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8th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

作者： Wang, Denggui Yang, Rong Shenzhen Univ Coll Machatron & Control Engn Shenzhen Peoples R China

ISBN: (纸本)9781538663240

Pedestrian detection is a significant task with many applications including smart vehicles, surveillance and robotics. Due to the variations in appearance, pose, color, illumination and interference, accuracy and robustness in pedestrian detection are desired to be improved. This paper proposes a new method that introduces Choquet integral to fuse the Histogram of Oriented Gradients (HOG) and local binary pattern (LBP) descriptor in parallel. The fusion descriptor is used as a detector for pedestrian detection with Support Vector Machine (svm) algorithm. Experiments are carried out on the INRIA Person Dataset and the results validate the efficiency of the proposed method.

关键词： Pedestrian detection HOG LBP svm algorithm

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Optimization of Injection Production Matching Strategy in Reservoir Development Process Using Support Vector Machine algorithm 24

Optimization of Injection Production Matching Strategy in Re...

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International Conference on Machine Intelligence and Digital Applications (MIDA)

作者： Jiang, Chunhua Daqing Oilfield Ltd Co Inst Geol Oil Prod Plant 6 Daqing 163000 Heilongjiang Peoples R China

ISBN: (纸本)9798400718144

This article explores how to use Support Vector Machine (svm) algorithm to optimize the injection production matching strategy in the process of reservoir development. By establishing an svm-based prediction model, this article aims to improve the injection and production efficiency of oil fields and address the limitations of traditional methods in processing nonlinear and complex data. The article first reviews the main challenges in current reservoir management and existing injection production matching methods, followed by a detailed introduction to the principle of svm algorithm and its application in reservoir management. Through comparative experiments and case analysis, the effectiveness of the svm model in improving oilfield recovery and economic benefits is verified. After adopting the svm strategy, the injection production efficiency improves by about 15% and the oil-water ratio improves by 20%. The svm model also tends to perform stably in oil fields of different geological types. During the one-year experimental period, the svm algorithm maintains a performance improvement of about 5% in each month. The experimental data results show the effectiveness and reliability of svm algorithm in oilfield injection production matching optimization, demonstrating the potential of svm algorithm in improving oilfield development efficiency and economic benefits.

关键词： Reservoir management Injection production matching strategy svm algorithm Linear regression method

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Automated Polycystic Ovarian Syndrome Identification with Follicle Recognition 3

Automated Polycystic Ovarian Syndrome Identification with Fo...

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3rd International Conference on Signal Processing and Communication (ICPSC)

作者： Madhumitha, J. Kalaiyarasi, M. Ram, S. Sakthiya Bannari Amman Inst Technol Dept EIE Sathyamangalam Tamil Nadu India

ISBN: (纸本)9781665428644

The use of ultrasound, also known as sonography, has assisted in the identification and care of infertile patients. Ultrasound imaging of the ovary's follicles provides crucial details about the ovary, such as the type of cyst, the large range of follicles, and the size of the follicles reaction to hormonal imbalance. Image Segmentation provides additional details about the region of interest in an image and accurately identifies the object and its background from the image. However, since segmentation on ultrasound images is difficult owing to noise, identification of follicles can be made simple and efficient by combining photograph preprocessing with morphological operations. svm, KNN and Logistic Regression algorithm of Machine learning are used for classification which taking into considerations of all the specifications of PCOS Ovaries and Normal ovaries. The result obtained through the classification are compared through physical identification. The proposed hybrid method of combining all three algorithms is implemented, for which the accuracy obtained is 98%.

关键词： Polycystic Ovary Segmentation Classification svm algorithm KNN algorithm Logistic Regression

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Action recognition for sports combined training based on wearable sensor technology and svm prediction

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PREVENTIVE MEDICINE 2023年第1期173卷 107582-107582页

作者： Liu, Zhewei Wang, Xuefeng Jiangsu Univ Science&Technol Suzhou Inst Technol Sch Publ Educ Zhangjiagang 215600 Peoples R China Jiangsu Univ Science&Technol Sch Publ Educ Zhangjiagang 215600 Peoples R China

