Pub Date : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042879
Peiyu Zhao, Xunlian Si, Zhonghui Dong
The carrying capacity of water resources and the environment has become a restrictive factor in economic development. It is also of great significance to Xi’an City, which is rapidly developing and lacking water. Based on the carrying capacity of water resources and environment, we construct an evaluation index system in four aspects: water resources, water environment, society, and economy. The entropy weight method is used to objectively give weights along with the TOPSIS method and the fuzzy comprehensive evaluation method to evaluate the method for the period from 2006 to 2020. The carrying capacity of water resources and the environment in Xi’an City, and its restrictive factors are explored with the obstacle degree model. In general, from 2006 to 2020, the carrying capacity of water resources and the environment in Xi’an showed a fluctuating upward trend. From the perspective of each subsystem, the comprehensive score of each subsystem showed an upward trend. From the perspective of obstacles, the water resources in Xi’an were restricted. The obstacles to environmental carrying capacity mainly came from water resources and water environment subsystems.
{"title":"Fuzzy Comprehensive Evaluation and Obstacle Factors of Water Resources on TOPSIS for Environment Carrying Capacity in Xi’an","authors":"Peiyu Zhao, Xunlian Si, Zhonghui Dong","doi":"10.1109/ECICE55674.2022.10042879","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042879","url":null,"abstract":"The carrying capacity of water resources and the environment has become a restrictive factor in economic development. It is also of great significance to Xi’an City, which is rapidly developing and lacking water. Based on the carrying capacity of water resources and environment, we construct an evaluation index system in four aspects: water resources, water environment, society, and economy. The entropy weight method is used to objectively give weights along with the TOPSIS method and the fuzzy comprehensive evaluation method to evaluate the method for the period from 2006 to 2020. The carrying capacity of water resources and the environment in Xi’an City, and its restrictive factors are explored with the obstacle degree model. In general, from 2006 to 2020, the carrying capacity of water resources and the environment in Xi’an showed a fluctuating upward trend. From the perspective of each subsystem, the comprehensive score of each subsystem showed an upward trend. From the perspective of obstacles, the water resources in Xi’an were restricted. The obstacles to environmental carrying capacity mainly came from water resources and water environment subsystems.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116806582","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042917
Chuan-Pin Lu, Zheng-Yang Wu
Mushroom growth depends on the microclimate in greenhouses. The environmental control system of greenhouses cannot monitor mushroom growth. Thus, the control of microclimate is not for mushroom growth but for farmers’ feelings or experiences. To develop an intelligent system for monitoring mushroom growth, an artificial intelligence algorithm based on digital image processing was proposed in this study to automatically locate mushrooms and calculate the pileus circle. Compared to the method in the literature, the low-cost image analysis algorithm was used to calculate the pileus circle in the method. The advantage of this method was using low-cost computers or embedded systems which greatly reduces the deployment cost of intelligent image systems and the utilization rate. In the proposed method, the Bayes classifier was used to separate the target from the background to improve the accuracy of the mushroom location. Then, the image preprocessing, Hough transform for circle and self-developed circle-based region matching algorithm were used to locate the mushroom and then determine the mushroom size based on the pileus circle found. In order to verify the effectiveness of the proposed method in terms of the localization accuracy of the mushroom pileus circle, the average accuracy of the proposed method was 87.0%, which was higher than that of the traditional Circle Hough Transform method by 60.7%. Moreover, its localization stability was superior to that of Circle Hough Transform and the average running time of a single image is 2.3 s. Based on the result, the effectiveness of the proposed method meets the practical requirements of mushroom cultivation.
