Pub Date : 2022-02-01DOI: 10.1109/ICTech55460.2022.00025
Zhilu Wang, Yunfeng Ding, Tianwu Zhang
With the booming development of economy and technology, China's electric industry has gradually realized intelligent, has developed into a comprehensive network including computer network, power network, information network. The current power information monitoring technology is mainly aimed at the power generation, transmission and transformation stage, and the lack of effective power information detection means in the power distribution stage. Therefore, a distribution network anomaly detection algorithm based on variational auto-encoder is proposed to solve the problem of anomaly detection of distribution terminal data. The input time series power load data is compressed and reconstructed, and the anomaly degree of samples is detected by reconstruction error. Experimental results show that the proposed algorithm has high detection rate and accuracy, as well as high robustness.
{"title":"Distribution Network Anomaly Detection Algorithm Based on VAE","authors":"Zhilu Wang, Yunfeng Ding, Tianwu Zhang","doi":"10.1109/ICTech55460.2022.00025","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00025","url":null,"abstract":"With the booming development of economy and technology, China's electric industry has gradually realized intelligent, has developed into a comprehensive network including computer network, power network, information network. The current power information monitoring technology is mainly aimed at the power generation, transmission and transformation stage, and the lack of effective power information detection means in the power distribution stage. Therefore, a distribution network anomaly detection algorithm based on variational auto-encoder is proposed to solve the problem of anomaly detection of distribution terminal data. The input time series power load data is compressed and reconstructed, and the anomaly degree of samples is detected by reconstruction error. Experimental results show that the proposed algorithm has high detection rate and accuracy, as well as high robustness.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125493369","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00058
Hao Yuan, Xiangru Meng, Linlin Zhang, ChunWen Liu
It has become a trend to obtain news information through network media, but everyone has different tendencies. People are more willing to browse the news they are interested in, so news recommendation becomes very important. The recommendation algorithm can screen out the news that the user is interested in from the massive information, so as to alleviate the problem of information overload in the era of big data. Deep learning model, this paper used to mining the characteristics of the users and news, to learn and build the model, the traditional recommendation algorithm of sparse matrix and the disadvantage of cold start, the experimental results show that this model adopted by the run on Adressa 1G data set is good, at the same time, accuracy and recall rate compared with the traditional collaborative filtering algorithm is improved, so this recommendation works well.
{"title":"A News Recommendation Algorithm Based on Deep Learning","authors":"Hao Yuan, Xiangru Meng, Linlin Zhang, ChunWen Liu","doi":"10.1109/ICTech55460.2022.00058","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00058","url":null,"abstract":"It has become a trend to obtain news information through network media, but everyone has different tendencies. People are more willing to browse the news they are interested in, so news recommendation becomes very important. The recommendation algorithm can screen out the news that the user is interested in from the massive information, so as to alleviate the problem of information overload in the era of big data. Deep learning model, this paper used to mining the characteristics of the users and news, to learn and build the model, the traditional recommendation algorithm of sparse matrix and the disadvantage of cold start, the experimental results show that this model adopted by the run on Adressa 1G data set is good, at the same time, accuracy and recall rate compared with the traditional collaborative filtering algorithm is improved, so this recommendation works well.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127954411","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00078
Anying Chai, Yue Ma, Zhenyu Yin, Zhiyun He, Zhiying Bi
In recent years, intelligent manufacturing has developed rapidly. Industrial IoT technologies are applied to different industrial scenarios. OPC UA is a service-oriented architecture, which has good interoperability. At the same time, it is a cross-platform communication standard that can realize the interconnection between heterogeneous network devices and solve the problem of information silos in the industrial IoT field. However, with the gradual increase of industrial equipment, the amount of data transmission in the network is increasing. The traditional OPC UA communication method based on client/server mode has defects such as tight coupling and performance bottleneck. It cannot meet the high throughput demand of the network. Therefore, these phenomena lead to longer time delays and lower transmission efficiency of network communication systems. To solve the above problems, this paper proposes a publish/subscribe communication model based on OPC UA. We design the overall architecture of the OPC UA publish/subscribe model and adopt a message agent mechanism to realize distributed communication of OPC UA. This model has functions such as message modeling, address space construction, and publish/subscribe. The architecture of this communication model is compatible with the C/S model, which can ensure compatibility and coexistence with the traditional OPC UA communication system. Meanwhile, in order to improve the distinguished service capability of the OPC UA system, a multi-priority data scheduling algorithm is proposed and integrated into the publish/subscribe communication model to improve the efficiency of real-time data transmission in industrial networks. The experimental results show that the communication model can accomplish distributed communication in industrial networks and be better applied in wireless sensor networks. The scheduling algorithm included in the model significantly improves the efficiency of real-time data transmission and reduces the time delay.
