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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Jiao, Pengfei Guo, Chunxiang Shaanxi Fashion Engineering University School of Economics and Management Shaanxi Xi'an China

ISBN: (纸本)9798350317558

Many enterprises face data quality issues such as missing data, data errors, data inconsistencies, etc. Using data mining algorithms to analyze and predict market data has become an important way for enterprises to improve their competitiveness and market efficiency. This article adopts data mining algorithms, uses large-scale market data for analysis and modeling, and constructs a data set containing multiple characteristic variables by collecting and sorting historical market data. This article chooses data mining algorithms to train and model the data set, and optimizes the performance and accuracy of the model by repeatedly adjusting model parameters and evaluation indicators. Research results show that the algorithm's accuracy test data is between 85% and 94%. By using algorithms for data analysis, companies can more accurately predict market trends, customer behavior and sales performance. This helps companies develop more precise marketing strategies and resource allocation plans, and improve marketing effectiveness and return rates. © 2024 IEEE.

关键词： computer algorithm Data Analysis and Prediction Data Mining Marketing Strategy

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Analysis of the contribution of rural road infrastructure development to economic growth based on computer algorithms

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Gao, Hailin Tong, Guangji School of Economics and Management Northeast Forestry University Heilongjiang Harbin150040 China

A convenient and efficient rural road network helps to develop the rural economy and promote national rural revitalization. This paper systematically analyzes the role of rural road infrastructure construction on economic growth from a theoretical perspective. Simultaneously, it employs a computer algorithm based on vector autoregression to construct an econometric model. Based on this theoretical analysis empirically examines the relationship between rural infrastructure construction and economic development. It collects data from a city’s rural area from 2000 to 2020 as a research sample and conducts a series of analyses, including VAR model estimation, impulse response, and variance decomposition. The results show that rural road infrastructure construction has a significant impact on economic growth, with coefficients of -0.288 and 0.356 for lags 1 and 2. The construction of rural road infrastructure is responsible for more than 90% of the variation in economic growth, whereas the opposite is about 10%. Therefore, rural road infrastructure development does not have a significant effect on economic growth in the short term but has a significant effect in the medium and long term. © 2024 Hailin Gao and Guangji Tong, published by Sciendo.

关键词： computer algorithm Impulse response Road infrastructure development Variance decomposition Vector autoregression

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An Improved algorithm Design and Implementation Based on Unsupervised Learning in computer Games 34

An Improved Algorithm Design and Implementation Based on Uns...

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34th Chinese Control and Decision Conference (CCDC)

作者： Wu, Gui Jianghan Univ Educ Adm Off Wuhan 430056 Peoples R China

ISBN: (纸本)9781665478960

At present, the computer games with the intelligent algorithm optimization are always a popular research direction of the artificial intelligence. In this research field, the key concerned technologies and the important resolve are how to continue to gain the final winning rate constantly by independent identification realization, movement optimization and real-time update games based on the unsupervised learning algorithm in the computer chess games. According to the typical artificial intelligence application scene of computer games, an improved algorithm based on the unsupervised learning is designed and proposed in the paper. This algorithm uses alfa-beta search tree to select the best matching pattern and applies the concept of feature learning to make the image recognition innovatively. With the characteristics of the Checkers and the common search methods, it proposes a feature and pattern learning method based on the K-means clustering algorithm. By the experimental data and results, the improved algorithm proposed in the paper can gain and keep a high winning rate in the real games.

