O. Fedusenko, Natalia Shkurpela, Iryna Domanetska, Anatoliy Fedusenko
The are crop planning problems exist in a modern agriculture of Ukraine. With the help of the intelligent support system for agro-technological decisions proposed by the authors, it is possible to simplify the planning process by using the concept of precision farming. Modern fields monitoring methods were analyzed and methods that will be used in the intelligent system are identified. The k-means method is one of them and will be applied to field clustering. The authors analyzed modern research and publications related to the concept of precision farming and the problem of implementing modern innovative information systems in agriculture of Ukraine. The decomposition of the intelligent system was carried out. Six main subsystems were identified, functional requirements were developed for each of them. Modern methods of fields monitoring are analyzed and methods that will be used in the intelligent system are identified, one of which is the k-means method, which will be applied to field clustering. Based on the already developed requirements, the authors have developed the general architecture of the system. The notation TOGAF was applied for the graphical display of the architecture. Based on the proposed architecture, intelligent system software was created. As a result of testing the soft-ware of the intelligent system, it is possible to draw a conclusion about its efficiency and readiness for implementation. The designed and developed system allows to carry out intellectual analysis of historical data of crops, to display results in the form of tables and graphs, to carry out planning of crops, agrotechnological operations and fertilizer application. The introduction of this system will improve the quality of management decisions and productivity of agricultural activities.
{"title":"Intelligent support system for agro-technological decisions for sowing fields","authors":"O. Fedusenko, Natalia Shkurpela, Iryna Domanetska, Anatoliy Fedusenko","doi":"10.17721/ait.2021.1.02","DOIUrl":"https://doi.org/10.17721/ait.2021.1.02","url":null,"abstract":"The are crop planning problems exist in a modern agriculture of Ukraine. With the help of the intelligent support system for agro-technological decisions proposed by the authors, it is possible to simplify the planning process by using the concept of precision farming. Modern fields monitoring methods were analyzed and methods that will be used in the intelligent system are identified. The k-means method is one of them and will be applied to field clustering. The authors analyzed modern research and publications related to the concept of precision farming and the problem of implementing modern innovative information systems in agriculture of Ukraine. The decomposition of the intelligent system was carried out. Six main subsystems were identified, functional requirements were developed for each of them. Modern methods of fields monitoring are analyzed and methods that will be used in the intelligent system are identified, one of which is the k-means method, which will be applied to field clustering. Based on the already developed requirements, the authors have developed the general architecture of the system. The notation TOGAF was applied for the graphical display of the architecture. Based on the proposed architecture, intelligent system software was created. As a result of testing the soft-ware of the intelligent system, it is possible to draw a conclusion about its efficiency and readiness for implementation. The designed and developed system allows to carry out intellectual analysis of historical data of crops, to display results in the form of tables and graphs, to carry out planning of crops, agrotechnological operations and fertilizer application. The introduction of this system will improve the quality of management decisions and productivity of agricultural activities.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"111 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81089890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577626
Shunfang Liu, W. Shen, Hongbo Cai, J. Wei, Cao Li
The software management of the process has played an important role during the software development of the Lunar based Ultraviolet Telescope. Full requirement analysis, practical management plan, clear division of development stage, stage of software life cycle model selection, effective configuration management control, which is an unprecedented management method suitable for the development of optical load software. The final operation results of the lunar based optical telescope show that the method is applicable and effective, and provides reference and reference for China's space load software management.
{"title":"A Software Managemente Method for the LUT","authors":"Shunfang Liu, W. Shen, Hongbo Cai, J. Wei, Cao Li","doi":"10.1109/IAEAC.2018.8577626","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577626","url":null,"abstract":"The software management of the process has played an important role during the software development of the Lunar based Ultraviolet Telescope. Full requirement analysis, practical management plan, clear division of development stage, stage of software life cycle model selection, effective configuration management control, which is an unprecedented management method suitable for the development of optical load software. The final operation results of the lunar based optical telescope show that the method is applicable and effective, and provides reference and reference for China's space load software management.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"69 1","pages":"1624-1628"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75650398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577268
Shangyi Xiaol, Li Tong, Ningning Liang, Jun Shu, Bin Yan, Ying Zeng
Target detection technique based on event-related potential (ERP) has become a new method to solve the problems of small target detection with complex background in remote-sensing images. Multiple ERP components reflect different stages of the visual information processing, previous studies usually used features of single ERP component to detecting targets. In this paper, a target detection model was built based on multiple ERP components evoked in rapid serial visual presentation (RSVP) of remote-sensing images. Experimental results showed that combing the spatiotemporal features of multiple ERP components could improve the detection accuracy, where the mean AUC could reach 89%.
