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CLUSTERING MINING ALGORITHM OF INTERNET OF THINGS DATABASE BASED ON python language

COMPUTING AND INFORMATICS 2023年第5期42卷 1136-1157页

作者： Wan, Fang Liu, Ying Nanchang Jiaotong Inst Business Coll Nanchang 330100 Jiangxi Peoples R China Nanchang Jiaotong Inst Sch Artificial Intelligence Nanchang 330100 Jiangxi Peoples R China

In order to solve the problems of reading delay in data mining of the Internet of Things database, a clustering mining algorithm of the Internet of Things database based on python language is proposed. We designed an improved crawler algorithm based on the open-source structure of scratch through python language, judge the similarity of recruitment data topics in the Internet of Things database through Bayesian classifier, and crawl the recruitment data in the Internet of Things database: the number of keywords in the text space, the degree of keyword extraction, and the number of keyword data in the text space. The time series model is used to eliminate the delay of text features. On this basis, the semi-supervised learning and semi-cluster analysis method is used to construct the corresponding classifier, complete the adaptive classification process of the text data stream and realize the clustering mining of the Internet of Things database based on python language. The experimental results show that this method has a low reading delay, and can mine the attention, number of posts and click time frequency of the Internet of Things database from which the recruitment data are obtained.

关键词： python language Internet of Things database data clustering data mining

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Research on Multi-Parameter Error Model of Backcalculated Modulus Using Abaqus Finite Element Batch Modeling Based on python language

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BUILDINGS 2024年第11期14卷 3454-3454页

作者： Xiong, Chunlong Yu, Jiangmiao Zhang, Xiaoning Luo, Chuanxi South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510640 Peoples R China Guangzhou Xiaoning Roadway Engn Technol Res Inst C Guangzhou 510641 Peoples R China

The error in modulus backcalculation is a crucial component in validating the rationality and reliability of results for engineering applications. The objective of this study is to identify the theoretical limitations associated with backcalculated modulus errors under typical parameter uncertainties and to determine the primary factors contributing to these errors. Firstly, using the actual measurements or data from the Long-Term Pavement Performance (LTPP) project, the statistical distributions of errors for typical parameters in the modulus backcalculation model were determined. Subsequently, a factor level table for orthogonal experimental design was developed, leading to the construction of 81 orthogonal design experimental schemes and their corresponding theoretical pavement structure models based on the actual error distributions. The deflection responses of 81 theoretical pavement structure models were then computed using an ABAQUS finite element batch analysis method devised in python. Furthermore, a multi-parameter error model for modulus was established using multiple linear regression and variance analysis. Finally, the theoretical limitations of modulus errors under actual errors were analyzed. The results show that the errors of thickness, load amplitude and load frequency follow a normal distribution, while the distribution of backcalculated modulus errors follows an approximate mixed Gaussian distribution. When the errors of multiple parameters are combined randomly, the modulus errors range from -100% to 595%, and the probability of the modulus errors being less than 15% is highest in the asphalt surface layer, followed by the subgrade, and then the base and subbase layers. Within the same error range, the modulus error is random. However, with different error ranges, the overall level of modulus error increases in proportion to the size of those ranges. Compared to factors such as thickness, load amplitude, and load frequency, the errors in deflect

关键词： error in modulus backcalculation distribution characteristics ABAQUS finite element batch analysis python language multi-parameter errors model

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Implementation Analysis of Encryption and Decryption Algorithm Based on python language 22

Implementation Analysis of Encryption and Decryption Algorit...

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Proceedings of the 2022 7th International Conference on Systems, Control and Communications

作者： Kai Xiao Wuhan Railway Vocational College of Technology China

ISBN: (纸本)9781450397247

Facing the Internet information transmission of WAN or LAN, it is difficult to ensure the security and stability of data transmission after key encryption by using traditional one-way password encryption and two-way stream password encryption. Therefore, a hybrid encryption algorithm of RSA, DES and BASE64 developed based on python language is proposed, and the encryption and decryption scheme of information transmission between network client and client, client and server is set up, including the encryption and decryption implementation of digital certificate accuracy, server registration, user login and communication, file transmission, password modification and log processing, etc., to improve the encryption and decryption security level of data file transmission and log processing, and to maximize the protection of network instant messaging Security and stability.

关键词： RSA algorithm Implementation of encryption and decryption DES algorithm python language

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Object-oriented Programming Course Reform Using python language in the Background of Artificial Intelligence

Object-oriented Programming Course Reform Using Python Langu...