{"title":"Development of Artificial Intelligence Algorithm based on Digital Image Processing for Calculating Growth Rate of Mushrooms","authors":"Chuan-Pin Lu, Zheng-Yang Wu","doi":"10.1109/ECICE55674.2022.10042917","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042917","url":null,"abstract":"Mushroom growth depends on the microclimate in greenhouses. The environmental control system of greenhouses cannot monitor mushroom growth. Thus, the control of microclimate is not for mushroom growth but for farmers’ feelings or experiences. To develop an intelligent system for monitoring mushroom growth, an artificial intelligence algorithm based on digital image processing was proposed in this study to automatically locate mushrooms and calculate the pileus circle. Compared to the method in the literature, the low-cost image analysis algorithm was used to calculate the pileus circle in the method. The advantage of this method was using low-cost computers or embedded systems which greatly reduces the deployment cost of intelligent image systems and the utilization rate. In the proposed method, the Bayes classifier was used to separate the target from the background to improve the accuracy of the mushroom location. Then, the image preprocessing, Hough transform for circle and self-developed circle-based region matching algorithm were used to locate the mushroom and then determine the mushroom size based on the pileus circle found. In order to verify the effectiveness of the proposed method in terms of the localization accuracy of the mushroom pileus circle, the average accuracy of the proposed method was 87.0%, which was higher than that of the traditional Circle Hough Transform method by 60.7%. Moreover, its localization stability was superior to that of Circle Hough Transform and the average running time of a single image is 2.3 s. Based on the result, the effectiveness of the proposed method meets the practical requirements of mushroom cultivation.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117129750","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042849
Maciej Szymkowski, Krzysztof Trusiak, K. Saeed
The widespread of Internet technologies highlights one important issue. The problem is related to security and safety of our data. Traditional logins and passwords are not efficient enough and cannot guarantee expected security level. Motivated by that we present an approach to utilize haptics device (stimuli generator) within biometrics-based security procedure. The combination of these elements is based on generation of divergent stimuli and observation of the human reaction that is measured with different liveliness parameters as heart rate, emotions from the face (valence and arousal) as well as hand movements. Right now, our analysis is rather theoretical as we are still in the process of data collection. Finally, we outline further steps in the research as well as recent conclusions.
{"title":"Haptics-based Biometrics Identity Recognition System","authors":"Maciej Szymkowski, Krzysztof Trusiak, K. Saeed","doi":"10.1109/ECICE55674.2022.10042849","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042849","url":null,"abstract":"The widespread of Internet technologies highlights one important issue. The problem is related to security and safety of our data. Traditional logins and passwords are not efficient enough and cannot guarantee expected security level. Motivated by that we present an approach to utilize haptics device (stimuli generator) within biometrics-based security procedure. The combination of these elements is based on generation of divergent stimuli and observation of the human reaction that is measured with different liveliness parameters as heart rate, emotions from the face (valence and arousal) as well as hand movements. Right now, our analysis is rather theoretical as we are still in the process of data collection. Finally, we outline further steps in the research as well as recent conclusions.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126757515","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042840
Qing-wei Shen
In order to improve the efficiency and accuracy of human resource management by big data technology, support vector machines are used to complete job matching. The element sample for the employee indicator is sparsely represented to obtain the matrix. The sample is binary classification by a support vector machine to judge the matching degree of employees to positions. Finally, the random transformation function is introduced to achieve dynamic recommendations in the big data environment. The experimental results show that the algorithm has high job matching accuracy, high dynamic recommendation efficiency, and batch recommendation.
{"title":"Research on Intelligent Matching Model Between Employees and Positions Based on Python Big Data Analysis","authors":"Qing-wei Shen","doi":"10.1109/ECICE55674.2022.10042840","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042840","url":null,"abstract":"In order to improve the efficiency and accuracy of human resource management by big data technology, support vector machines are used to complete job matching. The element sample for the employee indicator is sparsely represented to obtain the matrix. The sample is binary classification by a support vector machine to judge the matching degree of employees to positions. Finally, the random transformation function is introduced to achieve dynamic recommendations in the big data environment. The experimental results show that the algorithm has high job matching accuracy, high dynamic recommendation efficiency, and batch recommendation.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127744585","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042952
J. Cui, Qili Sun, Junmin Zhang
Nowadays, The SF6 circuit breaker is an indispensable critical protective device in the UHV power transmission network. In order to study the arc characteristics more accurately, a nozzle arc model is established based on mesoscopic lattice Boltzmann method. Based on this model, the arc process of SF6 circuit breaker is simulated. This paper analyzes the temperature change in 50$mu$s before and after zerocrossing current. The high-temperature particles mainly gather at the front end of the static contact, where the risk of thermal breakdown is greater. The distribution of temperature, density, and gas velocity on the arc core shows the cause of this hightemperature region.
{"title":"Simulation Analysis of Current Zero Arc Characteristics in SF6 Circuit-breaker by Lattice Boltzmann Method","authors":"J. Cui, Qili Sun, Junmin Zhang","doi":"10.1109/ECICE55674.2022.10042952","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042952","url":null,"abstract":"Nowadays, The SF6 circuit breaker is an indispensable critical protective device in the UHV power transmission network. In order to study the arc characteristics more accurately, a nozzle arc model is established based on mesoscopic lattice Boltzmann method. Based on this model, the arc process of SF6 circuit breaker is simulated. This paper analyzes the temperature change in 50$mu$s before and after zerocrossing current. The high-temperature particles mainly gather at the front end of the static contact, where the risk of thermal breakdown is greater. The distribution of temperature, density, and gas velocity on the arc core shows the cause of this hightemperature region.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133171798","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042960
Bingdian Yang, Shuo Yan, Jingyi Yao
With the continuous development of the traffic industry, the continuing education of the drivers also urgently needs to be improved under the background of epidemic normalization. In order to improve the manager′s learning status of the online training of employees, we designed a traffic safety education system based on real-time facial recognition. First of all, high-precision face recognition is achieved through a lightweight face recognition network. Head posture is estimated based on the 3D rotation of the face. When the set threshold value is reached, the warning “Please drive carefully” pops up to ensure the learning effect of drivers and help managers avoid the loss and risk of traffic accidents caused by drivers′ weak safety awareness.
