Computational intelligence in data mining : proceedings of the International Conference on CIDM, 10-11 December 2016 / Himansu Sekhar Behera, Durga Prasad Mohapatra, editors.
By: (3rd : International Conference on "Computational Intelligence in Data Mining" ((3rd : 2016 : Bhubaneswar, India))
Contributor(s): Behera, Himansu Sekhar,, editor literario
| Mohapatra, Durga Prasad,, editor literario
Material type:
E-bookSeries: (Advances in intelligent systems and computing, 2194-5357 ; volume 556).Publisher: Singapore : Springer, 2017Description: 1 recurso en línea (xix, 847 páginas) : ilustraciones.ISBN: 9789811038730; 9789811038747; 9811038732; 9811038740.Subject: Inteligencia artificial
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | Q342 .C667 2017 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.20023651 |
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Preface; Acknowledgements; About the Conference; Contents; About the Editors; 1 Safety and Crime Assistance System for a Fast Track Response on Mobile Devices in Bhubaneswar; Abstract; 1 Introduction; 2 Problem Statement; 3 Current Mechanism of Response to Crimes; 4 How the Situation can be Tackled?; 4.1 Victim at Center Approach; 4.2 Information Passing in Victim at Center Approach; 5 Safety and Crime Assistance System; 5.1 SCAS Architecture; 5.2 SCAS Advantages in Accidental Scenes; 5.3 Technical Architecture and Feasibility of SCAS; 6 Issues.
3 Proposed Algorithm4 Experimental Set up and Result Analysis; 4.1 Parameter Set up; 4.2 Dataset Information; 4.3 Experimental Results and Analysis; 5 Conclusion and Future Work; References; A Study of Dimensionality Reduction Techniques with Machine Learning Methods for Credit Risk Prediction; 1 Introduction; 2 Literature Review; 3 Methodology; 3.1 Information Gain; 3.2 Gain Ratio; 3.3 Principle Component Analysis; 3.4 Linear Discriminant Analysis; 3.5 Proposed Method; 4 Experiments; 4.1 Data Set Description; 4.2 Performance Measures; 5 Results and Analysis; 6 Conclusion; References.
3.2 Data Preprocessing3.3 Data Mining; 3.4 Data Visualization; 4 Experiments and Results; 5 Conclusion and Future Work; Acknowledgements; References; 4 Classical and Evolutionary Image Contrast Enhancement Techniques: Comparison by Case Studies; Abstract; 1 Introduction; 2 Procedure; 2.1 Transformation Function and Objective Function Used; 2.1.1 Algorithm for GA Based Approach; 2.1.2 Implementation of ABC Algorithm; 3 Results and Discussion; 3.1 Visual Comparison; 3.2 Quantitative Comparison; 3.2.1 Entropy; 3.2.2 Fitness Value; 3.2.3 SNR; 4 Conclusions; References.
7 Process Workflow, Login Page, and Registration Page8 Conclusion; References; 2 Major Global Energy (Biomass); Abstract; 1 Introduction; 2 Biomass as a Renewable Resource; 2.1 Biomass Energy -Bio Power; 2.2 Environment Impact; 2.3 Working of Biomass Heating Plant; 2.4 Various Issue; 2.5 Benefits of Biomass Heating; 2.6 Disadvantage; 2.7 Application; 3 Conclusion; Acknowledgements; References; 3 Detecting Targeted Malicious E-Mail Using Linear Regression Algorithm with Data Mining Techniques; Abstract; 1 Introduction; 2 Literature Survey; 3 Design and Implementation; 3.1 Data Importing.
Cost Effectiveness Analysis of a Vertical Midimew-Connected Mesh Network (VMMN)1 Introduction; 2 Interconnection of Vertical-Midimew Connected Mesh Network; 2.1 Basic Module; 2.2 Higher Level Network; 3 Cost Effectiveness Analysis; 3.1 Cost Parameters; 3.2 Distance Parameters; 3.3 Packing Density; 3.4 Message Traffic Density; 3.5 Cost Effective Factor; 3.6 Time-Cost Effective Factor; 4 Conclusion; References; 6 Cluster Analysis Using Firefly-Based K-means Algorithm: A Combined Approach; Abstract; 1 Introduction; 2 Preliminaries; 2.1 K-means Algorithm; 2.2 Firefly Algorithm (FA).
The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 - 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.
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