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2019 3rd International Conference on Education,Management Science and Economics(ICEMSE 2019)

作者： Yongcheng Wu Computer Engineering School Jingchu University of Technology

Using C++ or Java as the describing language is the traditional way of teaching of object-oriented programming（OOP）. Currently with the rapid development of AI and python programming language, teaching OOP using python become more and more important and suitable. In this paper, firstly the disadvantages of C++ and Java languages as well as the advantages of python for OOP teaching are discussed. Then the main content of OOP teaching using python is put forward, which consists of two parts: the basic part and application part. The basic part should include the basic grammar of python and basic knowledge and skills of OOP. For the application part, we suggest using an AI library Sklearn to practice some practical AI application. A specific instance of K-means clustering case teaching using Sklearn is also discussed in this paper.

关键词： course reform object-oriented programming python language artificial intelligence

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TEACHING METHOD REFORM OF python language PROGRAMMING COURSE BASED ON MINIMUM KNOWLEDGE SETS

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MECHATRONIC SYSTEMS AND CONTROL 2018年第4期46卷 181-186页

作者： Kui, Xiaoyan Liu, Weiguo Guo, Kehua Xia, Jiazhi Du, Huakun Cent S Univ Sch Informat Sci & Engn Changsha Hunan Peoples R China Cent S Univ Sch Geosci & Infophys Changsha Hunan Peoples R China

Reform of teaching content, teaching methods, and evaluation of examination system is an urgent issue of current teaching reform in higher education. python language is released under the background of calculating ecology, which is concise, clear, elegant, and easy to learn. There are more than thousands of third-party programming libraries. Rich resources of an open community also incur new problem, much information will consume large amounts of attention. How to make students absorb more knowledge and master more skills in the limited class time? Also, it is important for teachers to think about how to improve the efficiency of information cognition. The paper puts forward a teaching method of python language based on minimum knowledge sets, combining with the characteristics of different major students;the method can not only help students understand the ideas and methods of solving practical problems with the concept of calculation ecology but also raise good computational thinking, innovative thinking, and programming ability, and then effectively improve the quality of teaching and promote the development of higher education.

关键词： Higher education python language minimum knowledge sets computational thinking

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The construction of online course based on python language in cloud computing environment

The construction of online course based on Python Language i...

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2016 2nd Workshop on Advanced Research and Technology in Industry Applications(WARTIA 2016)

作者： Haiyue Li jianjun Zhang School of Continuing Education Beijing Institute of Technology

Today's society is a decade where new thing and new ideas were *** the suggestion of "Internet +",the education is also gradually catch up with the pace of the times,it thrives in the network-based cloud computing *** on the "Internet +" and the cloud computing environment,the research strives to create a network course based on the cloud computing platforms and python language,so that learners can be self-learning through online courses.

关键词： cloud computing python language Network Course Construction

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Design of Power Transformer Fault Detection of SCADA Alarm Using Fault Tree Analysis, Smooth Holtz-Winters, and L-BFGS for Smart Utility Control Centers

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IEEE ACCESS 2024年 12卷 116302-116324页

作者： Taksana, Radomboon Janjamraj, Natin Romphochai, Sillawat Bhumkittipich, Krischonme Mithulananthan, Nadarajah Rajamangala Univ Technol Thanyaburi Fac Engn Dept Elect Engn Pathum Thani 12110 Thailand Rajamangala Univ Technol Thanyaburi Fac Engn Dept Elect & Telecommun Engn Pathum Thani 12110 Thailand Univ Queensland Sch Informat Technol & Elect Engn Fac Engn Architecture & Informat Technol Brisbane Qld 4072 Australia

When a trip occurs, the utility of company-type 115/22 kV loading transformer trips out of the electrical system, cutting off power to the distribution of a company customer. The outage damage is valuable at 8.5 US/kWh. A 12-step load transfer procedure at the utility control center takes the operator 433 seconds to complete when restoring power to a customer experiencing an outage. Problem number 1 is that many Supervisor Control and Data Acquisition (SCADA) message alarms will appear during the event, which confuses the operator and possibly leads to an incorrect analysis of the trip event details. Problem number 2 occurs in the process where the operator incorrectly predicts the MW-load data of the Loading Transformer will cause a power outage, causing the neighboring loading transformer to overload and cause damage after the operator completes the LTR process. In this study, Pyauto2, an application developed with the python platform that connects to the utility control center's SCADA and runs automatically, is introduced Pyauto2 serves two purposes: to work as an operator to reduce person-hours in the utility company's LTR process and to analyze find accurate answers to trip events of 68 Loading Transformers installed in the electrical system in the central region of Thailand. The last purpose is to use Pyauto2 to reduce the LTR time. Pyauto2 can analyze the SCADA message alarm via fault tree analysis. To help plan the transfer load, it forecasts MW load data on the day of the loading transformer trip using two-time series forecasting techniques. Holt-Winters exponential smoothing (HWS) method is the second technique, and the triple exponential moving average (TEMA) is the first HWS method. In this study, the distorted data are filtered out via the exponential moving average (EMA) technique before being sent to TEMA and HWS for forecasting. The data gathered between 2017 and 2020 revealed distortion in the MW load data, which may be brought on using SCADA equipm