{"title":"Research and Implementation of Publish/Subscribe Communication Model Based on OPC UA","authors":"Anying Chai, Yue Ma, Zhenyu Yin, Zhiyun He, Zhiying Bi","doi":"10.1109/ICTech55460.2022.00078","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00078","url":null,"abstract":"In recent years, intelligent manufacturing has developed rapidly. Industrial IoT technologies are applied to different industrial scenarios. OPC UA is a service-oriented architecture, which has good interoperability. At the same time, it is a cross-platform communication standard that can realize the interconnection between heterogeneous network devices and solve the problem of information silos in the industrial IoT field. However, with the gradual increase of industrial equipment, the amount of data transmission in the network is increasing. The traditional OPC UA communication method based on client/server mode has defects such as tight coupling and performance bottleneck. It cannot meet the high throughput demand of the network. Therefore, these phenomena lead to longer time delays and lower transmission efficiency of network communication systems. To solve the above problems, this paper proposes a publish/subscribe communication model based on OPC UA. We design the overall architecture of the OPC UA publish/subscribe model and adopt a message agent mechanism to realize distributed communication of OPC UA. This model has functions such as message modeling, address space construction, and publish/subscribe. The architecture of this communication model is compatible with the C/S model, which can ensure compatibility and coexistence with the traditional OPC UA communication system. Meanwhile, in order to improve the distinguished service capability of the OPC UA system, a multi-priority data scheduling algorithm is proposed and integrated into the publish/subscribe communication model to improve the efficiency of real-time data transmission in industrial networks. The experimental results show that the communication model can accomplish distributed communication in industrial networks and be better applied in wireless sensor networks. The scheduling algorithm included in the model significantly improves the efficiency of real-time data transmission and reduces the time delay.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131796549","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00052
Zekai Sun, Xiangru Meng, PiChao Zheng, Xiangning Zhu, Lei Yang
It takes a lot of time and energy for users to obtain useful information from the massive data generated by the Internet. The text abstract is a refined expression of the content of the article, which can summarize the main content of the article. Text summarization technology can quickly allow users to obtain information that is valuable to them, and to a certain extent alleviate the problem of information overload in the era of big data. In this paper, we use the knowledge enhancement model to learn the semantic relationship of the real world by modeling the entity concept and other prior semantic knowledge in massive data, so as to overcome the disadvantage of using only the original language signal in the previous language model. Then the generative pre-training model is used to solve some specific problems in natural language generation, such as the exposure bias problem. The experimental results show that the model used in this paper works well on the Gigaword and CNN / DailyMail data sets. At the same time, the abstract generated on the nlpcc2017 Chinese abstract data has good accuracy and readability.
{"title":"Research and Application of Automatic Text Summarization Technology Based on Deep Learning","authors":"Zekai Sun, Xiangru Meng, PiChao Zheng, Xiangning Zhu, Lei Yang","doi":"10.1109/ICTech55460.2022.00052","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00052","url":null,"abstract":"It takes a lot of time and energy for users to obtain useful information from the massive data generated by the Internet. The text abstract is a refined expression of the content of the article, which can summarize the main content of the article. Text summarization technology can quickly allow users to obtain information that is valuable to them, and to a certain extent alleviate the problem of information overload in the era of big data. In this paper, we use the knowledge enhancement model to learn the semantic relationship of the real world by modeling the entity concept and other prior semantic knowledge in massive data, so as to overcome the disadvantage of using only the original language signal in the previous language model. Then the generative pre-training model is used to solve some specific problems in natural language generation, such as the exposure bias problem. The experimental results show that the model used in this paper works well on the Gigaword and CNN / DailyMail data sets. At the same time, the abstract generated on the nlpcc2017 Chinese abstract data has good accuracy and readability.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132980509","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00079
Le He
The sudden outbreak of COVID-19 has greatly affected the development of all industries, and the development of many enterprises has been severely impacted. In the context of epidemic prevention and control, the Internet has brought new development space for enterprise marketing, so more and more enterprises begin to enter the field of online marketing. With the continuous progress of Internet technology and the deepening of informatization, China's big data industry has made qualitative progress. The traditional marketing model cannot meet the needs of the increasingly fierce market competition. By applying big data technology to network marketing, enterprises can dig deeply into user information and formulate corresponding marketing strategies based on users' preferences, behavior patterns and shopping habits, so as to realize precise marketing and improve their economic benefits by mining potential customers. However, there are also some problems in the process of using big data technology to move towards precision, such as serious homogenization, low application level, and privacy security issues. Only by solving these problems can enterprises use big data to achieve higher quality development.
