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检索条件"任意字段=6th International Conference on Algorithms and Discrete Applied Mathematics"

共 914 条记录，以下是211-220 订阅

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Analysing Business Process Anomalies Using discrete-Time Markov chains 22

Analysing Business Process Anomalies Using Discrete-Time Mar...

引用

22nd IEEE international conference on High Performance Computing and Communications, 18th IEEE international conference on Smart City and 6th IEEE international conference on Data Science and Systems, HPCC-SmartCity-DSS 2020

作者： Yang, Lingkai McClean, Sally Donnelly, Mark Khan, Kashaf Burke, Kevin Ulster University School of Computing Jordanstown United Kingdom British Telecom Ipswich United Kingdom University of Limerick Macsi Limerick Ireland

ISBN: (纸本)9781728176499

Within a business context, anomalies can be viewed as indicators for inefficiencies or fraud, which impact upon product quality and customer satisfaction. the development of approaches to monitor, detect and predict anomalous business processes remains an important research topic. In this paper, we propose a method, combining discrete-Time Markov chains (DTMCs) and hitting probabilities (HP), for detecting anomalies occurring in the execution of business processes. Our method extends standard DTMCs to be able to estimate the probability of occurring for a process instance even though it is partially recorded (i.e., the initial executions are missing). the proposed method, denoted as HPDTMC, does not rely on prior knowledge about anomalies and the business process and can be trained on datasets already consisting of anomalies. A Šidák correction is applied to balance the probability of instances of varying length since naturally, process instances with more executions have lower sequence probability and more likely to be detected as anomalies by using DTMCs. We demonstrate the effectiveness of the method by evaluating it on two artificial datasets and one real-life dataset against seven classic anomaly detection methods. In the experiments, our approach reached an F1 score of 0.904 on average. Moreover, the proposed method outperforms competitors under noisy conditions. the main contribution of this paper is the proposed noise-robust method which is able to detect fully or partially recorded process instances of varying lengths. © 2020 IEEE.

关键词： Anomaly detection

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discrete Time Sliding Mode Control of Milling Chatter 6th

Discrete Time Sliding Mode Control of Milling Chatter

引用

6th international conference on Computer Science, applied mathematics and Applications (ICCSAMA)

作者： Paul, Satyam Lofstrand, Magnus Orebro Univ Sch Sci & Technol Orebro Sweden

ISBN: (纸本)9783030383640;9783030383633

the technique of mitigating chatter phenomenon in an effective manner is an important issue from the viewpoint of superior quality machining process with quality production. In this paper, an innovative solution to control chatter vibration actively in the milling process is presented. the mathematical modelling associated with the milling technique is presented in the primary phase of the paper. In this paper, an innovative technique of discrete time sliding mode control (DSMC) is blended with Type 2 fuzzy logic system. Superior mitigation of chatter is the outcome of developed active controller. the Lyapunov scheme is implemented to validate the stability criteria of the proposed controller. the embedded nonlinearity in the cutting forces and damper friction are compensated in an effective manner by the utilization of Type-2 fuzzy technique. the vibration attenuation ability of DSMC-Type-2 fuzzy (DSMC-T2) is compared with the discrete time PID (D-PID) and DSMC-Type-1 fuzzy (DSMC-T1) for validating the effectiveness of the controller. Finally, the numerical analysis is carried out to validate that DSMC-T2 is superior to D-PID and DSMC-T1 in the minimization of the milling chatter.

关键词： Milling chatter Type-2 fuzzy Sliding mode control

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Numerical solution of the dynamic incentive problem in discrete time taking into account the learning curve effect 6

Numerical solution of the dynamic incentive problem in discr...

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6th international conference Information Technology and Nanotechnology. Session Data Science, ITNT-DS 2020

作者： Pavlov, Oleg Samara National Research University Institute of Economics and Management Samara Russia

the paper considers the dynamic incentive problem in discrete time, taking into account the learning effect. the task is formulated as a dynamic game between the leader and the performers. To solve the problem, the principle of cost recovery is applied, which reduces the original task to the optimal control problem in discrete time. Numerical solutions of the problem for various models of learning curves are obtained using the Bellman dynamic programming method. Also, the study is conducted of the discount rate's impact on the solution of the incentive problem. Copyright © 2020 for this paper by its authors.

关键词： Dynamic programming

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Regularization Methods for Neural Network Models and Logistic Regression Models in the Problem of Classifying Industrial Products into Homogeneous Batches 34

Regularization Methods for Neural Network Models and Logisti...

