PRODUCTS

  • Workflow process mining based on machine learning

    This paper presents an algorithm of workflow process mining based on machine learning from the logs of business process instances, which can handle concurrence and recurrence of the business process that are the restrictions of other algorithms.

    5 Best Bitcoin Mining Hardware ASIC Machines (2021

    2021-4-23 · Bitmain Bitmain makes the AntMiner line of Bitcoin miners. Bitmain is based in Beijing, China and also operates a mining pool. MicroBT MicroBT is another Chinese ASIC miner manufacturer, based out of Shenzhen. Their WhatsMiner series is a major competitor to Bitmain’s AntMiner line.

    Feature Mining for Machine Learning Based

    2014-7-4 · Feature Mining for Machine Learning Based Compilation Optimization Abstract: Compilation optimization is critical for software performance. Before a product releases, the most effective algorithm combination should be chosen to minimize the object file size or to maximize the running speed.

    Path Optimization of Coal Mining Machine Based on

    2016-10-22 · On the intelligent coal face, when coals fall down, the roller on the coal mining machine can recognize roof coal-rock interface and programme a motion path to avoid knifing the roof rock. It can not only effectively protect the rocker arm of coal mining machine but observably improve the quality of the raw coal produced on the working face.

    A Motion Control Algorithm for a Continuous Mining

    2005-10-12 · A Motion Control Algorithm for a Continuous Mining Machine Based on a Hierarchical Real-Time Control System Design Methodology 1 Hui-Min Huang, John Horst, and Richard Quintero Robot Systems Division National Institute of Standards and Technology Gaithersburg, Maryland

    Data Mining and Machine Learning for Condition

    2017-1-1 · Keywords: condition-based maintenance; data analytics; data mining; machine learning; failure event * Corresponding author. Tel.: +39 051 2093406; fax: +39 051 2093411. E-mail address: [email protected]bo.it 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (creativecommons.

    Data Mining vs Machine Learning 15 Best Things

    2019-12-9 · Data Mining is similar to experimental studies and works as an extension to business analytics. Machine Learning on the other hand, includes algorithms that can automatically improve through data-based experience. With experience, it finds new algorithms and enables the study of an algorithm that can automatically extract the data.

    (PDF) Research on Data Mining Technology Based on

    Machine learning and statistical algorithm are two common data mining algorithms. The first is to use artificial intelligence technology to automatically find the re quired patterns and parameters...

    Machine Learning and Data Mining(机器学习与数据挖掘

    2018-1-22 · It is a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, bioinformatics, data compression, and computer graphics.

    Deep-learning-based information mining from ocean

    2020-3-19 · Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical- or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications.

    The 7 Best Cryptocurrency Mining Hardware for 2021

    2021-5-10 · When it comes to cryptocurrency mining profitability, it all comes down to balancing the initial cost of the Bitcoin mining machine, its power draw, and its hash rate.Once you have these figures, it’s easy to calculate your gains based on Bitcoin’s block reward and your electricity cost by using this mining

    Machine Learning Based Text Mining in Electronic

    2018-6-12 · This article presents the approach and experimental study results of machine learning based text mining methods with application for EHR analysis. It is shown how the application of ML-based text mining methods to identify classes and features correlation to increases the possibility of

    Digital Art Feature Association Mining Based on the

    2021-4-7 · Practical machine learning database feature and characteristics of digital art association mining frequent experimental results show that the heuristic characteristics mining algorithm can effectively mine feature the characteristics of the digital art association mining pattern to further improve the overall feature recognition effect, based

    Large‐scale data mining using genetics‐based

    In the last decade, genetics‐based machine learning methods have shown their competence in large‐scale data mining tasks because of the scalability capacity that these techniques have demonstrated. T...

    A Motion Control Algorithm for a Continuous Mining

    2005-10-12 · design procedure for a hierarchical computer-assisted coal mining control system. Based on this previous work, this paper describes our effort to develop a software control algorithm for the motion control of a Joy 14CM 2 continuous miner (a continuous mining machine, see figure 1) [Jo 82]. This implementation is referred to as the "tram

    Data Mining and Machine Learning Models for

    Data mining approaches can uncover underlying patterns in chemical and pharmacological property space decisive for drug discovery and development. Two of the most common approaches are visualization and machine learning methods. Visualization methods use dimensionality reduction techniques in order

    Data Mining and Machine Learning TDK Technologies

    Data mining techniques assume that the relationships which are to be discovered exist within the dataset being examined. Machine learning is implementing some form of artificial “learning”, where “learning” is the ability to alter an existing model based on new information. Machine learning is utilized to improve decision-making models.

    GitHub mihinsumaria/AgroAnalytics: Agro Analytics

    Agro Analytics Data Mining/Machine Learning Project based on Agricultural datasets. For more info, go to agroanalytics.info

    Deep-learning-based information mining from ocean

    Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical- or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications.