{"title":"Research on Intelligent Traffic Safety Education System Based on Facial State Recognition","authors":"Bingdian Yang, Shuo Yan, Jingyi Yao","doi":"10.1109/ECICE55674.2022.10042960","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042960","url":null,"abstract":"With the continuous development of the traffic industry, the continuing education of the drivers also urgently needs to be improved under the background of epidemic normalization. In order to improve the manager′s learning status of the online training of employees, we designed a traffic safety education system based on real-time facial recognition. First of all, high-precision face recognition is achieved through a lightweight face recognition network. Head posture is estimated based on the 3D rotation of the face. When the set threshold value is reached, the warning “Please drive carefully” pops up to ensure the learning effect of drivers and help managers avoid the loss and risk of traffic accidents caused by drivers′ weak safety awareness.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134600127","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042959
Ning Miao, Manni Hou, Xinye Hong, Gang Wang, Xun Peng, Gang Ren
The emergence of the Internet of Vehicles will transform how various road users interact with one another. The safety of road users, such as cyclists, may be enhanced by the real-time traffic data gathered by the on-road sensors and autonomous vehicles. To communicate with vehicles or pedestrians, cyclists still use physical indications like head movements and hand gestures at the moment rather than taking advantage of the Internet of Vehicles and sensors. We outline research that uses multimodel interaction to improve bike traffic safety. To enhance traffic information awareness and increase bike safety, we deploy user interaction with head-mounted displays and wearable haptic displays for cyclists. We propose the detailed system architecture design and traffic event alerts provided by haptic and augmented reality visual interaction in various traffic scenarios. Initial user feedbacks suggest the positive potential to enhance the cyclists′ safety and further improve directions.
{"title":"Enhancing the Cyclist Traffic Safety by Multimodel Interaction Design with Wearable Haptic Devices and Optical See-Through Head-Mounted Displays","authors":"Ning Miao, Manni Hou, Xinye Hong, Gang Wang, Xun Peng, Gang Ren","doi":"10.1109/ECICE55674.2022.10042959","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042959","url":null,"abstract":"The emergence of the Internet of Vehicles will transform how various road users interact with one another. The safety of road users, such as cyclists, may be enhanced by the real-time traffic data gathered by the on-road sensors and autonomous vehicles. To communicate with vehicles or pedestrians, cyclists still use physical indications like head movements and hand gestures at the moment rather than taking advantage of the Internet of Vehicles and sensors. We outline research that uses multimodel interaction to improve bike traffic safety. To enhance traffic information awareness and increase bike safety, we deploy user interaction with head-mounted displays and wearable haptic displays for cyclists. We propose the detailed system architecture design and traffic event alerts provided by haptic and augmented reality visual interaction in various traffic scenarios. Initial user feedbacks suggest the positive potential to enhance the cyclists′ safety and further improve directions.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132125069","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042939
Yoonjeong Choi, Yujin Lim
As vehicles are connected to the Internet, various services such as infotainment and automated driving can be provided. However, these services require a large amount of data download. When downloading content which has the large size, the content delivery latency can become too long to meet the constraints. To solve this problem, methods for caching the content close to the vehicles are being studied. Macro base station (MBS) and road side unit (RSU) provide storage spaces at a close distance from the vehicles and they can reduce the time required to deliver the requested content. In this paper, we propose a caching strategy in RSUs, aiming to maximize the amount of content delivered from RSUsin order to reduce the delivery latency. Besides, since RSUs are densely deployed in urban areas, RSUs can cache more content by reducing duplicate content among them. Deep deterministic policy gradient (DDPG) is adopted to decide how to cache content in RSUs. Experiments show that the proposed method not only maximizes the amount of content downloaded from RSUs, but also decreases the update cost.