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34th international conference on Information Technologies, InfoTech 2020

作者： Krutikov, Vladimir Nikolaevich Shkaberina, Guzel Sharipzhanovna Tovbis, Elena Mikhailovna Kazakovtsev, Lev Alexandrovich Kemerovo State University Department of Applied Mathematics 6 Krasnaya street Kemerovo650043 Russia Reshetnev Siberian State University of Science and Technology prosp. Krasnoyarskiy Rabochiy 31 Krasnoyarsk660031 Russia

ISBN: (数字)9781728169149

ISBN: (纸本)9781728169149

In this paper the problem of automatic grouping of semiconductor devices by homogeneous production batches is investigated. algorithms for training logistic regression and an artificial neural network with regularization in the problems of classification of industrial products into homogeneous production batches are proposed. © 2020 IEEE.

关键词： Neural networks

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Review on Sliding Mode Controller and Its Modified Types for Rehabilitation Robots 6

Review on Sliding Mode Controller and Its Modified Types for...

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6th IEEE international conference on Engineering, Technologies and applied Sciences, ICETAS 2019

作者： Ahmed, Syed Faiz Raza, Yarooq Mahdi, Hussain F. Wan Muhamad, W.M. Kamran Joyo, M. Shah, Asadullah Koondhar, M.Y. International Islamic University Malaysia American University of Kurdistan Iraq Universiti Kuala Lumpur Malaysia Sindh Agriculture University Tandojam Pakistan University of Diyala Iraq

ISBN: (纸本)9781728140827

Recent advancements in the field of rehabilitation robotics have led to the development of variety of exoskeletons that are used extensively during therapeutic exercises for the poststroke patients. these robotic devices are meant to provide ease and comfort to the patient undergoing therapy, so controlling these robots effectively is very crucial. Widely used control algorithms for controlling these devices are linear controllers which are not much robust and efficient as compared to non-linear controllers. Since rehabilitation robots are highly nonlinear in nature, therefore nonlinear controllers are required that can perform well under uncertainties and resistant to parametric changes. One of the most extensively used non-linear control method is Sliding Mode Controller (SMC). SMC has proved its robustness in terms of trajectory tracking, stability and insensitiveness to disturbances and parametric uncertainties. One drawback of using classical SMC is chattering, which is high frequency oscillations. this paper presents sliding mode controller and its different types along with the method of chattering removal, for controlling rehabilitation robotic devices. © 2019 IEEE.

关键词： Exoskeleton (Robotics)

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Research on Traffic Information Extraction Approach Based on Image Deep Learning

Research on Traffic Information Extraction Approach Based on...

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international conference on Transportation Information and Safety (ICTIS)

作者： Manke Lu Yi He Bo Cao Yihong Wang Feng Xu Intelligent Transport Systems Research Center Wuhan University of Technology Wuhan China China Merchants International Technology Company Limited Shenzhen China China Transport Telecommunication &#x0026 Information Center Beijing China

ISBN: (纸本)9781665497145

With the rapid development of deep learning methods in the field of computer vision, the effective methods can be applied to the classification and positioning of traffic targets based on real traffic data. this paper studies the application of convolutional neural network in the real traffic information extraction field. the YOLOv3 target detection algorithm, the Faster RCNN target detection algorithm and the SSD target detection algorithm are used to detect vehicles in the images collected in same road condition, and generate the result graph of the target detection. the experimental results show that the YOLOv3 target detection algorithm, Faster RCNN target detection algorithm and SSD target detection algorithm can identify all traffic targets in the traffic road images. It reveals the three algorithms meet the detection needs, and help to achieve non-contact traffic flow collection and feature recognition. Meanwhile these algorithms can provide technical means for traffic supervision and safety improvement.

关键词： Training Deep learning Roads Object detection Streaming media Information retrieval Real-time systems

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Reduced Order Modelling of Higher-Order Systems by ICG Technique

Reduced Order Modelling of Higher-Order Systems by ICG Techn...

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international conference on Computing, Communication & Automation (ICCCA)

作者： Ankur Gupta Amit Kumar Manocha GZSCCET MRS Punjab Technical University Bathinda Punjab India Punjab Institute of Technology (Maharaja Ranjit Singh Punjab Technical University) GTB Garh Moga Punjab India

ISBN: (纸本)9781665447539

the complexity of the control mechanisms is increasing with the developments occurring around the world. For the continuous monitoring of the complex systems, the order of the systems must be reduced. Hence, a model order abatement technique, enhanced clustering-plus-genetic (ICG) is presented in the paper. the technique is a merger of two techniques; one is improved pole clustering and second is genetic algorithm. An enhanced pole clustering technique lay-out the denominator while genetic algorithm succours to procure the numerator of reduced-order system. the technique proposed in the paper has the main feature that reduced-order system have the effect of all poles, existing in the higher-order system are involved in deriving the poles of reduced-order system. ICG MOR technique is applied to the single variable continuous-time as well as discrete-time system. the potency of the evolved method is checked by comparing the time and frequency domain performance characteristics of higher-order system with the value of parameters for reduced-order system and error values like integral absolute error (IAE), integral time absolute error (ITAE) and integral square error (ISE). To study the supremacy of the ICG technique, its comparison is executed with other techniques developed in recent years.

