检索结果-内蒙古大学图书馆

Australian and New Zealand Control Conference (ANZCC)

作者： Pooja, W. Snehal, N. Sonam, K. Wagh, S. R. Singh, N. M. VJTI EED Control & Decis Res Ctr CDRC Mumbai Maharashtra India

ISBN: (纸本)9781665416504

Machine learning is widely being used in medical field for disease diagnostics and *** area of machine learning is mainly classified into 3 parts: supervised, unsupervised and reinforcement *** machine learning (ML) algorithms are used in this paper for modeling and showing the impact of increased testing on the number of daily confirmed cases of COVID-19. The algorithms used to carry out this study are decision tree regression and random forest regression. Machine learning for modeling has proven to be significant for forecasting and hence decision making over the future course of actions. In this paper, Gaussian process regression has been used for modeling as well as forecasting the daily confirmed cases in South Korea. The results obtained show that if the number of tests conducted is increased to the population of South Korea, approximately equal to 51, 286, 183, the peak in the daily cases is obtained earlier and hence the overall number of daily cases is less compared to current cases.

关键词： COVID 19 decision tree algorithm Gaussian process regression machine learning random forest algorithm

来源：评论

学校读者我要写书评

暂无评论

decision tree algorithms for image data type identification

引用

LOGIC JOURNAL OF THE IGPL 2017年第1期25卷 67-82页

作者： Khoa Nguyen Dat Tran Ma, Wanli Sharma, Dharmendra Univ Canberra Fac Educ Sci Technol & Math Canberra ACT 2601 Australia

Identifying file type of file fragments has been investigated for a long time but it is still a challenge. It is found in the literature that high-entropy file fragments make the problem more complicated. Especially, existing popular file types share same compression algorithms such as deflate algorithm that causes file type identification for file fragment become harder. Applying machine learning or empirical techniques is to deal with this problem. Compression algorithms are used to reduce the size of files that have big data size and include image files. Many research work of file type identification have been done for JPEG format, and the Rate of Change feature is proven to work effectively for it. Conversely, few efforts have been made for PNG although this is a popular image format and widely used nowadays. In this article, we propose a new approach based on the deflate-encoded data detection, entropy-based clustering, and decision tree techniques to identify PNG data fragments which are the deflate-encoded fragments. Experiments showed high accuracy rates for the proposed method.

关键词： File fragment identification image data type identification PNG SVM decision tree algorithm Shannon entropy

来源：评论

学校读者我要写书评

暂无评论

Data Mining algorithms(KNN & DT) Based Predictive Analysis on Selected Candidates in Academic Performance 11

Data Mining Algorithms(KNN & DT) Based Predictive Analysis o...

引用

11th International Conference on Cloud Computing, Data Science and Engineering (Confluence)

作者： Ramalingam, M. Ilakkiya, R. Kongu Engn Coll Dept Informat Technol Erode Tamil Nadu India

ISBN: (纸本)9781665414517

we are presenting a predictive analysis of the academic performance of the students in Kongu Engineering College based on the academic performance of the passed out students. The performance of the students both in academic and in the placement is degrading every year which needs to be analyzed in order to improve the performance of the students for the upcoming batches. The placement performance of the students purely depends on academic performance and also on co-curricular performance. So, both will be taken for consideration. The involvement in the co-curricular activities and extra-curricular activities also affects the placement performance of the students. Thus, the data relating in the academic results, co-curricular activities, extracurricular involvement details and other personal details has to be considered for the prediction. The datasets are collected from various resources and the primary thirty six parameters were considered as parameters that have high impact on placement performance. The missing details were filled manually with the help of the faculties. Chi-square method is used for selecting the features that matches both the placed and non-placed students. Classification models were created to predict the placement performance of the students at the end of the last semester for each dataset.

关键词： Data Mining KNN decision tree algorithm Data Analytics

来源：评论

学校读者我要写书评

暂无评论

Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions

引用

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年第PartE期208卷 109244-109244页

作者： Otchere, Daniel Asante Ganat, Tarek Omar Arbi Ojero, Jude Oghenerurie Tackie-Otoo, Bennet Nii Taki, Mohamed Yassir Univ Teknol PETRONAS Dept Petr Engn Seri Iskandar 32610 Perak Darul Rid Malaysia Univ Teknol PETRONAS Ctr Res Enhanced Oil Recovery Seri Iskandar 32610 Perak Darul Rid Malaysia Univ Manchester Sch Earth & Environm Sci Oxford Rd Manchester M13 9PL Lancs England Natl Off Hydrocarbons & Mines Dept Explorat 5 Ave Moulay Rachid Rabat Morocco

