Multi Criteria Mapping Based on SVM and Clustering Methods
Author | : Abhishek Diddikadi |
Publisher | : |
Total Pages | : |
Release | : 2015 |
Genre | : |
ISBN | : |
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Author | : Abhishek Diddikadi |
Publisher | : |
Total Pages | : |
Release | : 2015 |
Genre | : |
ISBN | : |
Author | : Vishwa Shanthi Eerla |
Publisher | : |
Total Pages | : |
Release | : 2016 |
Genre | : |
ISBN | : |
Author | : Management Association, Information Resources |
Publisher | : IGI Global |
Total Pages | : 1853 |
Release | : 2019-03-01 |
Genre | : Technology & Engineering |
ISBN | : 1522580557 |
Decision makers, such as government officials, need to better understand human activity in order to make informed decisions. With the ability to measure and explore geographic space through the use of geospatial intelligence data sources including imagery and mapping data, they are better able to measure factors affecting the human population. As a broad field of study, geospatial research has applications in a variety of fields including military science, environmental science, civil engineering, and space exploration. Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications explores multidisciplinary applications of geographic information systems to describe, assess, and visually depict physical features and to gather data, information, and knowledge regarding human activity. Highlighting a range of topics such as geovisualization, spatial analysis, and landscape mapping, this multi-volume book is ideally designed for data scientists, engineers, government agencies, researchers, and graduate-level students in GIS programs.
Author | : Bhattacharyya, Siddhartha |
Publisher | : IGI Global |
Total Pages | : 770 |
Release | : 2015-04-30 |
Genre | : Computers |
ISBN | : 1466682922 |
Swarm Intelligence has recently emerged as a next-generation methodology belonging to the class of evolutionary computing. As a result, scientists have been able to explain and understand real-life processes and practices that previously remained unexplored. The Handbook of Research on Swarm Intelligence in Engineering presents the latest research being conducted on diverse topics in intelligence technologies such as Swarm Intelligence, Machine Intelligence, Optical Engineering, and Signal Processing with the goal of advancing knowledge and applications in this rapidly evolving field. The enriched interdisciplinary contents of this book will be a subject of interest to the widest forum of faculties, existing research communities, and new research aspirants from a multitude of disciplines and trades.
Author | : Nikita I. Lytkin |
Publisher | : |
Total Pages | : 83 |
Release | : 2009 |
Genre | : Cluster analysis |
ISBN | : |
Two approaches have been proposed in statistical and machine learning communities in order to address the problem of uncovering clusters with complex structure. One approach relies on the development of clustering criteria that are able to accommodate increasingly complex characteristics of the data. The other approach is based on simplification of structure of data by mapping it to a different feature space via a non-linear function and then clustering in the new space. This dissertation covers three related studies: development of a novel multi-dimensional clustering method, development of non-linear mapping functions that leverage higher-order co-occurrences between features in boolean data, and applications of these mapping functions for improving the performance of clustering methods. In particular, we treat clustering as a combinatorial optimization problem of finding a partition of the data so as to minimize a certain criterion. We develop a novel multi-dimensional clustering method based on a statistically-motivated criterion proposed by J. Neyman for stratified sampling from one-dimensional data. We show that this criterion is more reflective of the underlying data structure than the seemingly similar K-means criterion when second order variability is not homogeneous between constituent subgroups. Furthermore, experimental results demonstrate that generalization of the Neyman's criterion to multi-dimensional spaces and development of the associated clustering algorithm allow for statistically efficient estimation of the grand mean vector of a population. In the framework of the mapping-based approach to discovering complex cluster structures, we introduced a novel adaptive non-linear data transformation termed Unsupervised Second Order Transformation (USOT). The novelties behind USOT are (a) that it leverages in a unsupervised manner, higher-order co-occurrences between features in boolean data, and (b) that it considers each feature in the context of probabilistic relationships with other features. In addition, USOT has two desirable properties. USOT adaptively selects features that would influence the mapping of a given feature, and preserves the interpretability of dimensions of the transformed space. Experimental results on text corpora and financial time series demonstrate that by leveraging higher-order co-occurrences between features, clustering methods achieved statistically significant improvements in USOT space over the original boolean space.
