Gas disaster has always been a major safety problem in the coal mine field. The prediction of gas concentration in fully mechanized mining face is of great significance to ensure the safety of mine production and the safety of underground personnel. A Long short-term Memory (LSTM) neural network model based on time series is proposed for the prediction of gas concentration. Since there are many factors affecting the gas emission and there is a complex nonlinear relationship between them, a method of data preprocessing is proposed to weaken the data volatility, combined with the powerful GPU function of the computer, to build an LSTM neural network in the Tensorflow environment Gas Emission Prediction Model, using root mean square error (RMSE) and running time, for evaluating forecast performance. The prediction results are compared with the SVR network, and the results show that the LSTM model has higher prediction accuracy and prediction stability.
{"title":"Prediction of gas concentration in fully mechanized mining face based on LSTM model based on time series","authors":"Xiucai Guo, Xin Xie","doi":"10.1117/12.2671890","DOIUrl":"https://doi.org/10.1117/12.2671890","url":null,"abstract":"Gas disaster has always been a major safety problem in the coal mine field. The prediction of gas concentration in fully mechanized mining face is of great significance to ensure the safety of mine production and the safety of underground personnel. A Long short-term Memory (LSTM) neural network model based on time series is proposed for the prediction of gas concentration. Since there are many factors affecting the gas emission and there is a complex nonlinear relationship between them, a method of data preprocessing is proposed to weaken the data volatility, combined with the powerful GPU function of the computer, to build an LSTM neural network in the Tensorflow environment Gas Emission Prediction Model, using root mean square error (RMSE) and running time, for evaluating forecast performance. The prediction results are compared with the SVR network, and the results show that the LSTM model has higher prediction accuracy and prediction stability.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124531831","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}
Z. Wang, Zhi Xin, Xiaojun Tang, Xin Zhang, Yan Xie
In order to further enhance the active power regulation capacity of China power grid, this paper analyzes the necessity of constructing accident reserve capacity of power grid under the new power system from the aspects of receiving terminal characteristics, new energy development and load fluctuation. In order to further improve the active power regulation ability of my country's power grid, the necessity of constructing the emergency reserve capacity allocation of my country's power grid under the construction of a new power system is analyzed from the aspects of receiving terminal characteristics, new energy development and load fluctuation.
{"title":"Configuration method of power grid accident reserve for new power system","authors":"Z. Wang, Zhi Xin, Xiaojun Tang, Xin Zhang, Yan Xie","doi":"10.1117/12.2671916","DOIUrl":"https://doi.org/10.1117/12.2671916","url":null,"abstract":"In order to further enhance the active power regulation capacity of China power grid, this paper analyzes the necessity of constructing accident reserve capacity of power grid under the new power system from the aspects of receiving terminal characteristics, new energy development and load fluctuation. In order to further improve the active power regulation ability of my country's power grid, the necessity of constructing the emergency reserve capacity allocation of my country's power grid under the construction of a new power system is analyzed from the aspects of receiving terminal characteristics, new energy development and load fluctuation.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121653364","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}
The general purpose FPSO may encounter captain misjudgment, mooring system failure, direct alignment with the direction of the coming wave, and lead to a variety of wave directions, such as oblique wave, cross wave, and aft wave. The fluid analysis software FLUENT was used to simulate the general FPSO model, and seven wave directions of 0°, 30°, 60°, 90°, 120°, 150°, and 180° were simulated. The results show that the ship’s bow can withstand the extreme waves with the 100-year recurrence period in the Brazilian sea area successfully, but all the other conditions have different degrees of upsurge phenomenon. In addition, the bow board can resist not only the bow board up-wave phenomenon but also the bow board and cross wave, which makes the bow board up-wave degree lower. In the case of wave direction of 120°, 90°, and 180°, the threat degree of upsurge is very high, and it is necessary to further evaluate the capsizing risk. This conclusion has certain guiding significance for the design of ship-type FPSO in the following extreme sea conditions.