关键词： Fault section diagnosis transformer restoration fault tree analysis exponential moving average Holt-Winters method python language

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The Design of a Wellbeing Center with an Advanced Parametric Roof in Jabel Hafeet Mountain Located in Al Ain City, United Arab Emirates

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BUILDINGS 2024年第4期14卷 974页

作者： Alsuwaidi, Marwa Almahri, Noura Alazeezi, Latifa Alkhzaimi, Taif Bande, Lindita Ahmad, Anwar Al Khatib, Omar Fikry, Fayez Kim, Young Ki United Arab Emirates Univ Coll Engn Architectural Engn Dept POB 15551 Al Ain U Arab Emirates

Building construction in the UAE is a growing industry. While Abu Dhabi and Dubai have a majority of mid-rise and high-rise buildings, AL Ain has mostly low-rise and mid-rise buildings. Additionally, the construction industry in Al Ain has seen an increase in the recent years. The aim of this study is to design a wellness center with a parametric roof in the challenging topography of Jebel Hafeet Mountain in AL Ain. The building must be socially and environmentally sustainable and must align with the local culture. The methodology used includes the following steps: performing an analysis of the selected site and climate;building the design on challenging topography;creating a parametric roof design;conducting an energy and radiation analysis. Wellness is the act of practicing healthy habits to attain better physical and mental health outcomes. The center will be for females only to provide privacy and to achieve social sustainability (based on the local culture). It will be in Al Ain (Jabel Hafeet Mountain) because unlike the other cities in the UAE, Al Ain does not contain any wellness centers. The design of the parametric roof aims to adapt to the mountain and decrease solar radiation on the roof. Both of the above aim to bring innovation to the city, country, and region for the purpose of building a sustainable design that is adapted to the local culture and environment. The results show a significant energy and solar radiation after the use of such structure. These findings are relevant to local authorities and the private construction industry.

关键词： wellbeing center energy simulation parametric structure python language

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Dynamic characteristics analysis of CBGSCC bridge with large parameter samples

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STEEL AND COMPOSITE STRUCTURES 2024年第2期52卷 237-248页

作者： He, Zhongying Song, Yifan Wang, Genhui Sun, Penghui Henan Univ Dept Civil Engn & Architecture Kaifeng 475000 Henan Peoples R China Lanzhou Jiaotong Univ Dept Civil Engn Lanzhou 730000 Gansu Peoples R China

In order to make the dynamic analysis and design of improved composite beam with corrugated steel web (CBGSCC) bridge more efficient and economical, the parametric self-cyclic analysis model (SCAM) was written in python on Anaconda platform. The SCAM can call ABAQUS finite element software to realize automatic modeling and dynamic analysis. For the CBGSCC bridge, parameters were set according to the general value range of CBGSCC bridge parameters in actual engineering, the SCAM was used to calculate the large sample model generated by parameter coupling, the optimal value range of each parameter was determined, and the sensitivity of the parameters was analyzed. The number of diaphragms effects weakly on the dynamic characteristics. The deck thickness has the greatest influence on frequency, which decreases as the deck thickness increases, and the deck thickness should be 20-25 cm. The vibration frequency increases with the increase of the bottom plate thickness, the web thickness, and the web height, the bottom plate thickness should be 17-23mm, the web thickness should be 13-17 mm, and the web height should be 1.65-1.7 5 m. Web inclination and Skew Angle should not exceed 30 degrees, and the number of diaphragms should be 3-5 pieces. This method can be used as a new method for structural dynamic analysis, and the importance degree and optimal value range of each parameter of CBGSCC bridge can be used as a reference in the design process.

关键词： dynamic characteristic large sample parameters python language self-circulated analysis model composite box girder with steel bottom plate-corrugated web-concrete deck bridge dynamic characteristic large sample parameters python language self-circulated analysis model

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Prediction of mechanical properties of elastomeric materials using neural networks

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MATERIALS PHYSICS AND MECHANICS 2023年第5期51卷 66-78页

作者： Fomin, S. V. Rostovtsev, V. S. Meltsov, V. U. Shirokova, E. S. Vyatka State Univ Kirov Russia

The article is devoted to the use of neural networks for predicting the mechanical properties of rubber. Rubbers include, as a rule, more than one and a half dozen components. Each of the components has a complex and ambiguous effect on the complex of material properties. When developing new compositions, this significantly complicates and lengthens the solution of material science problems by traditional methods of composition selection. These problems can be effectively solved using machine learning techniques. The authors have developed approaches to the use of neural networks for predicting the mechanical properties of rubber from a known composition. In this article, neural network models have been created and optimized, which make it possible to predict the mechanical properties of elastomeric materials with high accuracy.

关键词： elastomers rubbers physical and mechanical properties convolutional neural network hyperparameter optimization neural network technologies python language keras library

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