In the field of sports, coaches have mainly relied on observing the performance of athletes on the spot to formulate suitable training plans for athletes, which has extremely high requirements for the professionalism of coaches. Based on the above requirements, this paper designs a sports action recognition system for sports enthusiasts based on the svm algorithm optimization model, and for the purpose of verifying the applicability of the system to different sports fields, experiments are carried out on basketball actions and race walking actions. The system uses wearable sensors to capture the motion data of the user, and then analyzes and identifies the user's actions through the svm algorithm optimization model. By standardizing the user's sports combination training under the system algorithm, the user can improve their training efficiency and reduce the risk of injury. To establish the human body motion model, this paper divides the human skeleton model into five motion branches. The rotation freedom constraints and joint rotation angle range limits are added to the model to ensure the accuracy of the motion analysis. Combining the forward kinematics of the robot and the homogeneous coordinate transformation, the human body joint rotation motion model and the human bone position and posture model are established. In the end, the user can standardize the sports combination training under the system algorithm. In this paper, through the research of wearable sensor technology and sports combined training action recognition, and apply it to practical life, it aims to promote its development and application.

关键词： Wearable sensor Sports combined training svm algorithm Injury prevention Action recognition

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The algorithm Study of Support Vector Machine Based on Social Network of Public Opinions

The Algorithm Study of Support Vector Machine Based on Socia...

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International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Xie Hongbiao Qiu Hongjun Hangzhou Dianzi Univ Informat Engn Sch Hangzhou 310018 Zhejiang Peoples R China

ISBN: (纸本)9783038350125

Public opinion refers to the certain social groups' subjective reflection of certain social phenomena and reality within a period of time. The important measures to maintain social stability and the ruling party's ruling safety are to instantly master the dynamic public opinion and to actively guide social public opinion. In this paper, the author found the model of social network public opinion hotspot issues. The svm algorithm is adopted to improve the information processing and analysis testing, effectively resolving the text classification problem. It verifies that this method plays an important role in the hot issues' analyses of the network link.

关键词： Social Network Public Opinion Hotspot svm algorithm

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Seizure Onset Detection based on a Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) System

Seizure Onset Detection based on a Uni- or Multi-modal Intel...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Conradsen, Isa Beniczky, Sandor Wolf, Peter Henriksen, Jonas Sams, Thomas Sorensen, Helge B. D. DTU Elect Engn Bldg 349 DK-2800 Lyngby Denmark Danish Epilepsy Ctr DK-4293 Dianalund Denmark

ISBN: (纸本)9781424441242

An automatic Uni- or Multi-modal Inteligent Seizure Acquisition (UISA/MISA) system is highly applicable for onset detection of epileptic seizures based on motion data. The modalities used are surface electromyography (sEMG), acceleration (ACC) and angular velocity (ANG). The new proposed automatic algorithm on motion data is extracting features as "log-sum" measures of discrete wavelet components. Classification into the two groups "seizure" versus "non-seizure" is made based on the support vector machine (svm) algorithm. The algorithm performs with a sensitivity of 91-100%, a median latency of 1 second and a specificity of 100% on multi-modal data from five healthy subjects simulating seizures. The uni-modal algorithm based on sEMG data from the subjects and patients performs satisfactorily in some cases. As expected, our results clearly show superiority of the multi-modal approach, as compared with the uni-modal one.

关键词： MISA system svm algorithm UISA system acceleration measurement acceleration measurement angular velocity measurement angular velocity measurement automatic algorithm biomechanics data acquisition discrete wavelet components discrete wavelet transforms diseases electromyography epileptic seizure onset detection feature extraction feature extraction log sum measures medical signal detection medical signal processing motion data multimodal intelligent seizure acquisition system neurophysiology sEMG support vector machine support vector machines surface electromyography unimodal intelligent seizure acquisition system

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Protein Sequence Structure Prediction Using Artificial Intelligent Techniques 16

Protein Sequence Structure Prediction Using Artificial Intel...

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International Conference on Advances in Information Communication Technology and Computing

作者： Upadhyay, Ved Prakash Panwar, Subhash Merugu, Ramchander Govt Engn Coll Bikaner Rajasthan India Mahatma Gandhi Univ Nalgonda Telangana India

ISBN: (纸本)9781450342131

Predicting structure of the protein is one of the most significant application of modern computational biology. Researchers are working on this field for so many years and have been tried various approaches for getting a good accuracy for the prediction task. With advent of artificial intelligence techniques researchers have started to focus on using machine learning algorithms for the task of protein structure prediction. Also AI techniques provides much better accuracy as compare to traditional methods used previously for protein structure prediction. Here we have been surveyed research work done by the researchers for predicting protein structure using AI techniques. We have been studied top most highly cited articles published in this field and derived a complete summery report regarding the application of AI techniques in protein structure prediction.