{"title":"Analysis on deck waves of general-purpose FPSO under extreme sea conditions","authors":"S. Zhao, Peilin Dou, Hongtao Yuan, Yue Qi, Xiu Li","doi":"10.1117/12.2672262","DOIUrl":"https://doi.org/10.1117/12.2672262","url":null,"abstract":"The general purpose FPSO may encounter captain misjudgment, mooring system failure, direct alignment with the direction of the coming wave, and lead to a variety of wave directions, such as oblique wave, cross wave, and aft wave. The fluid analysis software FLUENT was used to simulate the general FPSO model, and seven wave directions of 0°, 30°, 60°, 90°, 120°, 150°, and 180° were simulated. The results show that the ship’s bow can withstand the extreme waves with the 100-year recurrence period in the Brazilian sea area successfully, but all the other conditions have different degrees of upsurge phenomenon. In addition, the bow board can resist not only the bow board up-wave phenomenon but also the bow board and cross wave, which makes the bow board up-wave degree lower. In the case of wave direction of 120°, 90°, and 180°, the threat degree of upsurge is very high, and it is necessary to further evaluate the capsizing risk. This conclusion has certain guiding significance for the design of ship-type FPSO in the following extreme sea conditions.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122105498","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}
This paper is to predict the presence of recurrence for breast cancer patients by citing data. As a first step we will collect relevant data on breast cancer patients from the internet. Next, we will use decision trees in Scikit-learn to determine if there will be a recurrence of breast cancer in patients who have been cured. Through a series of calculations and predictions, the accuracy of our experimental model finally reaches 0.75 accuracy. These data can help us to accomplish our target prediction well.
{"title":"Breast cancer prediction using machine learning models","authors":"Zhiqi Li, Shirui Tian, Tain Ya, Zhenning Yang","doi":"10.1117/12.2672652","DOIUrl":"https://doi.org/10.1117/12.2672652","url":null,"abstract":"This paper is to predict the presence of recurrence for breast cancer patients by citing data. As a first step we will collect relevant data on breast cancer patients from the internet. Next, we will use decision trees in Scikit-learn to determine if there will be a recurrence of breast cancer in patients who have been cured. Through a series of calculations and predictions, the accuracy of our experimental model finally reaches 0.75 accuracy. These data can help us to accomplish our target prediction well.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"331 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063056","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}
Aiming at some key test positions of the installed shielding vehicle that do not meet the test distance, the paper analyzes the prominent problems that are difficult or impossible to measure during the shielding effectiveness test, and analyzes the factors that cause the problem. The hole-cavity coupling theory is used to establish the theoretical correction factor models of different frequency bands in the installed state are established, and the correctness of the proposed method is verified through theoretical calculations and actual case tests, and the theoretical correction factor of the installed state is used to correct the shielding effectiveness of the known empty vehicle, to obtain the application shielding performance of key positions where the installed shielding vehicle does not meet the test distance, avoiding the testing of the installed shielding vehicle, thus greatly improving the ability to obtain the shielding performance of the installed shielding vehicle.
{"title":"Research on shielding effectiveness of shielding vehicle based on wall boundary effect","authors":"Yang Qiu, C. Ma, Zongyuan Tian","doi":"10.1117/12.2673050","DOIUrl":"https://doi.org/10.1117/12.2673050","url":null,"abstract":"Aiming at some key test positions of the installed shielding vehicle that do not meet the test distance, the paper analyzes the prominent problems that are difficult or impossible to measure during the shielding effectiveness test, and analyzes the factors that cause the problem. The hole-cavity coupling theory is used to establish the theoretical correction factor models of different frequency bands in the installed state are established, and the correctness of the proposed method is verified through theoretical calculations and actual case tests, and the theoretical correction factor of the installed state is used to correct the shielding effectiveness of the known empty vehicle, to obtain the application shielding performance of key positions where the installed shielding vehicle does not meet the test distance, avoiding the testing of the installed shielding vehicle, thus greatly improving the ability to obtain the shielding performance of the installed shielding vehicle.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126420848","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}
Aiming at the problem that the accuracy of conventional algorithms is low in the case of few samples for bearing vibration signal fault diagnosis, this paper proposes a bearing fault diagnosis method based on prototypical network in few-shot and zero-shot scenarios. The method first uses the original vibration signals or spectrogram features as input; then uses the neural network model to extract the distinguishable features, and prototype center of each category is learned through prototypical network; finally, the classification of each sample is completed by the distance measurement method. The experimental results show that prototypical network method with scaled CQT features as input and convolutional neural network as encoder has excellent performance in few-shot and zero-shot bearing fault diagnosis.
