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Data Preprocessing and Intelligent Data Analysis

A. Famili, Wei-Min Shen, Richard Weber, Evangelos Simoudis
1997 Intelligent Data Analysis  
White, Preprocessing Remotely-Sensed Data for Efficient Analysis and Classification, Applications of Artificial Intelligence, Proceedings of SPIE-The International Society for Optical Engineering-1963,  ...  The following are some of the important issues to be considered when data has to be preprocessed for data analysis: (i) Although data preprocessing is useful and in many applications necessary in order  ...  Data Preprocessing and Intelligent Data Analysis A.  ... 
doi:10.3233/ida-1997-1102 fatcat:mhuuckxqzrdpxnmxrhw3v4672e

Data set preprocessing and transformation in a database system

Carlos Ordonez
2011 Intelligent Data Analysis  
This article presents a summary of our experience and recommendations to compute data set preprocessing and transformation inside a database system (i.e. data cleaning, record selection, summarization,  ...  In general, there is a significant amount of data mining analysis performed outside a database system, which creates many data management issues.  ...  Rote from Teradata Corporation for his valuable guidance and support to migrate many data mining projects into the DBMS.  ... 
doi:10.3233/ida-2011-0485 fatcat:7jifmmcbdbbmribvdylnx3eqri

Preprocessing remotely sensed data for efficient analysis and classification

Patrick M. Kelly, James M. White, Usama M. Fayyad, Ramasamy Uthurusamy
1993 Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry  
Interpreting remotely-sensed data typically requires expensive, specialized computing machinery capable of storing and manipulating large amounts of data quickly.  ...  In this paper, we present a method for accurately analyzing and categorizing remotely-sensed data on much smaller, less expensive platforms.  ...  The method of data analysis and classi cation presented in this paper rst preprocesses the data using a fast clustering algorithm.  ... 
doi:10.1117/12.141745 fatcat:xxphtjosgbhz3on5gtbvzqyv6u

Clustering of Preprocessed Web Usage Data Using ART1 Neural Network and Comparative Analysis of ART1, K-Means and SOM Clustering Techniques

H.K. Yogish, G.T. Raju
2013 2013 5th International Conference on Computational Intelligence and Communication Networks  
Web Usage Data is related to web activity. The majority of the techniques that have been used for pattern discovery from Web Usage Data are clustering methods.  ...  In e-commerce applications, clustering methods can be used for the purpose of generating marketing strategies, product offerings, personalization and Web site adaptation and also used for preload webpages  ...  It involves two stages -Feature Extraction stage and the Clustering Stage. First, the features from the preprocessed log data are extracted and a binary pattern vector P is generated.  ... 
doi:10.1109/cicn.2013.73 fatcat:erecma7sgzbkdflgeunsabwz6i

A Data Preprocessing Method Applied to Cluster Analysis on Stock Data by Kmeans

Zhigang Xiong, Zhongneng Zhang
2016 Proceedings of the 2016 International Conference on Intelligent Control and Computer Application   unpublished
Recent years, more and more data mining methods are involved in applications like stock price analysis or predication, etc. Kmeans is one commonly used algorithm in those applications.  ...  In this paper, we propose one way to quantify the variation trend of different curves, which can make kmeans clustering algorithm more effective on stocks analysis.  ...  In general, people are willing to use cluster analysis to guide International Conference on Intelligent Control and Computer Application (ICCA 2016) the trading transaction of stocks.  ... 
doi:10.2991/icca-16.2016.32 fatcat:nz4zondbyfc7jcpc74oxi7kane

Data Preprocessing Techniques in Convolutional Neural Network based on Fault Diagnosis towards Rotating Machinery

Shengnan Tang, Shouqi Yuan, Yong Zhu
2020 IEEE Access  
, and cyclic spectral analysis.  ...  Finally, the potential challenges and research objects are prospected on data preprocessing in intelligent fault diagnosis of rotary machinery.  ...  Finally, the challenges and prospects of data preprocessing are provided in intelligent fault diagnosis towards rotating machinery. II.  ... 
doi:10.1109/access.2020.3012182 fatcat:j6btd65gtnbjzbdbowtrqd6qju

Application of Computational Intelligence Methods for the Automated Identification of Paper-Ink Samples Based on LIBS

Krzysztof Rzecki, Tomasz Sośnicki, Mateusz Baran, Michał Niedźwiecki, Małgorzata Król, Tomasz Łojewski, U Rajendra Acharya, Özal Yildirim, Paweł Pławiak
2018 Figshare  
Laser-induced breakdown spectroscopy (LIBS) is an important analysis technique with applications in many industrial branches and fields of scientific research.  ...  This paper proposes the use of various computational intelligence methods to develop a reliable and fast classification of quasi-destructively acquired LIBS spectra into a set of predefined classes.  ...  The analysis of the LIBS spectrum consisted of the following steps: 1. independent preprocessing of LIBS spectra; 2. selection of data for the cross validation and testing sets; 3. data analysis based  ... 
doi:10.6084/m9.figshare.7272380 fatcat:rzsba2nl3zgsvnp437nlq7b77a

Application of Computational Intelligence Methods for the Automated Identification of Paper-Ink Samples Based on LIBS