Feature Selection, a critical data preprocessing step in machine learning, is an effective way in removing irrelevant variables, thus reducing the dimensionality of input features. Removing uninformative or, even worse, misinformative input columns helps train a machine learning model on a more generalised data with better performances on new and unseen data. In this paper, eight feature selection techniques paired with the gradient boosting regressor model were evaluated based on the statistical comparison of their prediction errors and computational efficiency in characterising a shallow marine reservoir. Analysis of the results shows that the best technique in selecting relevant logs for permeability, porosity and water saturation prediction was the Random Forest, SelectKBest and Lasso regularisation methods, respectively. These techniques did not only reduce the features of the high dimensional dataset but also achieved low prediction errors based on MAE and RMSE and improved computational efficiency. This indicates that the Random Forest, SelectKBest, and Lasso regularisation can identify the best input features for permeability, porosity and water saturation predictions, respectively.

关键词： Feature selection techniques Dimensionality reduction techniques Reservoir characterisation Ensemble machine learning decision tree algorithm

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Assisted Prediction for Free-Space Continuous Variable Quantum Teleportation

IEEE PHOTONICS JOURNAL

引用

IEEE PHOTONICS JOURNAL 2022年第4期14卷 1页

作者： Xu, Jiaye Mao, Yun Chen, Yuxin Xu, Xiaowen Guo, Ying Cent South Univ Sch Phys & Elect Changsha 410083 Peoples R China Cent South Univ Sch Automat Changsha 410083 Peoples R China

Satellite-based quantum communication is critical in establishing a global quantum network for its ability to achieve thousand-kilometer-level tasks without the requirement of quantum relay. The free-space channel, however, is affected by diffraction, regular refraction, and atmospheric turbulence, which induce random wandering and broadening of the transmitted beam, resulting in the transmittance of fluctuation. In such a scenario, the ability to predict the unknown situation has become a problem worth considering. In this paper, we suggest a machine learning (ML) assisted prediction of continuous-variable quantum teleportation (CVQT) over satellite-ground channel. We apply the prediction algorithm, which involves k-nearest neighbor (KNN) algorithm and decision tree (DT) algorithm, to the squeezing parameter and the satellite altitude. Numerical analysis shows that the predicted parameter can reflect the actual derivation and calculation under certain circumstances within the allowable range of error. Moreover, we apply the prediction algorithm to the case affected by the fluctuating parameter transmittance. The results show that the ML-assisted prediction results are consistent with the actual data when zenith angles, turbulence strengths, and wavelengths are taken into account. It demonstrates the high identifying accuracy without increasing the complexity of the system.

关键词： Continuous variable quantum teleportation machine learning K-nearest neighbor algorithm decision tree algorithm

来源：评论

学校读者我要写书评

暂无评论

An overview of big data mining and data privacy protection technologies

An overview of big data mining and data privacy protection t...

引用

作者： Jinyang Liu Wuhan City College

With the advent of the era of big data, data mining techniques have significantly improved their ability to extract valuable information from data. However, privacy dangers are growing. Consequently, securing the protection of personal privacy during the mining of massive amounts of data has become a significant challenge. This paper examines the relationship between data mining techniques and privacy protection measures through a review of the pertinent literature. It provides a concise analysis of the benefits and drawbacks of commonly utilized classification algorithms in data mining. In addition, it examines the interplay between data mining techniques and privacy protection and summarizes important privacy protection *** privacy protection methods. These techniques include data anonymization,association rule concealing, data perturbation, etc. By comprehending these privacy protection techniques, appropriate privacy safeguards can be selected to ensure the privacy and security of the data when conducting data mining.

关键词： big data mining privacy protection big data processing workflow decision tree algorithm k-means algorithm

来源：评论

学校读者我要写书评

暂无评论

Data Mining for Animal Health to Improve Human Quality of Life: Insights from a University Veterinary Hospital 10

Data Mining for Animal Health to Improve Human Quality of Li...

引用

10th International Conference on Data Science, Technology and Applications (DATA)

作者： Tamburis, Oscar Masciari, Elio Esposito, Christian Fatone, Gerardo Univ Naples Federico II Dept Vet Med & Anim Prod Via Delpino 1 Naples Italy Univ Naples Federico II Dept Comp Sci & Elect Engn Naples Italy Univ Salerno Dept Comp Sci Fisciano SA Italy

ISBN: (纸本)9789897585210

The increasing importance of Veterinary Informatics is driving the implementation of integrated veterinary information management systems (VIMS) for the capture, storage, analysis and retrieval of animal data. In this paper, a decision tree algorithm was implemented, starting from the database of the University Veterinary Hospital at Federico II University of Naples, aiming at building a predictive model for an effective recognition of neoplastic diseases and zoonoses for cats and dogs focusing to Campania Region, in order to figure out, according to the One (Digital) Health perspective specifics, the connection between humans, animals, and surrounding environment.