关键词： Unsupervised Learning computer algorithm computer Games Machine Learning

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computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

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JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY 2020年第3期82卷 622-627页

作者： Marchetti, Michael A. Liopyris, Konstantinos Dusza, Stephen W. Codella, Noel C. F. Gutman, David A. Helba, Brian Kalloo, Aadi Halpern, Allan C. Soyer, H. Peter Curiel-Lewandrowski, Clara Kittler, Harald Caffery, Liam Malvehy, Josep Wellenhof, Rainer Hofmann Mem Sloan Kettering Canc Ctr Dept Med Dermatol Serv 16 East 60th St New York NY 10022 USA Thomas J Watson Res Ctr IBM Res Div Yorktown Hts NY USA Emory Univ Sch Med Dept Neurol Atlanta GA 30322 USA Emory Univ Sch Med Dept Psychiat Atlanta GA 30322 USA Emory Univ Sch Med Dept Biomed Informat Atlanta GA USA Kitware Inc Clifton Pk NY USA Univ Queensland Dermatol Res Ctr Brisbane Qld Australia Univ Arizona Canc Ctr Tucson AZ USA Med Univ Vienna Dept Dermatol Vienna Austria Univ Queensland Brisbane Qld Australia Hosp Clin Barcelona Barcelona Spain Med Univ Graz Graz Austria

Background: computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain. Objective: To determine if computer algorithms from an international melanoma detection challenge can improve dermatologists' accuracy in diagnosing melanoma. Methods: In this cross-sectional study, we used 150 dermoscopy images (50 melanomas, 50 nevi, 50 seborrheic keratoses) from the test dataset of a melanoma detection challenge, along with algorithm results from 23 teams. Eight dermatologists and 9 dermatology residents classified dermoscopic lesion images in an online reader study and provided their confidence level. Results: The top-ranked computer algorithm had an area under the receiver operating characteristic curve of 0.87, which was higher than that of the dermatologists (0.74) and residents (0.66) (P < .001 for all comparisons). At the dermatologists' overall sensitivity in classification of 76.0%, the algorithm had a superior specificity (85.0% vs. 72.6%, P = .001). Imputation of computer algorithm classifications into dermatologist evaluations with low confidence ratings (26.6% of evaluations) increased dermatologist sensitivity from 76.0% to 80.8% and specificity from 72.6% to 72.8%. Limitations: Artificial study setting lacking the full spectrum of skin lesions as well as clinical metadata. Conclusion: Accumulating evidence suggests that deep neural networks can classify skin images of melanoma and its benign mimickers with high accuracy and potentially improve human performance.

关键词： automated melanoma diagnosis computer algorithm computer vision deep learning dermatologist International Skin Imaging Collaboration International Symposium on Biomedical Imaging machine learning melanoma reader study skin cancer

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Machine learning-based processing of unbalanced data sets for computer algorithms

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OPEN computer SCIENCE 2023年第1期13卷

作者： Zhou, Qingwei Qi, Yongjun Tang, Hailin Wu, Peng Guangdong Baiyun Univ Fac Megadata & Comp Guangzhou 510450 Guangdong Peoples R China Mongolian Univ Sci & Technol Sch Informat & Commun Technol Ulan Bator 13341 Mongolia Sichuan Tourism Univ Sch Informat & Engn Chengdu 610000 Sichuan Peoples R China

The rapid development of technology allows people to obtain a large amount of data, which contains important information and various noises. How to obtain useful knowledge from data is the most important thing at this stage of machine learning (ML). The problem of unbalanced classification is currently an important topic in the field of data mining and ML. At present, this problem has attracted more and more attention and is a relatively new challenge for academia and industry. The problem of unbalanced classification involves classifying data when there is insufficient data or severe category distribution deviations. Due to the inherent complexity of unbalanced data sets, more new algorithms and tools are needed to effectively convert a large amount of raw data into useful information and knowledge. Unbalanced data set is a special case of classification problem, in which the distribution between classes is uneven, and it is difficult to classify data accurately. This article mainly introduces the research on the processing method of computer algorithms based on the processing method of unbalanced data sets based on ML, aiming to provide some ideas and directions for the processing of computer algorithms based on unbalanced data sets based on ML. This article proposes a research strategy for processing unbalanced data sets based on ML, including data preprocessing, decision tree data classification algorithm, and C4.5 algorithm, which are used to conduct research experiments on processing methods for unbalanced data sets based on ML. The experimental results in this article show that the accuracy rate of the decision tree C4.5 algorithm based on ML is 94.80%, which can be better used for processing unbalanced data sets based on ML.