Author | : G.E. Phillips-Wren |
Publisher | : IOS Press |
Total Pages | : 604 |
Release | : 2014-05-22 |
Genre | : Business & Economics |
ISBN | : 1614993998 |
Advances in technology have resulted in new and advanced methods to support decision-making. For example, artificial intelligence has enabled people to make better decisions hrough the use of Intelligent Decision Support Systems (DSS). Emerging research in DSS demonstrates that decision makers can operate in a more timely manner using real-time data, more accurately due to data mining and 'big data' methods, more strategically by considering a greater number of factors, more precisely and inclusively due to the availability of social networking data, and with a wider media reach with video and audio technology._x000D_ _x000D_This book presents the proceedings of the IFIP TC8/Working Group 8.3 conference held at the Université Pierre et Marie Curie in Paris, France, in June 2014. Throughout its history the conference has aimed to present the latest innovations and achievements in Decision Support Systems. This year the conference looks to the next generation with the theme of new technologies to enable DSS2.0. The topics covered include theoretical, empirical and design science research; case-based approaches in decision support systems; decision models in the real-world; healthcare information technology; decision making theory; knowledge management; knowledge and resource discovery; business intelligence; group decision support systems; collaborative decision making; analytics and ‘big data’; rich language for decision support; multimedia tools for DSS; Web 2.0 systems in decision support; context-based technologies for decision making; intelligent systems and technologies in decision support; organizational decision support; research methods in DSS 2.0; mobile DSS; competing on analytics; and social media analytics._x000D_ _x000D_ The book will be of interest to all those who develop or use Decision Support Systems. The variety of methods and applications illustrated by this international group of carefully reviewed papers should provide ideas and directions for future researchers and practitioners alike.
Author | : Wong Stephen Tin Chi |
Publisher | : World Scientific Publishing Company |
Total Pages | : 400 |
Release | : 2008-01-02 |
Genre | : Science |
ISBN | : 9813106999 |
Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields.This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.
Author | : Mohammad Zakwan |
Publisher | : Elsevier |
Total Pages | : 722 |
Release | : 2022-10-22 |
Genre | : Computers |
ISBN | : 0323985173 |
Water Resource Modeling and Computational Technologies, Seventh Edition provides the reader with a comprehensive overview of the applications that computational techniques have in various sectors of water resource engineering. The book explores applications of recent modeling and computational techniques in various sectors of water resource engineering, including hydroinformatics, irrigation engineering, climate change, hydrologic forecasting, floods, droughts, image processing, GIS, water quality, aquifer mapping, basin scale modeling, computational fluid dynamics, numerical modeling of surges and groundwater flow, river engineering, optimal reservoir operation, multipurpose projects, and water resource management. As such, this is a must read for hydrologists, civil engineers and water resource managers. Presents contributed chapters from global experts in the field of water resources from both a science and engineering perspective Includes case studies throughout, providing readers with an opportunity to understand how case specific challenges can help with computational techniques Provides basic concepts as well as a literature review on the application of computational techniques in various sectors of water resources
Author | : Salvatore Corrente |
Publisher | : |
Total Pages | : 0 |
Release | : 2023 |
Genre | : |
ISBN | : |
Author | : Gwo-Hshiung Tzeng |
Publisher | : CRC Press |
Total Pages | : 404 |
Release | : 2017-08-15 |
Genre | : Business & Economics |
ISBN | : 1351680625 |
When people or computers need to make a decision, typically multiple conflicting criteria need to be evaluated; for example, when we buy a car, we need to consider safety, cost and comfort. Multiple criteria decision making (MCDM) has been researched for decades. Now as the rising trend of big-data analytics in supporting decision making, MCDM can be more powerful when combined with state-of-the-art analytics and machine learning. In this book, the authors introduce a new framework of MCDM, which can lead to more accurate decision making. Several real-world cases will be included to illustrate the new hybrid approaches.