Handbook of Research on Machine Learning Innovations and Trends, Volume I

  • 11h 19m
  • Aboul Ella Hassanien, Tarek Gaber (eds)
  • IGI Global
  • 2017

Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression.

The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.

In this Book

  • T-Spanner Problem: Genetic Algorithms for the T-Spanner Problem
  • Breast Cancer Diagnosis Using Relational Discriminant Analysis of Malignancy- Associated Changes
  • Early-Stage Ovarian Cancer Diagnosis Using Fuzzy Rough Sets with SVM Classification
  • Data Storage Security Service in Cloud Computing: Challenges and Solutions
  • Workload Management Systems for the Cloud Environment
  • Segmentation of Brain Tumor from MRI Images Based on Hybrid Clustering Techniques
  • Localization and Mapping for Indoor Navigation: Survey
  • Enzyme Function Classification: Reviews, Approaches, and Trends
  • A Review of Vessel Segmentation Methodologies and Algorithms: Comprehensive Review
  • Cloud Services Publication and Discovery
  • Enhancement of Data Quality in Health Care Industry: A Promising Data Quality Approach
  • Investigation of Software Reliability Prediction Using Statistical and Machine Learning Methods
  • Fuzzy-Based Approach for Reducing the Impacts of Climate Changes on Agricultural Crops
  • Directional Multi-Scale Stationary Wavelet-Based Representation for Human Action Classification
  • Data Streams Processing Techniques Data Streams Processing Techniques
  • A Preparation Framework for EHR Data to Construct CBR Case-Base
  • Detecting Significant Changes in Image Sequences
  • Multiple Sequence Alignment Optimization Using Meta-Heuristic Techniques
  • Recent Survey on Medical Image Segmentation
  • Machine Learning Applications in Breast Cancer Diagnosis
  • A Hybrid Optimization Algorithm for Single and Multi-Objective Optimization Problems
  • Neuro-Imaging Machine Learning Techniques for Alzheimer's Disease Diagnosis
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