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检索条件"任意字段=2nd International Conference on Algorithms for Big Data, ICABD 2014"

共 223 条记录，以下是61-70 订阅

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An improved algorithm for international cooperation competitiveness 2

An improved algorithm for international cooperation competit...

引用

2022 2nd international conference on Artificial Intelligence, big data and algorithms, CAIBDA 2022

作者： Liu, Yang Zhang, Yan Northwestern Polytechnical University Development and Planning Office Shaanxi Xi'an710072 China Northwestern Polytechnical University Library Shaanxi Xi'an710072 China

ISBN: (纸本)9783800760268

In the era of knowledge economy, the use of big data to assist scientific research management and decision-making is a common concern of researchers. The international (regional) Cooperation and Exchange Projects in NSFC are the concentrated embodiment of international cooperation competitiveness. In this article, we use the data dictionary function of the Cingta big data platform to obtain 11078 international Cooperation Project data in 31 provinces from 2010 to 2019. The international cooperation competitiveness of each province was comprehensively analyzed by constructing the revised comprehensive international cooperation competitiveness index, subject international cooperation competitiveness index and institution international cooperation competitiveness index respectively. It provides reference basis for national and regional scientific research institutions to formulate relevant scientific research policies. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： international cooperation

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Testing Problems of Agglomeration Degree algorithms Based on Shaanxi data

Testing Problems of Agglomeration Degree Algorithms Based on...

引用

big data, Information and Computer Network (BDICN), international conference on

作者： Aixiong Gao Yingqin Zhang Ru Liu International Business School Shaanxi Normal University Xi’an P.R.China School of Economics and Management Xi’an University of Posts and Telecommunications Xi’an P.R.China

In order to test potential problems of agglomeration degree algorithms, EG algorithm is presented to measure the industrial agglomeration for each of 90 industries and their sub-industries based on micro data of firms in Shaanxi. Conclusions are drawn that: (1) Modifiable areal unit problem exists because of decreasing agglomeration with smaller geographic areas aggregation; (2) Average agglomeration of sub-industries is mostly higher than their parent industries; (3) HHI has insignificant correlation with industrial agglomeration; (4) Agglomeration measured based on data of manufacturing industries has similar results with data of overall industries.

关键词： Industries Manufacturing industries Correlation Benchmark testing big data Market research Computer networks

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Improved K-Nearest Neighbor Missing data Classification Based on Interval Value Imputation

Improved K-Nearest Neighbor Missing Data Classification Base...

引用

Electrical Engineering, big data and algorithms (EEBDA), IEEE international conference on

作者： Ziyang Zhang Can Tang School of Mathematics and Statistics Shandong University of Finance and Economics Jinan China International School Beijing University of Posts and Telecommunications Beijing China

In reality, when processing data sets for classification, there are often missing data sets, which brings inconvenience to the classification work. To this end, this paper proposes a method to impute incomplete data based on the interval value of K nearest neighbors. The method uses the Euclidean distance between the incomplete data and the complete data to find the K closest complete data to the incomplete data, so that the nearest neighbor can be constructed according to the corresponding attribute value of the complete data to the missing attribute value of the incomplete data. interval. Next, the dataset is constructed into an interval-valued dataset. Based on the interval-valued distance algorithm, the incomplete data can be classified by the K-nearest neighbor algorithm. The experimental results show that the improved K-nearest neighbor algorithm based on interval value imputation is more efficient than the traditional 0-value imputation, median imputation and mean imputation K-nearest neighbor algorithm under certain circumstances.

关键词： Training Electrical engineering Euclidean distance big data Classification algorithms

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The Advancement of Biomedical Relation Extraction through Cloud Computing and big data Analysis 2

The Advancement of Biomedical Relation Extraction through Cl...