{"title":"Target Detection for Remote Sensing Image Based on Multiple ERP Components","authors":"Shangyi Xiaol, Li Tong, Ningning Liang, Jun Shu, Bin Yan, Ying Zeng","doi":"10.1109/IAEAC.2018.8577268","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577268","url":null,"abstract":"Target detection technique based on event-related potential (ERP) has become a new method to solve the problems of small target detection with complex background in remote-sensing images. Multiple ERP components reflect different stages of the visual information processing, previous studies usually used features of single ERP component to detecting targets. In this paper, a target detection model was built based on multiple ERP components evoked in rapid serial visual presentation (RSVP) of remote-sensing images. Experimental results showed that combing the spatiotemporal features of multiple ERP components could improve the detection accuracy, where the mean AUC could reach 89%.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"123 1","pages":"1199-1202"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75808327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577890
Wei Na, Li Mingyong
The cooperative problem of multi-agent robots is discussed in this paper. The methods of solving robot role assignments can be classified as static roles, dynamic roles and combination of static and dynamic roles. The combination of static and dynamic roles assignment is adapted in this paper. An optimal objective function model of the soccer robots competition is established to complete the role transformation of the robot. The coordinated problem of multi-agent robots is solved by cooperative game algorithm. The simulation results show that the proposed model is correct and effective.
{"title":"Cooperative Game for the Roles Assignment of the Multi-agent Robot System","authors":"Wei Na, Li Mingyong","doi":"10.1109/IAEAC.2018.8577890","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577890","url":null,"abstract":"The cooperative problem of multi-agent robots is discussed in this paper. The methods of solving robot role assignments can be classified as static roles, dynamic roles and combination of static and dynamic roles. The combination of static and dynamic roles assignment is adapted in this paper. An optimal objective function model of the soccer robots competition is established to complete the role transformation of the robot. The coordinated problem of multi-agent robots is solved by cooperative game algorithm. The simulation results show that the proposed model is correct and effective.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"382 1","pages":"954-957"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75524525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577474
Haiting Cui
In order to improve detection rate and reduce missing detection rate and false detection rate of big data, an abnormal large data elimination method based on PSO-SVM is proposed. Big data is chosen as a set, proximity of which is measured, according to fuzzy sets in fuzzy theory to measure data’ similarity degree. In order to determine redundant data and judge whether big data is abnormal, using support vector machine to train each particle and get fitness function through measuring the proximity between data by a constructed function, and then eliminating abnormal big data through the sliding window. Taking KDD99 big data as object, simulation experiment has higher detection rate and low false detection rate based on PSO-SVM method.
{"title":"Research on Eliminating Abnormal Big Data based on PSO-SVM","authors":"Haiting Cui","doi":"10.1109/IAEAC.2018.8577474","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577474","url":null,"abstract":"In order to improve detection rate and reduce missing detection rate and false detection rate of big data, an abnormal large data elimination method based on PSO-SVM is proposed. Big data is chosen as a set, proximity of which is measured, according to fuzzy sets in fuzzy theory to measure data’ similarity degree. In order to determine redundant data and judge whether big data is abnormal, using support vector machine to train each particle and get fitness function through measuring the proximity between data by a constructed function, and then eliminating abnormal big data through the sliding window. Taking KDD99 big data as object, simulation experiment has higher detection rate and low false detection rate based on PSO-SVM method.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"17 10","pages":"2460-2463"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72595473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577843
Zhicheng Zhao, Yaqun Zhao
FFTW and CUFFT are used as typical FFT computing libraries based on CPU and GPU respectively. This paper tests and analyzes the performance and total consumption time of machine floating-point operation accelerated by CPU and GPU algorithm under the same data volume. The results show that CUFFT based on GPU has a better comprehensive performance than FFTW.
{"title":"The Optimization of FFT Algorithm Based with Parallel Computing on GPU","authors":"Zhicheng Zhao, Yaqun Zhao","doi":"10.1109/IAEAC.2018.8577843","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577843","url":null,"abstract":"FFTW and CUFFT are used as typical FFT computing libraries based on CPU and GPU respectively. This paper tests and analyzes the performance and total consumption time of machine floating-point operation accelerated by CPU and GPU algorithm under the same data volume. The results show that CUFFT based on GPU has a better comprehensive performance than FFTW.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"145 1","pages":"2003-2007"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74776865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577706
Tao Li, Xinyu Huang, Ming Luo
In order to optimize plunge process parameters and analyze the relationship between milling parameters and force coefficient under the same processing conditions, a test is designed in this paper to explore the correlation between milling force coefficient and milling speed based on the existing model of milling force and the specific milling conditions. Three-way milling force in this paper are measured under the same cutting condition and different feeding rate when milling three different step holes. Through identify the shear force coefficient and edge force coefficient, this paper explores the correlation between the milling force and milling speed, feed rate and milling depth according to the Pearson correlation. In this paper, an experimental and simulation example of plunge milling aluminum alloy material is given.
