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Deep learning: concepts, methodologies, tools, and applications / Information Resources Management Association. — 1 online resource — <URL:http://elib.fa.ru/ebsco/2257552.pdf>.

Record create date: 6/7/2019

Subject: Data mining.; Machine learning — Industrial applications.; Big data.; Invisible Web.; Big data.; Data mining.; Invisible Web.; Machine learning — Industrial applications.

Collections: EBSCO

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"This book is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis"--.

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Table of Contents

  • Title Page
  • Copyright Page
  • Editorial Advisory Board
  • List of Contributors
  • Table of Contents
  • Preface
  • Section 1: Fundamental Concepts and Theories
    • Chapter 1: Artificial Neural Network What-If Theory
    • Chapter 2: A Brief Review on Deep Learning and Types of Implementation for Deep Learning
    • Chapter 3: Introduction to Machine Learning
    • Chapter 4: A Comparative Analysis of a Novel Anomaly Detection Algorithm with Neural Networks
    • Chapter 5: Complex-Valued Neural Networks
    • Chapter 6: Ant Colony Optimization Applied to the Training of a High Order Neural Network with Adaptable Exponential Weights
    • Chapter 7: A Comparative Study of Neural Network and Fuzzy Logic Control Based Active Shunt Power Filter for 400 Hz Aircraft Electric Power System
  • Section 2: Development and Design Methodologies
    • Chapter 8: Hierarchical Method Based on Artificial Neural Networks for Power Output Prediction of a Combined Cycle Power Plant
    • Chapter 9: A Model Augmenting Credit Risk Management in the Banking Industry
    • Chapter 10: Prediction of Biosorption Capacity Using Artificial Neural Network Modeling and Genetic Algorithm
    • Chapter 11: An ANN Model for Predicting the Quantity of Lead and Cadmium Ions in Industrial Wastewater
    • Chapter 12: Artificial Neural Network (ANN) in Network Reconfiguration for Improvement of Voltage Stability
    • Chapter 13: ANN Modeling of Motional Resistance for Micro Disk Resonator
    • Chapter 14: A Prescriptive Stock Market Investment Strategy for the Restaurant Industry using an Artificial Neural Network Methodology
    • Chapter 15: An Adaptive Second Order Neural Network with Genetic-Algorithm-based Training (ASONN-GA) to Forecast the Closing Prices of the Stock Market
    • Chapter 16: Identification of Helicopter Dynamics based on Flight Data using Nature Inspired Techniques
    • Chapter 17: Efficient Imbalanced Multimedia Concept Retrieval by Deep Learning on Spark Clusters
    • Chapter 18: Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)
    • Chapter 19: A Decision Making Method Based on Society of Mind Theory in Multi-Player Imperfect Information Games
    • Chapter 20: New CICT Framework for Deep Learning and Deep Thinking Application
    • Chapter 21: A Deep Learning Approach for Hepatocellular Carcinoma Grading
    • Chapter 22: A Deep Learning Solution for Multimedia Conference System Assisted by Cloud Computing
    • Chapter 23: Learning from Unbalanced Stream Data in Non-Stationary Environments Using Logistic Regression Model
    • Chapter 24: Discovering Gathering Pattern Using a Taxicab Service Rate Analysis Method based on Neural Network
    • Chapter 25: Analysis of Gait Flow Image and Gait Gaussian Image Using Extension Neural Network for Gait Recognition
    • Chapter 26: A Learning-based Neural Network Model for the Detection and Classification of SQL Injection Attacks
  • Section 3: Tools and Technologies
    • Chapter 27: A Hybrid NIDS Model Using Artificial Neural Network and D-S Evidence
    • Chapter 28: Speckle Noise Filtering Using Back-Propagation Multi-Layer Perceptron Network in Synthetic Aperture Radar Image
    • Chapter 29: Simulation of Stock Prediction System using Artificial Neural Networks
    • Chapter 30: Optimization of Cutting Parameters for AISI H13 Tool Steel by Taguchi Method and Artificial Neural Network
    • Chapter 31: Neural Networks and Statistical Analysis for Time and Cost Prediction Models of Urban Redevelopment Projects
    • Chapter 32: Multi-Sensor Motion Fusion Using Deep Neural Network Learning
    • Chapter 33: ePortfolios as a Tool for Integrative Learning
    • Chapter 34: Digital Investigation of Cybercrimes Based on Big Data Analytics Using Deep Learning
    • Chapter 35: Novel Scalable Deep Learning Approaches for Big Data Analytics Applied to ECG Processing
    • Chapter 36: An Investigation Into the Efficacy of Deep Learning Tools for Big Data Analysis in Health Care
    • Chapter 37: Efficient Large-Scale Stance Detection in Tweets
    • Chapter 38: An Analysis in Tissue Classification for Colorectal Cancer Histology Using Convolution Neural Network and Colour Models
    • Chapter 39: Spam Detection on Social Media Using Semantic Convolutional Neural Network
    • Chapter 40: Counterfactual Autoencoder for Unsupervised Semantic Learning
    • Chapter 41: Semantic Similarity Measurement Using Knowledge-Augmented Multiple-prototype Distributed Word Vector
