(s): 1|
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Table of contents
Publication Year: 2017, Page(s):iii - xv|
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Conference committees
Publication Year: 2017, Page(s):1 - 3|
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Author index
Publication Year: 2017, Page(s):1 - 7|
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Research and implementation of improved random forest algorithm based on Spark
Publication Year: 2017, Page(s):499 - 503In order to improve the efficiency and adaptability of classical random forest algorithm in large data environment, an improved random forest algorithm based on Spark is proposed. Firstly, an improved random forest algorithm (FRF) based on the Fayyad boundary point principle is proposed to deal with the shortcomings of classical random forest algorithm in the process of discretization of continuou... View full abstract»
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Using big data to enhance crisis response and disaster resilience for a smart city
Publication Year: 2017, Page(s):504 - 507
Cited by: Papers (2)High population growth, urbanization, and global climate change drive up the frequency of disasters, causing grave losses of people's lives and property worldwide. Additionally, globalization, technological development, and the changing roles of individuals in society will require entirely new approaches, tools, and capabilities to help inform decision making under uncertain conditions. However, t... View full abstract»
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Data augmented design: Urban planning and design in the new data environment
Publication Year: 2017, Page(s):508 - 512The new data environment composed by big data and open data has descripted urban physical and social space in a more detailed way. Currently, numerous quantitative urban studies have been conducted under new data environment. However, most studies concentrated on status quo evaluation and problem identification of urban system, and few of them have a perspective into future-oriented urban planning... View full abstract»
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Exploring the relationship between maize yield and climate big data on maize belt of northeast China
Publication Year: 2017, Page(s):513 - 516Data-driven agronomy is becoming popular by reducing the climate uncertainty in the era of agriculture big data. In this paper, many data mining approaches were used to extract embedded knowledge from climate variability and explore the relationship between NDVI data and maize yield. The results show that the Oct NDVI is important for Liaoning, while the Aug NDVI is important for Heilongjiang and ... View full abstract»
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Research on dynamic changes of urban square space in spatial and temporal based on Baidu thermal diagram a case study on the Wuyi square of Changsha
Publication Year: 2017, Page(s):517 - 522Using Baidu thermal diagram big data, analyzed the spatial and temporal behavior of Wuyi square, by applying spatial clustering, nuclear density analysis, spatial superposition and other spatial quantitative analysis method, verify and explain this time and space dynamic changes of internal factors. According to the analysis, under the support of Baidu thermal diagram big data, the dynamic changes... View full abstract»
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On the tourism marketing by WeChat official account of Dehong Dai and Jingpo autonomous prefecture for the National Day golden week in 2016 against the backdrop of big data
Publication Year: 2017, Page(s):523 - 526Researchers often discuss marketing strategies against the backdrop of big data, or use big data in tourism marketing. Limited is known about how a destination should use social media for tourism marketing at big data age. The paper is trying to do a tentative exploration for it by taking the WeChat tourism marketing of Dehong Dai and Jingpo autonomous prefecture for the national day golden week i... View full abstract»
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Construction for the city taxi trajectory data analysis system by Hadoop platform
Publication Year: 2017, Page(s):527 - 531To analysis the taxi trajectory data, an unified intelligent transportation platform which is based on Hadoop and massively parallel processing technology is constructed. In the intelligent transportation platform, the design model, function modules, technical scheme and SGD algorithm are proposed. Combining with the operation of the vehicle data, the platform realizes data analysis for vehicle tr... View full abstract»
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Revealing the characteristics of active area in the city by Taxi GPS data a study of Shenzhen, China
Publication Year: 2017, Page(s):532 - 536Taxi serves as a main transportation means for urban residents. The driving behavior recorded by Taxi GPS data can be a mirror to urban life. Therefore, this study adopts taxi GPS data to extract active area of the city and examine the weekday and weekend discrepancy. Moreover, the point of interests (POI) is combined to reveal the characteristics of the city. The method proposed in this study can... View full abstract»
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Design and implementation of a scalable distributed web crawler based on Hadoop
Publication Year: 2017, Page(s):537 - 541