{"title":"Bearing fault diagnosis based on prototypical network","authors":"Hao Shen, Dexin Zhao, L. Wang, Qi Liu","doi":"10.1117/12.2671906","DOIUrl":"https://doi.org/10.1117/12.2671906","url":null,"abstract":"Aiming at the problem that the accuracy of conventional algorithms is low in the case of few samples for bearing vibration signal fault diagnosis, this paper proposes a bearing fault diagnosis method based on prototypical network in few-shot and zero-shot scenarios. The method first uses the original vibration signals or spectrogram features as input; then uses the neural network model to extract the distinguishable features, and prototype center of each category is learned through prototypical network; finally, the classification of each sample is completed by the distance measurement method. The experimental results show that prototypical network method with scaled CQT features as input and convolutional neural network as encoder has excellent performance in few-shot and zero-shot bearing fault diagnosis.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132652945","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}
Zhengyi Ma, Qiming Yu, Run Xue, Yan Li, Haibo Liu, Haining Li, Peilong Lu
Deepfake open source technology has lowered the threshold for AI face swapping to a very low level, making it possible to swap faces with one click. The cost of "disinformation" is greatly reduced, so that some deeply faked pictures and videos can be spread on social networks The social network can spread explosively. However, in the defense layer, there are almost no standardized and automated detection tools for deepfake. There is no such tool. Therefore, whether for individuals or platforms, the time window for fighting fake and disinformation is very short, but it is very difficult. In this paper, we use the Transformer model as a base, improve the model and optimize the structure of the model, so that the model can extract the depth features of the video and build a more accurate and efficient deepfake inspection method.
{"title":"Deepfake detection technique based on improved transformer model","authors":"Zhengyi Ma, Qiming Yu, Run Xue, Yan Li, Haibo Liu, Haining Li, Peilong Lu","doi":"10.1117/12.2671814","DOIUrl":"https://doi.org/10.1117/12.2671814","url":null,"abstract":"Deepfake open source technology has lowered the threshold for AI face swapping to a very low level, making it possible to swap faces with one click. The cost of \"disinformation\" is greatly reduced, so that some deeply faked pictures and videos can be spread on social networks The social network can spread explosively. However, in the defense layer, there are almost no standardized and automated detection tools for deepfake. There is no such tool. Therefore, whether for individuals or platforms, the time window for fighting fake and disinformation is very short, but it is very difficult. In this paper, we use the Transformer model as a base, improve the model and optimize the structure of the model, so that the model can extract the depth features of the video and build a more accurate and efficient deepfake inspection method.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131637706","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}
Statistical learning methods require large-scale data to make the significant generalized probability and observation error close to each other. Few-shot learning can alleviate this situation, but it cannot break through the limitations of statistical learning methods. The training model only depends on the correlation between data distributions. There may be potential risks in applying these models to decision-making in the natural environment. This paper studies feature selection in small sample regression analysis based on AutoMPG and MOP The performance of the two datasets on the regression task is first verified through three classical regression analysis models. Then, through the causal inference method, this paper analyzes the causal effect of the relationship between the features in the dataset and finds that two groups of features do not have a causal relationship. Finally, by setting up a simulation environment, this paper illustrates the potential risks of not considering the causal effect in feature selection.