关键词： machine learning unbalanced data sets classification algorithm data processing computer algorithm decision tree classification

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Some results on constructing three-level blocked designs with general minimum lower-order confounding

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2025年

作者： Li, Zhi Li, Zhiming Tian, Rui Li, Zhengqi Xinjiang Univ Coll Math & Syst Sci Urumqi Peoples R China

Blocked designs are widely used in experimental situations when the experimental units are not homogeneous. This article introduces the blocked general minimum lower-order confounding (B1-GMC) criterion for selecting optimal three-level blocked designs. Some properties of three-level B1-GMC designs are provided in terms of their complementary sets. We obtain a systematic theory on constructing three-level B1-GMC designs. Several efficient algorithms for finding three-level B1-GMC designs are provided and implemented by Python. For application, B1-GMC designs with 27-, 81- and 243-run, respectively, are tabulated.

关键词： Blocked designs blocked general minimum lower-order confounding computer algorithm

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Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis

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BMC ORAL HEALTH 2025年第1期25卷 1-21页

作者： Sadeghi, Termeh Sarrafan Ourang, Seyed AmirHossein Sohrabniya, Fatemeh Sadr, Soroush Shobeiri, Parnian Motamedian, Saeed Reza Shahid Beheshti Univ Med Sci Res Inst Dent Sci Dentofacial Deform Res Ctr Tehran Iran Hamadan Univ Med Sci Sch Dent Dept Endodont Hamadan Iran Mem Sloan Kettering Canc Ctr Dept Radiol New York NY 10065 USA Shahid Beheshti Univ Med Sci Sch Dent Dept Orthodont Daneshjoo BlvdShahid Chamran Highway Tehran *** Iran

BackgroundArtificial intelligence (AI) methods, including machine learning and deep learning, are increasingly applied in orthodontics for tasks like assessing skeletal maturity. Accurate timing of treatment is crucial, but traditional methods such as cervical vertebral maturation (CVM) staging have limitations due to observer variability and complexity. AI has the potential to automate CVM assessment, enhancing reliability and user-friendliness. This systematic review and meta-analysis aimed to evaluate the overall performance of artificial intelligence (AI) models in assessing cervical vertebrae maturation (CVM) in radiographs, when compared to *** databases of Medline (via PubMed), Google Scholar, Scopus, Embase, IEEE ArXiv and MedRxiv were searched for publications after 2010, without any limitation on language. In the present review, we included studies that reported AI models' performance on CVM assessment. Quality assessment was done using Quality assessment and diagnostic accuracy Tool-2 (QUADAS-2). Quantitative analysis was conducted using hierarchical logistic regression for meta-analysis on diagnostic accuracy. Subgroup analysis was conducted on different AI subsets (Deep learning, and Machine learning).ResultsA total of 1606 studies were screened of which 25 studies were included. The performance of the models was acceptable. However, it varied based on the methods employed. Eight studies had a low risk of bias in all domains. Twelve studies were included in the meta-analysis and their pooled values for sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated for each cervical stage (CS). The most accurate CVM evaluation was observed for CS1, boasting a sensitivity of 0.87, a specificity of 0.97, and a DOR of 213. Conversely, CS3 exhibited the lowest performance with a sensitivity of 0.64, and a specificity of 0.96, yet maintaining a DOR of *** has demonstrated

关键词： Artificial intelligence Growth and development Cervical vertebrae Orthodontics computer algorithm

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Comparison of QT Correction Methods in the Pediatric Population of a Community Hospital: A Retrospective Study

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Congenital Heart Disease 2024年第1期19卷 107-121页

作者： Koren Hyogene Kwag Ibrahim Kak Ying Li Walid Khass Alec McKechnie Oksana Nulman Brande Brown Manoj Chhabra Department of Pediatrics New York Presbyterian Brooklyn Methodist HospitalBrooklyn11215USA Department of Population Health Sciences Division of BiostatisticsWeill Cornell MedicineNew York10065USA