    Resources Data Mining and Machine Learning

    2020-12-1 · 10 Sequence Mining: Chap10 PDF, Chap10 PPT. 11 Graph Pattern Mining: Chap11 PDF, Chap11 PPT. 12 Pattern and Rule Assessment: Chap12 PDF, Chap12 PPT. PART III. CLUSTERING. 13 Representative-based Clustering: Chap13 PDF, Chap13 PPT. 14 Hierarchical Clustering: Chap14 PDF, Chap14 PPT. 15 Density-based Clustering: Chap15 PDF, Chap15 PPT

    Machine Learning Based Text Mining in Electronic

    2018-6-12 · This article presents the approach and experimental study results of machine learning based text mining methods with application for EHR analysis. It is shown how the application of ML-based text mining methods to identify classes and features correlation to increases the possibility of

    Data Mining and Machine Learning: Fundamental

    2021-1-22 · Zaki & Meira Jr. (RPI and UFMG) Data Mining and Machine Learning Chap 13: Rep-based Clustering 2/31 K-means Algorithm: Objective The sum of squared errors scoring function is defined as

    A Motion Control Algorithm for a Continuous Mining

    2005-10-12 · design procedure for a hierarchical computer-assisted coal mining control system. Based on this previous work, this paper describes our effort to develop a software control algorithm for the motion control of a Joy 14CM 2 continuous miner (a continuous mining machine, see figure 1) [Jo 82]. This implementation is referred to as the "tram

    Deep-learning-based information mining from ocean

    Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical- or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications.

    Mining assumptions for software components using

    Simulation-Based Approaches for Verification of Embedded Control Systems: An Overview of Traditional and Advanced Modeling, Testing, and Verification Techniques. IEEE Control Systems Magazine 36, 6 ( 2016 ), 45-64. Google Scholar; Wenchao Li, Lili Dworkin, and Sanjit A. Seshia. 2011. Mining

    Algorithmic Trading Strategy Based On Massive Data

    2017-9-23 · U.S stocks everyday by mining the public data. To achieve this we build models that predict the daily return of a stock from a set of features. These features are constructed based on quoted and external data that is available before the prediction date. When considering machine learning models we

    Data Mining and Machine Learning TDK Technologies

    Data mining techniques assume that the relationships which are to be discovered exist within the dataset being examined. Machine learning is implementing some form of artificial “learning”, where “learning” is the ability to alter an existing model based on new information. Machine learning is utilized to improve decision-making models.

    GitHub mihinsumaria/AgroAnalytics: Agro Analytics

    Agro Analytics Data Mining/Machine Learning Project based on Agricultural datasets. For more info, go to agroanalytics.info

    A guide to predictive maintenance for the

    2020-4-16 · With the coming age of Industry 4.0, it’s no longer prudent, strategic or economically smart to wait until a critical mining asset has broken down to fix the machine.

    交通数据挖掘技术(Data Mining for Transportation)_东南

    交通数据挖掘技术(Data Mining for Transportation),spContent=The motivation for this course started with the development of information techniques. The amount of traffic data collected is growing at an increasing rate and are expecting more sophisticated analysis

    Machine Learning Based Text Mining in Electronic

    2018-6-12 · This article presents the approach and experimental study results of machine learning based text mining methods with application for EHR analysis. It is shown how the application of ML-based text mining methods to identify classes and features correlation to increases the possibility of

    Deep-learning-based information mining from ocean

    Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical- or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications.

    How mining companies are using AI, machine

    2019-9-13 · Many of us would assume that advances in robotics, automation, artificial intelligence (AI) and machine learning would have been driven by the mining industry, due to the remote mine sites, the

    Mining assumptions for software components using

    Simulation-Based Approaches for Verification of Embedded Control Systems: An Overview of Traditional and Advanced Modeling, Testing, and Verification Techniques. IEEE Control Systems Magazine 36, 6 ( 2016 ), 45-64. Google Scholar; Wenchao Li, Lili Dworkin, and Sanjit A. Seshia. 2011. Mining

    Algorithmic Trading Strategy Based On Massive Data

    2017-9-23 · U.S stocks everyday by mining the public data. To achieve this we build models that predict the daily return of a stock from a set of features. These features are constructed based on quoted and external data that is available before the prediction date. When considering machine learning models we

    Data Mining Lab UESTC

    Fundamental Data Mining. Synchronization-based Clustering, Subspace Clustering, Co-clustering, Multi-view learning, transfer learning, low-rank representation, etc. >> detail. Data Mining, Machine Learning, Brain Network Mining Qinli Yang. Associate Professor Research Fields: Data Mining, Hydrology and Water Resources. Zhongjing Yu.

    GitHub mihinsumaria/AgroAnalytics: Agro Analytics

    Agro Analytics Data Mining/Machine Learning Project based on Agricultural datasets. For more info, go to agroanalytics.info

    A guide to predictive maintenance for the

    2020-4-16 · With the coming age of Industry 4.0, it’s no longer prudent, strategic or economically smart to wait until a critical mining asset has broken down to fix the machine.

    What Is Text Mining? A Beginner's Guide MonkeyLearn

    Machine learning is a discipline derived from AI, which focuses on creating algorithms that enable computers to learn tasks based on examples. Machine learning models need to be trained with data, after which they’re able to predict with a certain level of accuracy automatically.

    交通数据挖掘技术(Data Mining for Transportation)_东南

    交通数据挖掘技术(Data Mining for Transportation),spContent=The motivation for this course started with the development of information techniques. The amount of traffic data collected is growing at an increasing rate and are expecting more sophisticated analysis