关键词： Artificial Intelligence Protein structure Prediction Computational biology svm algorithm

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Advanced And Effective Classification of Parkinson's Disease Using Enhanced Neural Networks

Advanced And Effective Classification of Parkinson's Disease...

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International Conference on Intelligent Computing and Control Systems (ICICCS)

作者： Kumar, Kaveti Kiran Babu, Panthagani Vijay Gopi, Simhadri Chinna Arfa, Zoya Vignans Fdn Sci Technol & Res CSE Dept Vadlamudi Andhra Pradesh India MLRIT CSE Dept Hyderabad Telangana India

ISBN: (纸本)9781728148762

A disease that causes due to degeneration in the nerve cells in brain parts with which movements are controlled is a Parkinson's disease. Parkinson's disease increased its occurrence with age and it's becoming the second most common neurodegenerative disorder. Due to this disease, people begin to experience difficulty in speaking, writing, walking. We can diagnose this disease by using voice recordings dataset, handwritten images, and by using several techniques. In this paper, we are using a voice dataset to identify Parkinson's disease which is collected from different people with and without Parkinson's disease. There are several medical tools to identify this disease but it may take time and laborious to identify this disease. In this patients has to take any number of tests as a single test cannot give an effective diagnosis of a disease. So to mitigate this, our work establishes a computer-based analysis technique. We can identify and diagnose this disease using several classification algorithms in machine learning like decision trees, naive bayes algorithm, svm algorithm are few neural networks. In this paper, we use neural networks to classify the disease.

关键词： Decision trees Naive Bayes algorithm svm algorithm Parkinson's disease (PD) Multilayer Perceptron(MLP)

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The three dimensional model of Ideological and Political Instructors

The three dimensional model of Ideological and Political Ins...

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International Conference on Smart City and Systems Engineering (ICSCSE)

作者： Wang, Feng Zhu, Wenjuan Wen, Quan Xu, Ting Chen, Guang Jiangxi Univ Tradit Chinese Med Coll Comp Nanchang 330004 Jiangxi Peoples R China Jiangxi Univ Tradit Chinese Med Coll Pharm Nanchang 330004 Jiangxi Peoples R China Univ Tradit Chinese Med Dept Student Affairs Nanchang 330004 Jiangxi Peoples R China Nanchang Yuzhang Middle Sch Dept Math Nanchang 330006 Jiangxi Peoples R China Jiangxi Univ Tradit Chinese Med Sch Econ & Management Nanchang 330004 Jiangxi Peoples R China

ISBN: (纸本)9781509055302

The University Ideological and political counselors as ideological communicators, has important role in the social stability and unity, with the country of thought right unified attention, more and more researchers take this as an important research project, played a very good effect, but with the diversification of education trend, how to carry out more quantitative analysis of Ideological and political instructors, this problem is an important project of scientific research personnel, establish based on the qualitative discussion on the quantitative model, through the establishment of three-dimensional model of University Counselors ideological and political considerations, the establishment of svm algorithm and expert system are introduced, have good robustness, high precision, consider the evaluation of the effectiveness of the fair.

关键词： expert system Ideological and political instructor svm algorithm three dimensional model

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Countries Condition of Forestation and Trees Percentage using Machine learning 8

Countries Condition of Forestation and Trees Percentage usin...

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8th International Conference on System Modeling and Advancement in Research Trends (SMART)

作者： Abdullha, Abir Habib, Yeasin Masum, Md Raisul Islam Rabby, A. K. M. Shahariar Azad Daffodil Int Univ Dept CSE Dhaka Bangladesh Apurba Technol Dhaka Bangladesh

ISBN: (纸本)9781728132457

Most countries are now in a dangerous place for forestation and some are in developed forestation. So forestation and trees percentage prediction are to predict the condition of the countries about their condition of forestation and tress percentage. The paper is about a machine learning model to predict the countries condition. We used logistic regression, svm AND Naive Bayes to predict the condition also for matrix. we also find the accuracy of logistic regression, svm, Nave Bayes, Ada boosting classifier, Decision tree, ANN, Linear Discriminant Analysis, Gradient Boosting Classifier, MLP Classifier to find our best accuracy and compare with them with our data. we give details of selected algorithms. We collected some previous data and present data and comparing them to predict the condition of the country. we use some conditions and logic for machine learning. By logistic regression, svm and Nave Bayes will show us the prediction and condition of those chosen countries.

关键词： Logistics algorithm svm algorithm Naive Bayes algorithm Details About algorithms Compare algorithm Accuracy Condition of Countries in Forestation

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