Objective:Accurate measurement of QT interval,the ventricular action potential from depolarization to repolarization,is important for the early detection of Long QT *** most effective QT correction(QTc)formula has yet to be determined in the pediatric population,although it has intrinsically greater extremes in heart rate(HR)and is more susceptible to errors in *** authors of this study compare six dif-ferent QTc methods(Bazett,Fridericia,Framingham,Hodges,Rautaharju,and a computer algorithm utilizing the Bazett formula)for consistency against variations in HR and RR ***:Descriptive Retrospective *** included participants from a pediatric cardiology practice of a community hospital who had an ECG performed in *** participants were healthy patients with no past medical history and no regular ***:ECGs from 95 participants from one month to 21 years of age(mean 9.7 years)were included with a mean HR of 91 beats per minute(bpm).The two-sample paired t-test or Wilcoxon signed-rank test assessed for any difference between QTc methods.A statistically signiﬁcant difference was observed between every combination of two QTc *** Spearman’s rank correlation analysis explored the QTc/HR and QTc/RR relationships for each *** method was most independent of HR and RR with the lowest absolute value of correlation coefﬁ*** and computer had moderate correlations,while Framingham and Rautaharju exhibited strong *** were positive for Bazett and computer,reﬂecting results from prior studies demonstrating an over-correction of Bazett at higher *** the linear QTc/HR regression analysis,Bazett had the slope closest to zero,although computer,Hodges,and Fridericia had comparable ***,Fridericia had the linear QTc/RR regression coefﬁcient closest to *** Bland-Altman method assessed for bias and the limits of agreement between correction *** an

关键词： Corrected QT interval QT prolongation long QT syndrome electrocardiogram retrospective study bazett fridericia framingham hodges rautaharju computer algorithm

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An Improved algorithm Design and Implementation Based on Unsupervised Learning in computer Games

An Improved Algorithm Design and Implementation Based on Uns...

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第34届中国控制与决策会议

作者： Gui Wu Educational Administration office Jianghan University

At present,the computer games with the intelligent algorithm optimization are always a popular research direction of the artificial *** this research field,the key concerned technologies and the important resolve are how to continue to gain the final winning rate constantly by independent identification realization,movement optimization and real-time update games based on the unsupervised learning algorithm in the computer chess *** to the typical artificial intelligence application scene of computer games,an improved algorithm based on the unsupervised learning is designed and proposed in the *** algorithm uses alfa-beta search tree to select the best matching pattern and applies the concept of feature learning to make the image recognition *** the characteristics of the Checkers and the common search methods,it proposes a feature and pattern learning method based on the K-means clustering *** the experimental data and results,the improved algorithm proposed in the paper can gain and keep a high winning rate in the real games.

关键词： Unsupervised Learning computer algorithm computer Games Machine Learning

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Graph-Theory-Based Derivation, Modeling, and Control of Power Converter Systems

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IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS 2022年第6期10卷 6557-6571页

作者： Li, Yuzhuo Kuprat, Johannes Li, Yunwei Liserre, Marco Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada Univ Kiel Chair Power Elect Kiel Germany

Graph-theoretical approaches have been widely applied in many disciplines, however, their implementation in power electronics converters and systems is still in the exploring stage. In this overview, we summarize the milestones and general applications of this powerful mathematical tool and illustrate its unique benefits in some emerging/challenging power electronics research topics, for example, systematic converter derivation and modeling, advanced control, and so on. Given the multidiscipline nature of power electronics, graph theory can serve as a bridge for experts in different disciplines with a universal framework for complex problems. With solid mathematical foundations, it can stimulate research of topological aspects in both converter and systematic levels, fits well for nowadays power electronics converter. It is hoped that this article can serve as a timely and handy summary for engineers/students who want to enter the field and promote the innovation of power-electronics-enabled applications.

关键词： Circuit theory computer algorithm converter modeling and control converter system converter topology duality graph theory isomorphism power routing

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