引用

2nd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2022

作者： Wang, Zishuo Fujian Agriculture and Forestry University International College Fuzhou350007 China

ISBN: (数字)9781728181158

ISBN: (纸本)9781728181158

Due to the development of biology and medicine, more and more biomedical relationships are collected in the literature. Meanwhile, with the completion of the human genome project, the post-genome era is beginning. Proteomics, metabolomics, and other interdisciplinary disciplines formed by biology, medicine, and information technology are constantly emerging. In this case, Biomedical information extraction brings a faster and more convenient retrieval mechanism for medicine, which can make doctors consult the interaction between drugs more quickly to avoid adverse drug reactions. Specifically, it brings a more efficient pre-experiment to the field of biological research because a large number of protein interactions are presented on the computer without the need for researchers to extract them from the literature. However, this emerging field often faces significant challenges. (1) The imbalance of data sets makes computers deceive themselves and produce a tendentious result. (2) Annotating the training dataset is a waste of human and material resources. (3) The accuracy of the results obtained by different algorithms is too low. This paper summarizes the research progress in this field in recent years including most classical methods, e.g., rule-based, supervised and unsupervised, On this basis, the existing problems in this field are demonstrated and corresponding feasible solutions are proposed. Finally, through the basic knowledge and development momentum of biology and computer science, this field's future development direction and improvement direction are discussed. Overall, these results shed light on the progress of biomedical research, the practical operation norms of biology and medicine and the improvement of research efficiency. © 2022 IEEE.

关键词： big data

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Design model of maximum output power of wave energy

Design model of maximum output power of wave energy

引用

Electrical Engineering, big data and algorithms (EEBDA), IEEE international conference on

作者： Bo Liu Rui Zhao Weiqin Wang Maynooth International Engineering College Fuzhou University Fuzhou China

Traditional fuel is increasingly exhausted, and environmental problems are becoming more and more serious. Therefore, the development and utilization of low carbon, energy saving and green. Renewable energy is the theme of energy development in today's era. Wave energy has a high energy density and little energy loss during its propagation. In this paper, the force analysis of wave energy devices under different states is carried out, and the mathematical model is established to maximize the energy conversion efficiency of wave energy devices. The model established in this paper accords with the physical law, and the results obtained are in line with the objective reality. The output power of the wave energy device in one cycle is relatively ideal.

关键词： Analytical models Renewable energy sources Green products Force Hydrodynamics Reliability engineering data models

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The Principle and Applications of Asynchronous FIFO

The Principle and Applications of Asynchronous FIFO

引用

Electrical Engineering, big data and algorithms (EEBDA), IEEE international conference on

作者： Zixu Hao Lingxi Liu Birong Tian Department of Informatics Beijing University of Technology Beijing China International School of Nanjing Yuhuatai High School Nanjing China College of Science Wuhan University of Technology Wuhan China

With the rapid development of integrated circuits, a complete system of integrated Circuits contains multiple clocks in a chip. Under the control of different clock domains, data can become metastable state between transfers or storage. This paper describes one of the effective methods to solve the problem about the metastable state, the method is asynchronous FIFO. We study Synchronous FIFO and Asynchronous FIFO in this paper. The article analyses the reasons for the emergence of sub-stability metastable state and how to use the Gray Code to solve metastable state problems effectively. We can generate empty/full status bits via Gray Code pointer, it can effectively reduce the probability of metastable state. This paper has the significance of guiding the use of FIFO.

关键词： Integrated circuits Electrical engineering Codes big data Stability analysis Reflective binary codes Synchronization

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Research on Multi-AGVs Cooperative Transportation Strategy in Warehouse Logistics Environment Based on HCA Algorithm

Research on Multi-AGVs Cooperative Transportation Strategy i...