{"title":"Problems and strategies in the process of network marketing towards precision in the context of big data","authors":"Le He","doi":"10.1109/ICTech55460.2022.00079","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00079","url":null,"abstract":"The sudden outbreak of COVID-19 has greatly affected the development of all industries, and the development of many enterprises has been severely impacted. In the context of epidemic prevention and control, the Internet has brought new development space for enterprise marketing, so more and more enterprises begin to enter the field of online marketing. With the continuous progress of Internet technology and the deepening of informatization, China's big data industry has made qualitative progress. The traditional marketing model cannot meet the needs of the increasingly fierce market competition. By applying big data technology to network marketing, enterprises can dig deeply into user information and formulate corresponding marketing strategies based on users' preferences, behavior patterns and shopping habits, so as to realize precise marketing and improve their economic benefits by mining potential customers. However, there are also some problems in the process of using big data technology to move towards precision, such as serious homogenization, low application level, and privacy security issues. Only by solving these problems can enterprises use big data to achieve higher quality development.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131047161","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00073
Lei Shu
The existing sensitive information encryption and decryption system has the problem of imperfect encryption and decryption model, which leads to a long node request time. A sensitive information encryption and decryption system based on branch obfuscation algorithm is designed. Hardware part: using ultra-long instruction set multimedia application chip, reading data by PC, and expanding the width of external memory interface; Software: obtain the characteristics of sensitive information network, disrupt the information ranking and then encrypt, construct encryption and decryption model of confidential communication, transmit data through public channels, extract encryption and decryption identification of sensitive information, and design the storage and control function of system software with branch obfuscation algorithm. Experimental results: The average node request time of the sensitive information encryption and decryption system in this paper and the other three encryption systems are 99.477ms, 133.145ms, 135.611ms, 135.941ms respectively, indicating that the sensitive information encryption and decryption system integrated with branch obfuscation algorithm has higher application value.
{"title":"Design of Sensitive Information Encryption and Decryption System Based on Branch Obfuscation Algorithm","authors":"Lei Shu","doi":"10.1109/ICTech55460.2022.00073","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00073","url":null,"abstract":"The existing sensitive information encryption and decryption system has the problem of imperfect encryption and decryption model, which leads to a long node request time. A sensitive information encryption and decryption system based on branch obfuscation algorithm is designed. Hardware part: using ultra-long instruction set multimedia application chip, reading data by PC, and expanding the width of external memory interface; Software: obtain the characteristics of sensitive information network, disrupt the information ranking and then encrypt, construct encryption and decryption model of confidential communication, transmit data through public channels, extract encryption and decryption identification of sensitive information, and design the storage and control function of system software with branch obfuscation algorithm. Experimental results: The average node request time of the sensitive information encryption and decryption system in this paper and the other three encryption systems are 99.477ms, 133.145ms, 135.611ms, 135.941ms respectively, indicating that the sensitive information encryption and decryption system integrated with branch obfuscation algorithm has higher application value.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132437576","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00084
Hao Wang, Xiwang Li
This study aims to use the support vector regression (SVR) theory, according to the nonlinear characteristics of iron ore price series fluctuation, based on the 5000 daily transaction data of iron ore in Dalian Commodity Exchange as the research object, the Adaboost -SVR iron ore price prediction model optimized by the novel BAT algorithm (NBA) is established. The model takes the maximum, minimum, closing price and trading volume of the daily transaction data as input parameters and the closing price of the next trading day as output parameters. The prediction results of the research model are compared and analyzed. The results show that the prediction value of the research model is closer to the real value, and the mean relative error (MRE) and root mean square error (RMSE) of the research model are 0.006 and 20.19, respectively, which are better than the prediction results of the traditional support vector regression model. The research model provides technical support and decision-making basis for the market monitoring and early warning of iron ore, and has advantages in accuracy compared with traditional forecasting methods.