Cited by: Papers (1)In this article, an efficient and scalable distributed web crawler system based on Hadoop will be design and implement. In the paper, firstly the application of cloud computing in reptile field is introduced briefly, and then according to the current status of the crawler system, the specific use of Hadoop distributed and cloud computing features detailed design of a highly scalable crawler system... View full abstract»
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Research on construction of data switching center for intelligence campus
Publication Year: 2017, Page(s):542 - 545Information constructions at colleges have transferred from digitalized campus to intelligence campus. Data switching center makes converting, cleansing, monitoring, comparison and other process to data of each business system, which provides an important support to intelligence campus. View full abstract»
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POI data applied in extracting the boundary of commercial centers
Publication Year: 2017, Page(s):44 - 47Twenty-first century as an important symbol of the era of the knowledge economy and big data, Internet and networking have a rapid development and have become indispensable data sources in people's lives. Besides, because of its convenience and quickness, these are increasingly applied in more and more aspects. Among them, POI as a true representative of the geographical entity on the network map ... View full abstract»
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A double-stage hierarchical ANFIS model for short-term wind power prediction
Publication Year: 2017, Page(s):546 - 551Output power determination of wind generators is always associated with some uncertainties due to wind speed and other weather parameters alteration, and precise short-term predictions are essential for their efficient operation. This can efficiently support transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, we propose ... View full abstract»
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Short-term wind power forecasting using a double-stage hierarchical hybrid GA-ANN approach
Publication Year: 2017, Page(s):552 - 556
Cited by: Papers (1)Power generation from wind generators is always associated with some intermittency due to wind speed and other weather parameters variation, and accurate short-term forecasts are essential for their efficient and effective operation. This can well support transmission and distribution system operators and schedulers to enhance the power network control and management in the smart grid context. Thi... View full abstract»
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The spectrum analysis technology and feature extraction of rotor system steady and speeding-change process
Publication Year: 2017, Page(s):557 - 562High-precision spectral analysis techniques are the important means to carry out research of rotor system stability. It can be achieved feature extraction parameters about rotor system steady-state and spectrum of vibration signals during speeding-change process. For a big calculation error problem existed in commercial software come with spectral analysis in the status, It is proposed that the sp... View full abstract»
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A probabilistic power flow algorithm based on semi-variable and series expansion
Publication Year: 2017, Page(s):563 - 567
Cited by: Papers (1)Traditional power flow algorithm such as the trend for front-and-spoke networks and backward substitution method and a cyclic structure NR method cannot fully reflect the uncertainties affecting the system, and a lot of new energy sources access to change the original properties of the grid, so that a single flow algorithm has significant limitations, the study calculated adapt to the trend of lar... View full abstract»
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Research on output characteristics of large-scale wind farms in coastal area randomness concerned
Publication Year: 2017, Page(s):568 - 572In order to study coastal intensive large-scale wind farm output characteristics and interrelatedness, take large-scale wind farm in coastal Jiangsu as an example, based on the measured wind power output data in EMS systems correlation between wind farms and the active output probability distributions, the monthly maximum output were analyzed. Studied the active output fluctuations of wind farms a... View full abstract»
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Research on impact of prediction error of new energy on power grid based on probabilistic power flow algorithm
Publication Year: 2017, Page(s):573 - 577
Cited by: Papers (1)Research on evaluation for overload probability, probability-limit and static safety of voltage based on stochastic trend, can be used to discover vulnerabilities in the power grid. Wind power output, load changes, forced outages and generator fault lines and other uncertainties were considered. Random disturbances of large-scale new energy generation accessing the grid concerned, linear Monte Car... View full abstract»
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Feature extraction of electric information acquisition system based on Haar wavelet transform
Publication Year: 2017, Page(s):578 - 583This paper studies the structure features of the collected power consumers' power consumption data, in which the 96 measured data points indicating a single user's power consumption curve of a day. The 96 measured data points are taken as 96 variables for analysis. The dimensionality of original data is reduced by principal component analysis (PCA), and then the K-means algorithm is employed to cl... View full abstract»