    • Chapter 42: Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System
  • Section 4: Utilization and Applications
    • Chapter 43: Feature Extraction of Video Using Artificial Neural Network
    • Chapter 44: Optimization Through Nature-Inspired Soft-Computing and Algorithm on ECG Process
    • Chapter 45: Optimal Model Parameters of Inverse Kinematics Solution of a 3R Robotic Manipulator Using ANN Models
    • Chapter 46: Application of Artificial Neural Networks to Reliable Nuclear Data for Nonproliferation Modeling and Simulation
    • Chapter 47: Application of Artificial Neural Networks in Predicting the Degradation of Tram Tracks Using Maintenance Data
    • Chapter 48: Forecasting of Electricity Demand by Hybrid ANN-PSO Models
    • Chapter 49: Backpropagation Neural Network for Interval Prediction of Three-Phase Ampacity Level in Power Systems
    • Chapter 50: Meteorological Data Forecast using RNN
    • Chapter 51: Automated Whale Blow Detection in Infrared Video
    • Chapter 52: Business Applications of Deep Learning
    • Chapter 53: Classifying Behaviours in Videos with Recurrent Neural Networks
    • Chapter 54: Case Studies in Amalgamation of Deep Learning and Big Data
    • Chapter 55: Big Spectrum Data and Deep Learning Techniques for Cognitive Wireless Networks
    • Chapter 56: Investigation on Deep Learning Approach for Big Data
    • Chapter 57: Depth Maps and Deep Learning for Facial Analysis
    • Chapter 58: Resource Scheduling and Load Balancing Fusion Algorithm with Deep Learning Based on Cloud Computing
    • Chapter 59: A Survey on Supervised Convolutional Neural Network and Its Major Applications
    • Chapter 60: Use of Images of Leaves and Fruits of Apple Trees for Automatic Identification of Symptoms of Diseases and Nutritional Disorders
    • Chapter 61: Using MLP Neural Networks to Detect Late Blight in Brazilian Tomato Crops
    • Chapter 62: Identifying the Antecedents of Children's Market Using Neural Network
    • Chapter 63: Translation of Medical Texts using Neural Networks
    • Chapter 64: Discrete-Time Decentralized Inverse Optimal Higher Order Neural Network Control for a Multi-Agent Omnidirectional Mobile Robot
    • Chapter 65: Classification of Breast Thermograms Using Statistical Moments and Entropy Features with Probabilistic Neural Networks
  • Section 5: Organizational and Social Implications
    • Chapter 66: BP-Neural Network for Plate Number Recognition
    • Chapter 67: Using Functional Link Artificial Neural Network (FLANN) for Bank Credit Risk Assessment
    • Chapter 68: Parkinson's Disease Detection with Gait Recognition using Soft Computing Techniques
    • Chapter 69: Predicting Hypoglycemia in Diabetic Patients Using Time-Sensitive Artificial Neural Networks
    • Chapter 70: A Method for Identifying Fatigue State of Driver's Face Based on Improved AAM Algorithm
    • Chapter 71: Comparing Predictive Ability of Classifiers in Forecasting Online Buying Behaviour
    • Chapter 72: Neural Network Modeling for Organizational Psychology
    • Chapter 73: Human Skin Detection in Color Images Using Deep Learning
    • Chapter 74: Deep Learning and Online Education as an Informal Learning Process
    • Chapter 75: Efficiently Processing Big Data in Real-Time Employing Deep Learning Algorithms
    • Chapter 76: Deep-Learning-Based Classification and Diagnosis of Alzheimer's Disease
    • Chapter 77: Sentiment Recognition in Customer Reviews Using Deep Learning
    • Chapter 78: Fall Behavior Recognition Based on Deep Learning and Image Processing
    • Chapter 79: Classification Approach for Breast Cancer Detection Using Back Propagation Neural Network
    • Chapter 80: Neural Network Based Automated System for Diagnosis of Cervical Cancer
    • Chapter 81: An Adaptive Neural Network for the Cost Estimation of E-Learning Projects in the United Kingdom
  • Section 6: Critical Issues and Challenges
    • Chapter 82: A Hybrid Approach Based on Genetic Algorithm and Particle Swarm Optimization to Improve Neural Network Classification
    • Chapter 83: Phased Method for Solving Multi-Objective MPM Job Shop Scheduling Problem
    • Chapter 84: Cognitive Intelligence
    • Chapter 85: Research on Methodology of Correlation Analysis of Sci-Tech Literature Based on Deep Learning Technology in the Big Data
    • Chapter 86: Research on O2O Platform and Promotion Algorithm of Sports Venues Based on Deep Learning Technique
    • Chapter 87: Learner-Centered Pedagogies
    • Chapter 88: Software Defect Prediction Using Genetic Programming and Neural Networks
    • Chapter 89: Modified Differential Evolution Algorithm Based Neural Network for Nonlinear Discrete Time System
    • Chapter 90: Vector Optimization of Neural Network Classifiers
  • Section 7: Emerging Trends
    • Chapter 91: Towards Developing the Piece-Wise Linear Neural Network Algorithm for Rule Extraction
    • Chapter 92: Learning about Complex Systems from the Bottom Up
  • Index

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