关键词： Veterinary Medicine Electronic Medical Record decision tree algorithm One Health

来源：评论

学校读者我要写书评

暂无评论

Environmental cost control system of manufacturing enterprises using artificial intelligence based on value chain of circular economy

引用

ENTERPRISE INFORMATION SYSTEMS 2022年第8-9期16卷 Article: 1856422页

作者： Chen, Min Liu, Qian Huang, Shuai Dang, Chenlu Wenzhou Univ Acad Financial Res Sch Business Wenzhou Peoples R China Suihua Univ Sch Literature & Media Suihua Peoples R China Shanghai Univ Finance & Econ Sch Publ Econ & Adm Shanghai Peoples R China Xian Int Studies Univ Sch Econ & Finance Xian 710128 Peoples R China

In this study, expecting to form a virtuous circle conducive to socio-economic development. The problems of environmental cost control mode, and the relationship between the value chain and environmental cost control was discussed. The decision tree algorithm of artificial intelligence (AI) was applied in designing the environmental cost control system of manufacturing enterprises to realise the internalisation of environmental cost. The external environmental consumption cost was calculated by taking an oil production plant as the research object according to the environmental cost report of the oil production plant, and relevant suggestions were proposed for the enterprise's environmental cost scheme control.

关键词： Circular economy manufacturing enterprises environmental cost control artificial intelligence decision tree algorithm value chain

来源：评论

学校读者我要写书评

暂无评论

Copper particle detection method by in-situ resistance background implemented in conductance-path recognition algorithm (iRB-CPR) among dominant aluminum particles

引用

MEASUREMENT 2022年 193卷 1页

作者： Sejati, Prima Asmara Baidillah, Marlin Ramadhan Prayitno, Yosephus Ardean Kurnianto Ibrahim, Kiagus Aufa Kawashima, Daisuke Takei, Masahiro Chiba Univ Grad Sch Sci & Engn Dept Mech Engn Div Fundamental Engn Chiba 2638522 Japan Univ Gadjah Mada Vocat Coll Dept Elect Engn & Informat Yogyakarta 55281 Indonesia Natl Res & Innovat Agcy Jakarta 10340 Indonesia Univ Gadjah Mada Vocat Coll Dept Mech Engn Yogyakarta 55281 Indonesia Chiba Univ Grad Sch Engn Dept Mech Engn Div Fundamental Engn Chiba Japan

Copper particle has been detected among dominant aluminum particles by in-situ resistance background implemented in conductance-path recognition algorithm (iRB-CPR). The iRB is a particle volume fraction prediction from a resistance background database measured by shifted-four-wire measurement (SRM) in various particle arrangements. The CPR is adopted from a decision tree algorithm to predict the particle conductance path by comparing the real-condition resistances classified by iRB. The selected resistance background is used as a denominator to normalize the resistance measurement by SRM under unknown particle arrangement in the real condition. Finally, Cu is detected by comparing the normalized resistances with the normalized spatial-mean resistance. The iRB-CPR successfully suppress the resistance deviation ratio in the simulation (r)(sim) 93.8% and experiment (r)(exp) 73.9%. Moreover, the Cu detection by iRB-CPR satisfies give a low error E-S = 6.11% at S = 180 under alpha = 10%. This research opens a new detection modality as a part of non-ferrous metal particles recovery.

关键词： Electrical resistance measurement Conducting path Non-ferrous metal particles decision tree algorithm

来源：评论

学校读者我要写书评

暂无评论

Suggesting teaching methods by analyzing the behavior of children with special needs

引用

BIO-algorithmS AND MED-SYSTEMS 2020年第1期16卷 1-20页

作者： Shrawankar, Urmila Shireen, Azra GH Raisoni Coll Engn Dept Comp Sci & Engn Nagpur MS India

The behavioral pattern of children with special needs depends on their emotional and developmental disability. Any abnormal and incorrect pattern of behavior which is below the level of development as the expected norm can be considered as "the challenging behavior." For supporting children with behavioral problems, many interventions and strategies alone, or in combination, are used. Behavioral and developmental problems, if not treated well, in childhood, may cause a problem and have negative long-term and short-term effects on a child's personal life, education, family, and professional life. Detailed knowledge about the child's behavior is important to define the problem. Hence, the software contains the questionnaire pattern, which is divided into categories like parents, teachers, doctors, and friends. Child behavior checklist is used to define the questionnaire. Images and video analysis are used to detect the current emotion in the child. By analyzing the behavioral pattern and current emotion, the teaching method will be suggested.

关键词： behavioral disorder behavioral recognizing data analytics data preprocessing decision tree algorithm Microsoft emotion/face API mood detection teaching interventions video frames detector video processing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：