{"title":"Research on Iron Ore Price Prediction Based on AdaBoost-SVR","authors":"Hao Wang, Xiwang Li","doi":"10.1109/ICTech55460.2022.00084","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00084","url":null,"abstract":"This study aims to use the support vector regression (SVR) theory, according to the nonlinear characteristics of iron ore price series fluctuation, based on the 5000 daily transaction data of iron ore in Dalian Commodity Exchange as the research object, the Adaboost -SVR iron ore price prediction model optimized by the novel BAT algorithm (NBA) is established. The model takes the maximum, minimum, closing price and trading volume of the daily transaction data as input parameters and the closing price of the next trading day as output parameters. The prediction results of the research model are compared and analyzed. The results show that the prediction value of the research model is closer to the real value, and the mean relative error (MRE) and root mean square error (RMSE) of the research model are 0.006 and 20.19, respectively, which are better than the prediction results of the traditional support vector regression model. The research model provides technical support and decision-making basis for the market monitoring and early warning of iron ore, and has advantages in accuracy compared with traditional forecasting methods.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115411107","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00095
Chao Fu, R. Guo, Dan Yang, Hongliang Wang, Xiaoxing Zhang
Segmentation and 3D visualization of carotid vessels is an important part of the treatment of carotid stenosis conditions. In this paper, we propose a novel method for automatic 3D reconstruction of carotid vessels by combining the region growing algorithm and the marching cubes algorithm. The automatic segmentation and 3D reconstruction of carotid vessels can be achieved by only manually and interactively selecting a point in the target vessel in human CTA images. The experiments demonstrate that this method has good practicality, can reduce a large amount of manual intervention, and has the advantage of saving time and effort.
{"title":"Automatic 3D Reconstruction of Carotid Vessels Based on Region Growing Method","authors":"Chao Fu, R. Guo, Dan Yang, Hongliang Wang, Xiaoxing Zhang","doi":"10.1109/ICTech55460.2022.00095","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00095","url":null,"abstract":"Segmentation and 3D visualization of carotid vessels is an important part of the treatment of carotid stenosis conditions. In this paper, we propose a novel method for automatic 3D reconstruction of carotid vessels by combining the region growing algorithm and the marching cubes algorithm. The automatic segmentation and 3D reconstruction of carotid vessels can be achieved by only manually and interactively selecting a point in the target vessel in human CTA images. The experiments demonstrate that this method has good practicality, can reduce a large amount of manual intervention, and has the advantage of saving time and effort.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116179547","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00022
Ruimei Gao
Public laboratory as the basis of scientific research project activities in order to guarantee, during the practice operation need to reserve a large amount of data information, so under the background of new era in order to better implement diversified experimental activities, to ensure that the relevant data information is scientific reserves, must be combined with CS of optimization and improvement of the structure of information system. In this paper, on the basis of understanding the content of CS structure, according to the operational requirements of the practical system in the development of the relevant system at the same time to carry out experimental verification.
{"title":"Research and Implementation of Public Laboratory Information System Based on CS Structure","authors":"Ruimei Gao","doi":"10.1109/ICTech55460.2022.00022","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00022","url":null,"abstract":"Public laboratory as the basis of scientific research project activities in order to guarantee, during the practice operation need to reserve a large amount of data information, so under the background of new era in order to better implement diversified experimental activities, to ensure that the relevant data information is scientific reserves, must be combined with CS of optimization and improvement of the structure of information system. In this paper, on the basis of understanding the content of CS structure, according to the operational requirements of the practical system in the development of the relevant system at the same time to carry out experimental verification.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127062291","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00057
Wen Shi, Yue-Xia Tian, Song Wang, ChunWen Liu, Lei Yang, PiChao Zheng
This article is mainly to study the optimal storage allocation strategy of automated three-dimensional warehouse. A target mathematical model will be established from three aspects: goods circulation efficiency, shelf stability, and sorting and storage of goods, and a multi-target dimensionality reduction method will be used to convert multiple targets into single targets. The algorithm is based on genetic algorithm, introduces niche technology and simulated annealing algorithm for improvement, and adopts an adaptive cross-mutation operator to protect outstanding individuals in the later stage of the iteration. Finally, take the automated warehouse of a spandex company in Lianyungang as an example for experimental analysis. The results show that, compared with the regular genetic algorithm, the improved one converges faster, the solution set quality is better, and it is more effective for the storage allocation.
{"title":"Research on Storage Allocation Strategy of Automated Warehouse Based on Improved Genetic Algorithm","authors":"Wen Shi, Yue-Xia Tian, Song Wang, ChunWen Liu, Lei Yang, PiChao Zheng","doi":"10.1109/ICTech55460.2022.00057","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00057","url":null,"abstract":"This article is mainly to study the optimal storage allocation strategy of automated three-dimensional warehouse. A target mathematical model will be established from three aspects: goods circulation efficiency, shelf stability, and sorting and storage of goods, and a multi-target dimensionality reduction method will be used to convert multiple targets into single targets. The algorithm is based on genetic algorithm, introduces niche technology and simulated annealing algorithm for improvement, and adopts an adaptive cross-mutation operator to protect outstanding individuals in the later stage of the iteration. Finally, take the automated warehouse of a spandex company in Lianyungang as an example for experimental analysis. The results show that, compared with the regular genetic algorithm, the improved one converges faster, the solution set quality is better, and it is more effective for the storage allocation.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130597431","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：