Krzysztof Rzecki, Tomasz Sośnicki, Mateusz Baran, Michał Niedźwiecki, Małgorzata Król, Tomasz Łojewski, U Acharya, Özal Yildirim, Paweł Pławiak
2018 Sensors  
Laser-induced breakdown spectroscopy (LIBS) is an important analysis technique with applications in many industrial branches and fields of scientific research.  ...  This paper proposes the use of various computational intelligence methods to develop a reliable and fast classification of quasi-destructively acquired LIBS spectra into a set of predefined classes.  ...  Data Analysis 129 Table 2 . 2 Computational intelligence methods and their basic parameters used for LIBS spectra identification.were also tested, but they are computationally intensive and take  ... 
doi:10.3390/s18113670 fatcat:3p7ey6cw2bgwxg2pzseiejmrtq

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

S. Ganapathy, P. Yogesh, A. Kannan
2012 Computational Intelligence and Neuroscience  
For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time.  ...  The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.  ...  Data Preprocessing Agent. The data preprocessing agent uses a preprocessing technique called attribute selection algorithm for effective preprocessing.  ... 
doi:10.1155/2012/850259 pmid:23056036 pmcid:PMC3465880 fatcat:odtttnvxprdq3bt5zgsmf322rm

Research and application of network status prediction based on BP neural network for intelligent production line

Yue Ma, Le Li, Zhenyu Yin, Anying Chai, Mingshi Li, Zhiying Bi
2021 Procedia Computer Science  
The algorithm uses the ARMA prediction model to predict the network data, and calculates and predicts the entire network operation through the optimized BP neural network.  ...  The algorithm uses the ARMA prediction model to predict the network data, and calculates and predicts the entire network operation through the optimized BP neural network.  ...  Data Collection and Preprocessing This paper mainly uses the SNMP (Simple Network Management Protocol) to collect network operating data in the intelligent production line.  ... 
doi:10.1016/j.procs.2021.02.049 fatcat:pfekwhgjrrfoxd77oxxkdxq2ly

Data Quality Assurance for the Simulation Data Analysis in the EDISON-SDR

Sunil Ahn
2017 International Journal of Reliable Information and Assurance  
Recently, the convergence of computation, data, and artificial intelligence has emerged as an important factor that enables new discovery.  ...  Key requirements for efficient computational simulation data analysis are to provide a high level of quality control over the data and extraction of sufficient and consistent metadata from 1 heterogeneous  ...  Recently, the convergence of computation, data, and artificial intelligence has emerged as an important factor that enhances the efficiency of research and education and enables new discovery [2] .  ... 
doi:10.21742/ijria.2017.5.2.04 fatcat:6hx23cmzcbh3ph4wqgescg4rmq

Empirical research of hybridizing principal component analysis with multivariate discriminant analysis and logistic regression for business failure prediction

Hui Li, Jie Sun
2011 Expert systems with applications  
The optimal feature set for a specific task of BFP is determined by an empirical means of splitting all available data for thirty times to obtain the optimal preprocessing procedure for PCA.  ...  Meanwhile, the use of PCA on all available data to extract features for MDA and logit to make predictions is also employed to make a comparison.  ...  The inside principle of BFP is to find hidden patterns in data by using intelligent and statistical techniques.  ... 
doi:10.1016/j.eswa.2010.11.043 fatcat:3aztsawdp5bt7p42i4yyifqshm

Model Intelligent Agent Untuk Membantu Peran Psikolog Dalam Proses Interpretasi Jawaban Tes

Azizah Fatmawati
2021 JOINTECS (Journal of Information Technology and Computer Science)  
Therefore, this research has obejctives to design and implement the intelligent agent model in order to help psychologist to process the interpretation of test taker answer.  ...  The highest success of the answers recognized by the model is 76.67% and the highest accuracy percentage reaches 100%.  ...  Analysis Overview Diagram Scenarios merupakan proses bagaimana sesuatu akan terjadi.  ... 
doi:10.31328/jointecs.v6i1.2152 fatcat:3en2o3a4g5f5xjcosjorlfydua

A Soft Computing Approach to Knowledge Flow Synthesis and Optimization [chapter]

Tomas Rehorek, Pavel Kordik
2013 Advances in Intelligent Systems and Computing  
Kordík (FIT CTU Prague) A Soft-Computing Approach to Knowledge Flow Synthesis and Optimization September 5, 2012 9 / 15 Methodology STGP Grammar: Preprocessing, Modeling Preprocessing PCA Projection  ...  Kordík (FIT CTU Prague) A Soft-Computing Approach to Knowledge Flow Synthesis and Optimization September 5, 2012 8 / 15 Methodology STGP Grammar: Validaton Process Validation Process Preprocessing  ... 
doi:10.1007/978-3-642-32922-7_3 fatcat:w4vqgx7iz5cqbalwqr7nocyfha

Research on Patent Information Analyzing and Predicting System Based on Data Mining

Yang Liu
2015 International Journal of Hybrid Information Technology  
We designed the function structure of the system which consists of patent data preprocessing, patent data mining and patent mining results visualization.  ...  The rapid development of computer science and technology promote the transform of the patent information analysis method from the traditional previous text analysis, simple statistical analysis to data  ...  Yuan [8] et. al. explained the advantages of using data mining technology for patent intelligence analysis, and confirmed the feasibility and effectiveness of this method by using it for intelligence  ... 
doi:10.14257/ijhit.2015.8.5.23 fatcat:urr3azfjxzcj3o4tsgnawh53cm
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