Interdisciplinary Approaches to Information Systems and Software Engineering
- 5h 8m
- Akhouri Pramod Krishna, Alok Bhushan Mukherjee
- IGI Global
- 2019
It is now more important than ever to implement approaches and methods that can be effective in extracting meaningful information from large data sets. Although data sets may be available for different aspects of society, we may not assess the intrinsic characteristics of their behavior effectively. Additionally, frameworks are needed that can store, process, and represent the data in such a manner that can be of practical significance.
Interdisciplinary Approaches to Information Systems and Software Engineering is an essential reference publication that assesses the significance of robust information systems in characterizing events of varying nature and dimensions. Additionally, the book includes studies on the development and application of decision-making and prediction modeling frameworks using different approaches such as agent-based modeling, spatial decision support systems, and spatial data mining. Covering topics such as management information systems, knowledge discovery, and mathematical analysis, this book is ideal for professionals, researchers, and academicians in various disciplines including computer science, information technology, geographical information systems, remote sensing, and earth system sciences.
In this Book
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Soil Quality Assessment Using Analytic Hierarchy Process (AHP): A Case Study
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IT Governance or IT Outsourcing: Is There a Clear Winner?
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Project Teamwork Assessment and Success Rate Prediction Through Meta-Heuristic Algorithms
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Systematic Model for Decision Support System
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Identification of Tectonic Activity and Fault Mechanism from Morphological Signatures
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Natural Hazard: Tropical Cyclone – Evaluation of HE and IMSRA Over CS KYANT
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Segmentation of Different Tissues of Brain from MR Image
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Sentilyser: Embedding Voice Markers in Homeopathy Treatments
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Intelligent Information System for Academic Institutions: Using Big Data Analytic Approach
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Developing Logistic Regression Models to Identify Salt-Affected Soils Using Optical Remote Sensing