{"title":"The feature selection strategy of few-shot learning based on causal inference","authors":"Jining Zhang, Xiaodong Zhu, Yuanning Liu","doi":"10.1117/12.2672724","DOIUrl":"https://doi.org/10.1117/12.2672724","url":null,"abstract":"Statistical learning methods require large-scale data to make the significant generalized probability and observation error close to each other. Few-shot learning can alleviate this situation, but it cannot break through the limitations of statistical learning methods. The training model only depends on the correlation between data distributions. There may be potential risks in applying these models to decision-making in the natural environment. This paper studies feature selection in small sample regression analysis based on AutoMPG and MOP The performance of the two datasets on the regression task is first verified through three classical regression analysis models. Then, through the causal inference method, this paper analyzes the causal effect of the relationship between the features in the dataset and finds that two groups of features do not have a causal relationship. Finally, by setting up a simulation environment, this paper illustrates the potential risks of not considering the causal effect in feature selection.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134232414","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}
The weight reduction of the frame longitudinal beam directly affects the weight reduction of the frame. The intelligent algorithm is applied to the lightweight problem of the frame, and aimed to the area of the longitudinal beam section is optimized. The genetic algorithm, simulated annealing algorithm, particle swarm optimization algorithm and ant colony optimization are compared. The static working condition of the optimized frame is analyzed. The results show that all four algorithms can get the solution satisfying the constraint conditions, and the particle swarm optimization algorithm is the fastest, the simulated annealing algorithm is the slowest, and the other two algorithms are moderate. All four algorithms reduced the weight of the frame, the ant colony optimization reduced by 4.1%, and the other three ways reduced by 6.8%.
{"title":"Comparison of algorithms based on lightweight frame problems","authors":"Jian Zhang, Wei Ran, Xuemei Qi","doi":"10.1117/12.2671851","DOIUrl":"https://doi.org/10.1117/12.2671851","url":null,"abstract":"The weight reduction of the frame longitudinal beam directly affects the weight reduction of the frame. The intelligent algorithm is applied to the lightweight problem of the frame, and aimed to the area of the longitudinal beam section is optimized. The genetic algorithm, simulated annealing algorithm, particle swarm optimization algorithm and ant colony optimization are compared. The static working condition of the optimized frame is analyzed. The results show that all four algorithms can get the solution satisfying the constraint conditions, and the particle swarm optimization algorithm is the fastest, the simulated annealing algorithm is the slowest, and the other two algorithms are moderate. All four algorithms reduced the weight of the frame, the ant colony optimization reduced by 4.1%, and the other three ways reduced by 6.8%.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132686166","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}
With the continuous improvement of radar performance, it is very difficult to break through the enemy's radar defense net by relying solely on trajectory planning. In actual penetration, fighters use a variety of electronic jamming methods to achieve penetration. Based on the dynamic changes of RCS, this paper model the discovery probability of penetration fighters under active jamming and passive jamming respectively, and studies the factors that affect the penetration probability and survival rate of fighters under different jamming situations. By comparing the radar detection probability with and without jamming, it is concluded that the fighter's active and passive jamming can effectively reduce the radar detection probability. This article has certain guiding significance for the fighter's dynamic penetration.
{"title":"Study on detection probability of radar under active and passive jamming","authors":"Wenyuan Zhang, Haojun Xu, Zeng-gui Chen, B. Pei","doi":"10.1117/12.2672654","DOIUrl":"https://doi.org/10.1117/12.2672654","url":null,"abstract":"With the continuous improvement of radar performance, it is very difficult to break through the enemy's radar defense net by relying solely on trajectory planning. In actual penetration, fighters use a variety of electronic jamming methods to achieve penetration. Based on the dynamic changes of RCS, this paper model the discovery probability of penetration fighters under active jamming and passive jamming respectively, and studies the factors that affect the penetration probability and survival rate of fighters under different jamming situations. By comparing the radar detection probability with and without jamming, it is concluded that the fighter's active and passive jamming can effectively reduce the radar detection probability. This article has certain guiding significance for the fighter's dynamic penetration.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128841685","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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