[PDF] Machine Learning And Data Mining In Aerospace Technology eBook

Author : Aboul Ella Hassanien
Publisher : Springer
Page : 232 pages
File Size : 49,92 MB
Release : 2019-07-02
Category : Technology & Engineering
ISBN : 3030202127

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This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the ‘eagle eyes’ that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites – which can determine satellites’ current status and predict their failure based on telemetry data – is one of the most important current issues in aerospace engineering. This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.

Author : Vignesh, U.
Publisher : IGI Global
Page : 272 pages
File Size : 19,76 MB
Release : 2024-03-05
Category : Technology & Engineering
ISBN :

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The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience. Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field.

Author : Aboul-Ella Hassanien
Publisher : Springer Nature
Page : 880 pages
File Size : 17,9 MB
Release : 2020-03-23
Category : Technology & Engineering
ISBN : 3030442896

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This book presents the proceedings of the 1st International Conference on Artificial Intelligence and Computer Visions (AICV 2020), which took place in Cairo, Egypt, from April 8 to 10, 2020. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, intelligent systems and applications, and intelligent networks.

Author : Md. Shahriare Satu
Publisher : Springer Nature
Page : 597 pages
File Size : 20,99 MB
Release : 2023-06-10
Category : Computers
ISBN : 303134619X

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The two-volume set LNICST 490 and 491 constitutes the proceedings of the First International Conference on Machine Intelligence and Emerging Technologies, MIET 2022, hosted by Noakhali Science and Technology University, Noakhali, Bangladesh, during September 23–25, 2022. The 104 papers presented in the proceedings were carefully reviewed and selected from 272 submissions. This book focuses on theoretical, practical, state-of-art applications, and research challenges in the field of artificial intelligence and emerging technologies. It will be helpful for active researchers and practitioners in this field. These papers are organized in the following topical sections: imaging for disease detection; pattern recognition and natural language processing; bio signals and recommendation systems for wellbeing; network, security and nanotechnology; and emerging technologies for society and industry.

Author : Jesus Salcedo
Publisher : Packt Publishing Ltd
Page : 247 pages
File Size : 44,47 MB
Release : 2019-04-30
Category : Computers
ISBN : 1838821554

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Get efficient in performing data mining and machine learning using IBM SPSS Modeler Key FeaturesLearn how to apply machine learning techniques in the field of data scienceUnderstand when to use different data mining techniques, how to set up different analyses, and how to interpret the resultsA step-by-step approach to improving model development and performanceBook Description Machine learning (ML) combined with data mining can give you amazing results in your data mining work by empowering you with several ways to look at data. This book will help you improve your data mining techniques by using smart modeling techniques. This book will teach you how to implement ML algorithms and techniques in your data mining work. It will enable you to pair the best algorithms with the right tools and processes. You will learn how to identify patterns and make predictions with minimal human intervention. You will build different types of ML models, such as the neural network, the Support Vector Machines (SVMs), and the Decision tree. You will see how all of these models works and what kind of data in the dataset they are suited for. You will learn how to combine the results of different models in order to improve accuracy. Topics such as removing noise and handling errors will give you an added edge in model building and optimization. By the end of this book, you will be able to build predictive models and extract information of interest from the dataset What you will learnHone your model-building skills and create the most accurate modelsUnderstand how predictive machine learning models workPrepare your data to acquire the best possible resultsCombine models in order to suit the requirements of different types of dataAnalyze single and multiple models and understand their combined resultsDerive worthwhile insights from your data using histograms and graphsWho this book is for If you are a data scientist, data analyst, and data mining professional and are keen to achieve a 30% higher salary by adding machine learning to your skillset, then this is the ideal book for you. You will learn to apply machine learning techniques to various data mining challenges. No prior knowledge of machine learning is assumed.

Author : Vaclav Skala
Publisher : Springer Nature
Page : 909 pages
File Size : 41,93 MB
Release : 2022-08-01
Category : Technology & Engineering
ISBN : 9811923477

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This book is a compilation of peer reviewed papers presented at International Conference on Machine Intelligence and Data Science Applications (MIDAS 2021), held in Comilla University, Cumilla, Bangladesh during 26 – 27 December 2021. The book covers applications in various fields like image processing, natural language processing, computer vision, sentiment analysis, speech and gesture analysis, etc. It also includes interdisciplinary applications like legal, healthcare, smart society, cyber physical system and smart agriculture, etc. The book is a good reference for computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.

Author : Ioannis K. Hatzilygeroudis
Publisher : Springer Nature
Page : 204 pages
File Size : 28,62 MB
Release : 2023-02-06
Category : Technology & Engineering
ISBN : 3031223713

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This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms. Integrated or Hybrid Machine Learning methodologies combine together two or more Machine Learning approaches achieving higher performance and better efficiency when compared to those of their constituent components and promising major impact in science, technology and the society. The book consists of an editorial note and an additional eight chapters and is organized into two parts, namely: (i) Recent Application Areas of Fusion of Machine Learning Paradigms and (ii) Applications that can clearly benefit from Fusion of Machine Learning Paradigms. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.

Author : Abhishek Kumar
Publisher : CRC Press
Page : 241 pages
File Size : 18,83 MB
Release : 2022-03-09
Category : Computers
ISBN : 1000539970

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In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.