关键词： Linear systems discrete-time systems Corporate acquisitions Frequency-domain analysis conferences Reduced order systems Steady-state

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Type Identification and Feature Selection of Chinese Poor Families Based on Density and Feature Aggregation

Type Identification and Feature Selection of Chinese Poor Fa...

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IEEE international conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Hui Liu Jinchong Zhu Yang Liu Ran Zhang Zheng Zhang Dalian University of Technology Dalian China School of software Dalian University of Technology Dalian China International School Shenyang Jianzhu University Shenyang China International School of Information Science & Engineering Dalian University of Technology Dalian China

the problem of poverty is widespread throughout the world. From the dataset of families to identify poor family types and screen main features. It is of great research significance to take targeted measures in poverty alleviation. In this paper, a clustering method based on density and hierarchy is designed to solve the problem of density inhomogeneity and discontinuous data clustering of poor families. the algorithm divides the dense data into several initial clusters and merges iteratively according to the core-point distance between clusters. then, we propose a feature selection algorithm based on feature distribution location for the important feature selection problem of multidimensional poverty data. this algorithm locates the locations of various features gathered in the data space according to the Gaussian mixture components, and selects the features with relatively discrete locations as the main features of each category of data. Experiments show that proposed methods can recognize clusters of different densities in the data space and select important features of each category. And the analysis of dataset of Chinese Poor Families provides a basis for further designing targeted measures in poverty alleviation.

关键词： Cloud computing conferences Computational modeling Clustering methods Clustering algorithms Big Data Feature extraction

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Recommendation Engines: Traditional vs Deep Learning Approaches

Recommendation Engines: Traditional vs Deep Learning Approac...

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IEEE international conference on Computing, Communication and Security (ICCCS)

作者： Aniket Dhawad Suranjana Sarkar Amit Agarwal Rama Kishore Darlapudi Enterprise Analytics &#x0026 Data Science Artificial Intelligence-Center of Excellence Wells Fargo International Solutions Private Limited Bangalore India

ISBN: (纸本)9781665440400

With digitlzation growing by leap and bounds, websites are now overloaded with products and information density, making it challenging for customers to choose between a variety of products. the Recommendation engine enables companies to deliver their customers more personalized and customized products or information efficiently. As a result, the recommendation engine eventually helps in boosting different business performance metrics such as revenues, Click- through Rates (CTRs), conversions, etc., for these companies significantly. And in the long run, it also optimizes user experience, thus translating to higher customer satisfaction and retention. In this paper, we will highlight some of the contemporary algorithms used in building high-performance recommendation engines, illustrate use cases from Tech Giants that can be applied in the context of the banking and financial services domain and identify major challenges that are open for further research work. Also, in this paper, we will be using recommendation engine and recommender system alternatively as both are synonymous.

关键词： Computational modeling Scalability Buildings Companies User experience Reproducibility of results Registers

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Exploiting symmetries of small prime-sized DFTs 13th

Exploiting symmetries of small prime-sized DFTs

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13th international conference on Parallel Processing and applied mathematics, PPAM 2019

作者： Popovici, Doru thom Parikh, Devangi N. Spampinato, Daniele G. Low, Tze Meng Lawrence Berkeley National Lab BerkeleyCA United States University of Texas at Austin AustinTX United States Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9783030432287

Small prime-sized discrete Fourier transforms appear in various applications from quantum mechanics, material sciences and machine learning. the typical implementation of the discrete Fourier transform for such problem sizes is done as a cyclic convolution using algorithms like Rader or Bluestein. However, these approaches exhibit extra computation and expensive data movement. In this work, we present an alternative method by casting the Fourier transform as a direct symmetric matrix-vector multiplication. Exploiting the symmetries of the Fourier matrix and using knowledge from dense linear algebra, we present an implementation that reduces the amount of computation and requires less memory usage. We show that this approach achieves up to 2x performance gains on Intel and AMD architectures, compared to implementations offered by Intel MKL and FFTW that use Rader and Bluestein. © Springer Nature Switzerland AG 2020.

关键词： discrete Fourier transforms

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