引用

Electrical Engineering, big data and algorithms (EEBDA), IEEE international conference on

作者： Yuanzhuo Li Chang’an Dublin International College of Transportation Chang’an University Xi’an China

With the development of science and technology in the logistics industry, logistics robots have become the choice of more and more enterprises, which can reduce costs and improve work efficiency. Compared with the application of single AGV (Automated Guided Vehicle) in logistics transportation, the multi-AGVs method is more widely used. The basic A-star algorithm can provide path planning for single AGV in the static road network. Furthermore, HCA (Hierarchical Cooperative A-Star algorithms) introduces time quantity based on A-star to achieve path planning for multiple AGVs. This paper uses HCA algorithm and introduces Manhattan distance into grid map. Then, a multi-AGVs cooperative transportation strategy is proposed. The storage and transportation environment is simulated under the simulation environment of Webots. The multi-AGV cooperative transportation strategy proposed in this paper is verified and analyzed. Simulation results demonstrate the practicability of the navigation algorithm and the feasibility of the strategy.

关键词： Remotely guided vehicles Navigation Service robots Simulation Roads Warehousing Transportation

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Research of Classification Methods based on Machine Learning

Research of Classification Methods based on Machine Learning

引用

Health big data and Intelligent Healthcare (ICHIH), international conference on

作者： Jiyang Pan International College Nanjing Audit University Nanjing 211815 China

This paper mainly introduces three important machine learning algorithms: logistic regression, nearest neighbor and Bayes. First of all, the principle of each algorithm is explained, introducing the basic knowledge of each algorithm. Then, the formulas for each algorithm are derived, making the abstract concepts simple and easy to understand. Finally, the practical functions of the three algorithms in different fields are introduced. An example of logistic regression is the calculation of mortality, which is calculated by studying various physical characteristics of the patient. The nearest neighbor algorithm plays a role in predicting customer behavior. By improving the nearest neighbor algorithm, experimenters can classify data sets more easily and make the results of predictive analysis more accurate. Bayes algorithm plays an important role in predicting the type of disease. Researchers can predict the disease more accurately by analyzing and calculating the characteristics of patients. It greatly reduces the probability of misdiagnosis and missed diagnosis, and improves the efficiency of diagnosis.

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Attribute prediction of Pokémon images based on convolutional neural network

Attribute prediction of Pokémon images based on convolution...

引用

Electrical Engineering, big data and algorithms (EEBDA), IEEE international conference on

作者： Junwei Justin Chu Zijie Shan Xiang Sun Canadian International School of Guangzhou Guangzhou China

Image recognition has long been a fundamental research problem in computer vision, where the goal is to predict the class of a given image. Existing researches have focused on the category level while pay no attention on predicting object fine attribute information of object. To this end, in this paper, in order to investigate the classification effect of convolution neural network on Pokémon image data set, we use convolution neural network to classify the attributes of Pokémon, which can judge the attributes of a certain elf by its image. We used the pictures of the Pokémon in a scorching game "Pokémon " on the market as our data set. Specifically, we first a structure of the convolutional neural network and apply it to the Pokémon image data set, which can realize automatic recognition and attribute classification of elf images. Then the data enhancement method is used to preprocess the image data, which is combined with a convolutional neural network to improve the effect of attribute recognition and classification. Results show the effectiveness of our proposed method.

关键词： Electrical engineering Computer vision Image recognition Convolution Neural networks Games Predictive models

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Proceedings - 2022 international conference on Artificial Intelligence in Everything, AIE 2022

Proceedings - 2022 International Conference on Artificial In...

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2nd IEEE international conference on Artificial Intelligence in Everything, AIE 2022

ISBN: (纸本)9781665474009

The proceedings contain 127 papers. The topics discussed include: application of big data technology in rail transit vehicle manufacturing;key technologies of system big data oriented to intelligent network applications;auxiliary technology of firewall based on computer virus detection;comparison of compensation topologies for wireless charging systems in EV applications;intelligent mining method of audit data characteristics under financial shared service mode;grid development stages and saturation load forecasting based on logistic model;a comparison of approximate analytic and neural network solutions for effective mass Schrodinger equation with Yukawa’s potential;selection of energy internet economic value indicators based on interpretative structural modeling;optimal design of green building landscape space environment based on multiple path-finding algorithms;and the influence of computer vision algorithm on brain function network related to Parkinson’s disease.

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