{"title":"Edge Caching Based on Deep Reinforcement Learning in Vehicular Networks","authors":"Yoonjeong Choi, Yujin Lim","doi":"10.1109/ECICE55674.2022.10042939","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042939","url":null,"abstract":"As vehicles are connected to the Internet, various services such as infotainment and automated driving can be provided. However, these services require a large amount of data download. When downloading content which has the large size, the content delivery latency can become too long to meet the constraints. To solve this problem, methods for caching the content close to the vehicles are being studied. Macro base station (MBS) and road side unit (RSU) provide storage spaces at a close distance from the vehicles and they can reduce the time required to deliver the requested content. In this paper, we propose a caching strategy in RSUs, aiming to maximize the amount of content delivered from RSUsin order to reduce the delivery latency. Besides, since RSUs are densely deployed in urban areas, RSUs can cache more content by reducing duplicate content among them. Deep deterministic policy gradient (DDPG) is adopted to decide how to cache content in RSUs. Experiments show that the proposed method not only maximizes the amount of content downloaded from RSUs, but also decreases the update cost.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122318666","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042813
Haijun Yuan, Haoxin Zhai
The sharing of meteorological message transmission of information in satellite communication was researched. It was found that the meteorological message information collected by satellite communication equipment was 100 characters, while the transmission capacity was 158 characters. The content of the information sent by each meteorological observation station was at most one and a half of meteorological message information. Each observation station received all the information sent by other stations and the relationship expression between the number of stations. Thus, the minimum propagation time was obtained, and the corresponding information transmission aggregation model was established. According to the transmission of the specified station, the rules were found, and the information of other stations received by each station in each round was obtained. The transmission scheme of the meteorological message of the master station was as follows. The first round adopted closedloop sequential transmission, that is $2rightarrow 1,3 rightarrow 2,ldots, 1rightarrow$ n, while from the second round, each round adopted the mode of transmission from the i+2 station to the i station ($i leq n-2$). The mode 1$rightarrow$n-1,2$rightarrow$n was adopted by the first and second stations. Based on the result, a transmission model is established to find out the rule of station information sharing at a certain time. Finally, the number of stations N=9 was used to verify the feasibility of the propagation model.
{"title":"Time Optimization Propagation Model of Meteorological Message Propagation and Information in Satellite Communication","authors":"Haijun Yuan, Haoxin Zhai","doi":"10.1109/ECICE55674.2022.10042813","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042813","url":null,"abstract":"The sharing of meteorological message transmission of information in satellite communication was researched. It was found that the meteorological message information collected by satellite communication equipment was 100 characters, while the transmission capacity was 158 characters. The content of the information sent by each meteorological observation station was at most one and a half of meteorological message information. Each observation station received all the information sent by other stations and the relationship expression between the number of stations. Thus, the minimum propagation time was obtained, and the corresponding information transmission aggregation model was established. According to the transmission of the specified station, the rules were found, and the information of other stations received by each station in each round was obtained. The transmission scheme of the meteorological message of the master station was as follows. The first round adopted closedloop sequential transmission, that is $2rightarrow 1,3 rightarrow 2,ldots, 1rightarrow$ n, while from the second round, each round adopted the mode of transmission from the i+2 station to the i station ($i leq n-2$). The mode 1$rightarrow$n-1,2$rightarrow$n was adopted by the first and second stations. Based on the result, a transmission model is established to find out the rule of station information sharing at a certain time. Finally, the number of stations N=9 was used to verify the feasibility of the propagation model.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123725776","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 : 2022-10-28DOI: 10.1109/ECICE55674.2022.10042920
Jingxian Ma
Based on the analysis and evaluation of the effectiveness of postgraduate English learning, an intelligent evaluation model is proposed. This model applies the PSO algorithm to the achievement analysis system of graduate students. This algorithm analyzes student achievement data in the educational administration system to find out the internal relationship between courses. Based on the result, the educational administration staff can arrange teaching work scientifically. The results show that the method has the best effect on the evaluation of postgraduate English teaching with an average evaluation accuracy of 90%, a short evaluation time, and a test time shorter than 10 ms. This model improves the accuracy and efficiency of the evaluation of postgraduate English teaching and meets the requirements of teaching.
{"title":"Intelligent Evaluation Model for Postgraduate English Teaching Effectiveness Based on PSO Algorithm","authors":"Jingxian Ma","doi":"10.1109/ECICE55674.2022.10042920","DOIUrl":"https://doi.org/10.1109/ECICE55674.2022.10042920","url":null,"abstract":"Based on the analysis and evaluation of the effectiveness of postgraduate English learning, an intelligent evaluation model is proposed. This model applies the PSO algorithm to the achievement analysis system of graduate students. This algorithm analyzes student achievement data in the educational administration system to find out the internal relationship between courses. Based on the result, the educational administration staff can arrange teaching work scientifically. The results show that the method has the best effect on the evaluation of postgraduate English teaching with an average evaluation accuracy of 90%, a short evaluation time, and a test time shorter than 10 ms. This model improves the accuracy and efficiency of the evaluation of postgraduate English teaching and meets the requirements of teaching.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127866565","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：