{"title":"Analysis on the Correlation between Plunge Milling Parameters and Plunge Milling Force and Force Coefficient","authors":"Tao Li, Xinyu Huang, Ming Luo","doi":"10.1109/IAEAC.2018.8577706","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577706","url":null,"abstract":"In order to optimize plunge process parameters and analyze the relationship between milling parameters and force coefficient under the same processing conditions, a test is designed in this paper to explore the correlation between milling force coefficient and milling speed based on the existing model of milling force and the specific milling conditions. Three-way milling force in this paper are measured under the same cutting condition and different feeding rate when milling three different step holes. Through identify the shear force coefficient and edge force coefficient, this paper explores the correlation between the milling force and milling speed, feed rate and milling depth according to the Pearson correlation. In this paper, an experimental and simulation example of plunge milling aluminum alloy material is given.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"72 1","pages":"927-936"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78193250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we study inspection business model based on the distribution network, and spatial data model and the network automatic generating technique, which use GIS and satellite positioning. Furthermore, we study inspection automatic control method based on speech synthesis technology in order to control the inspection process effectively and ensure the inspection efficiency.
{"title":"Distribution Network Inspection Route Planning and the Application of Inspection Automatic Control Technique","authors":"Shangwei Yang, Haipeng Wang, Zhigang Ren, Shi-you Mu, Jianxiang Li, Jinlong Zhao","doi":"10.1109/IAEAC.2018.8577838","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577838","url":null,"abstract":"In this paper, we study inspection business model based on the distribution network, and spatial data model and the network automatic generating technique, which use GIS and satellite positioning. Furthermore, we study inspection automatic control method based on speech synthesis technology in order to control the inspection process effectively and ensure the inspection efficiency.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"42 1 1","pages":"1312-1315"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75954594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577930
Pengfei Fan, Liang Deng, Lei Su
This work demonstrates a computational method for predicting the light propagation through a single multimode fiber using a deep neural network. The experiment for gathering training and testing data is performed with a digital micro-mirror device that enables the spatial light modulation. The modulated patterns on the device and the captured intensity-only images by the camera form the aligned data pairs. This sufficiently-trained deep neural network frame has very excellent performance for directly inferring the intensity-only output delivered though a multimode fiber. The model is validated by three standards: the mean squared error (MSE), the correlation coefficient (corr) and the structural similarity index (SSIM).
{"title":"Light Propagation Prediction through Multimode Optical Fibers with a Deep Neural Network","authors":"Pengfei Fan, Liang Deng, Lei Su","doi":"10.1109/IAEAC.2018.8577930","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577930","url":null,"abstract":"This work demonstrates a computational method for predicting the light propagation through a single multimode fiber using a deep neural network. The experiment for gathering training and testing data is performed with a digital micro-mirror device that enables the spatial light modulation. The modulated patterns on the device and the captured intensity-only images by the camera form the aligned data pairs. This sufficiently-trained deep neural network frame has very excellent performance for directly inferring the intensity-only output delivered though a multimode fiber. The model is validated by three standards: the mean squared error (MSE), the correlation coefficient (corr) and the structural similarity index (SSIM).","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"36 1","pages":"1080-1084"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80059528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/IAEAC.2018.8577646
Janxin Zhou, X. Yao, Ning Zhou
In the production process of the test section, the power battery needs to pass through two room temperature standing and two parameters measurement. In this process, it needs to be handled by RGV (Rail-guided vehicle) many times. Combined with the scene of a power battery manufacturer's production line, this paper aims to minimize the task time and establish a model. Through further analysis, the complex production scheduling problem is transformed into a classical TSP problem, and the genetic algorithm is used to solve the problem. Experimental results show that the algorithm can effectively improve the operating efficiency of RGV.
{"title":"Solving Power Battery Scheduling Problem Based on TSP","authors":"Janxin Zhou, X. Yao, Ning Zhou","doi":"10.1109/IAEAC.2018.8577646","DOIUrl":"https://doi.org/10.1109/IAEAC.2018.8577646","url":null,"abstract":"In the production process of the test section, the power battery needs to pass through two room temperature standing and two parameters measurement. In this process, it needs to be handled by RGV (Rail-guided vehicle) many times. Combined with the scene of a power battery manufacturer's production line, this paper aims to minimize the task time and establish a model. Through further analysis, the complex production scheduling problem is transformed into a classical TSP problem, and the genetic algorithm is used to solve the problem. Experimental results show that the algorithm can effectively improve the operating efficiency of RGV.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"48 1","pages":"859-862"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80258442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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